We are scientists.
We are engineers.
We are drug hunters. We are insitro.

Adam Riesselman

Adam Riesselman is a computational biologist with experience in developing powerful, interpretable machine learning models for complex biological data. At insitro, Adam is focused on integrating high-throughput measurements with new scalable algorithms to understand disease.

Adam received a BA in Biochemistry: Cell and Molecular Biology from Drake University and his PhD in Biomedical Informatics at Harvard University with Debora Marks as a Department of Energy Computational Science Graduate Fellow. There he developed new statistical models for unsupervised mutation effect prediction from evolutionary data, de novo protein structure prediction via simulation, protein library design with improved biomolecular properties, and small molecule production optimization utilizing biosynthetic pathway engineering.

When not at the computer, Adam likes to cook and enjoy the outdoors by hiking, gardening, and biking.

Adriana Tajonar

Adriana is the Head of External Innovation at insitro where she searches for technologies, collaborations, and expertise to accelerate and maximize insitro’s research and development efforts.

Prior to joining insitro, Adriana was a Principal at The Column Group (TCG), a life science venture capital firm. In her role, she focused on ideation, formation, and launch of several companies in the TCG portfolio, including Accent Therapeutics and A2 Biotherapeutics, and served as board director or observer of these and other companies.

Adriana was also previously Entrepreneurship Program Manager at QB3 (California Institute for Quantitative Biosciences) where she managed the Startup in a Box Program. In this role, she evaluated and guided over 200 teams of scientists from top institutions in California towards starting companies in the life sciences.

Adriana obtained her PhD in the laboratory of Prof. Douglas Melton at Harvard University where she studied mechanisms of self-renewal and survival in human embryonic stem cells. Previously, Adriana did research in the lab of Prof. Rudolf Jaenisch as an undergraduate at the Massachusetts Institute of Technology.

In her free time, Adriana enjoys spending time with friends and family, traveling, visiting museums and exercising.

Ahmed Sandakli

Ahmed Sandakli is an Associate Scientist in Process Engineering, focused on implementing automation solutions for workflows across multiple functions.
Prior to joining insitro, Ahmed worked on optimizing, automating, and processing samples across several genomic assays at Verily Life Sciences. Before then, he was a part of the Genomics Platform at The Broad Institute, working on high-throughput SNP microarrays and NGS processing.

In his spare time, Ahmed enjoys hiking, weightlifting, yoga, and cooking.

Ajamete “Aj” Kaykas

As Chief Technology Officer, Aj is responsible for producing high-quality data sets to use in for machine learning-based target and drug discovery. He leads insitro’s wet lab activities which consists of functional genomics, disease modeling, phenotyping, automation, and process engineering.

Ajamete has spent over 28 years in both industry and academia, working in the areas of proteomics, genomics, and stem cell biology. Before joining insitro, Aj led the early target discovery team at Novartis Institutes for Biomedical Research in the Neuroscience unit. His team efforts have led to the discovery of multiple new disease targets and the development of better predictive preclinical models. He conducted his postdoc with Dr. Randy Moon at the University of Washington/Howard Hughes Medical Institute on Wnt-signaling. While in Randy’s lab, he conducted one of the first ever genome-wide RNAi screens and studied the role of Wnt-signaling in human disease and stem cell biology. He did his graduate work at the University of Wisconsin-Madison in Dr. Bill Sugden’s lab where he studied virology, immunology, and oncology.

In his free time, Aj enjoys traveling, kayaking, sailing, biking, making whiskey and most of all his family.

Albert Kim

Albert utilizes different automation technologies to ensure quality data generation from many of insitro’s scientific processes. This includes integrating specific assays onto automation, onboarding tools for efficient execution, and maintaining an environment for seamless research operations.

After graduating with his B.S. in Biochemistry and Philosophy from Wisconsin-Madison he started at Abbott Laboratories as an Associate Scientist focusing on instrument and assay validation for their diagnostics platform. After working in a big company environment, he joined Transcriptic, where he helped w/ assay integration and automation.

In his free time, Albert enjoys watching the NBA and trying out different banana bread recipes.

Alex Urrutia

Alex is an immunologist with broad and long-standing experience in basic research, pre-clinical model development and translational research to understand the immune response and its associated inflammation in various pathological contexts (i.e. infectious diseases, cancer).

At insitro, Alex is a Sr. Scientist in the translational assay group helping guide the team with a focus on identifying and validating intermediate phenotypes of disease processes. She is working in close collaboration with the genetic, disease modeling, process engineering and machine learning modules of insitro to accelerate and scale-up the interpretation of the output.

Prior to joining insitro, Alex transitioned from academia to Biopharma in 2017 as a Senior Scientific Researcher at Genentech in the Cancer Immunology department. She implemented translational tools with the aim of accelerating biomarker discovery in the context of immune checkpoint interventions. Additionally, Alex was a biological lead for the development of small/biological molecules in the space of anti-tumor immunity.

Alex was born in Paris, France and received her Ph.D. in Immunology and Physiopathology from the University Pierre et Marie Curie at the Institut Pasteur where she developed a standardized and high-throughput workflow for transcriptomic analysis of a syringe-based whole blood stimulation system to support the population-based integrative approach of the “Milieu Interieur” consortium.

In her free time, Alex enjoys listening to music, dancing, trying out new cuisines and exploring the outside world with her kids.

Alice Starr

Alice Starr is a software engineer, with experience designing and architecting scientific research applications. At insitro, Alice is focused on laboratory information and data architecture, making sure we make the most of our generated data. Prior to insitro, she was at Genentech, designing data solutions for the translational research and pathology organizations. She loves to tackle data challenges to advance science, which provides constant opportunities to learn.
Alice received a BS and MS in Mathematics and Computer Science from EPF, France and ITESM, Mexico.

When not working or playing with her two daughters, Alice likes to read and be outdoors as much as possible, walking or running on the beautiful California trails.

Alicia Cuevas

Alicia is a research associate focusing on developing and optimizing workflows to use on insitro’s automated systems.

Alicia was previously responsible for screening thousands of modified strains per week in a highly automated environment. She also spent time on a process quality management team where she worked with automation engineers, lab users, and software developers to build and test a paperless equipment management platform. Prior to her experience in process quality management, she worked with a small team creating one of the world’s largest induced pluripotent stem cell banks. The project was funded by a CIRM grant that resulted from the passing of proposition 71. Her focus was automating workflows on an integrated system and designing experiments focused on optimizing high throughput systems.

In her free time Alicia enjoys hiking, camping, reading, & museums.

Alicia Lee

Alicia is Senior Research Associate in High-Throughput Biology and she is working on differentiating iPSCs into appropriate cell types for disease modeling to produce data sets for insitro’s machine learning platform.

Prior to joining insitro, Alicia was working on cell therapies for neurodegenerative diseases at Neurona Therapeutics. Before then she was at the Gladstone Institutes working on cellular models of neurodegenerative diseases. Alicia has a bioengineering background and obtained her B.S. and M. Eng. in Bioengineering from UCSD.

In her spare time, Alicia enjoys reading, hiking and traveling.

Allison Lai

Allison Lai is the Controller / VP, Finance at insitro. She brings with her 18 years of experience in accounting and finance operations with most of her experience in the life sciences industry.

Prior to joining insitro, Allison served as VP, Finance & Controller at Adicet Bio, a pre-clinical stage biotechnology company engaged in the design and development of immunotherapies for cancer and other diseases, where she helped build and scale the accounting team. Before then, Allison was at Genomic Health, a global provider of genomic-based diagnostic tests, where she was most recently the Senior Director of Accounting and supported the organization’s increasing headcount and international growth. Allison has also held increasing roles at Affymax, a publicly-traded biotechnology company, and she started her career at PriceWaterhouseCoopers LLP in their audit and assurance practice.

Allison received her BA in Business Management Economics from the University of California, Santa Cruz and she is a Certified Public Accountant in the State of California.

Outside of the office, Allison is constantly chasing after her two sons and cheering on the Golden State Warriors.

Amy Lu

Amy is interested in creating machine learning methods with the needs of biological data in mind.

At insitro, Amy is researching and developing generalizable and interpretable models for data collected under different biological conditions.

She obtained her MSc in Computer Science at the University of Toronto/Vector Institute as a recipient of the NSERC CGS-M award, where she worked on developing self-supervised protein representation methods, benchmarking out-of-sample generalization in microscopy image classifiers, and quantifying algorithmic bias in word embeddings of clinical notes. She partially completed her Masters as a visiting student in Dr. Anshul Kundaje’s group at Stanford University on an NSERC scholarship, working on domain adaptation in transcription factor binding.

Prior to her MSc, Amy was a research intern at Harvard Medical School/Boston Children’s Hospital, working on interpretable machine learning models to discover disease-associated variants, and at EPFL, where she worked on molecular dynamics simulations. She obtained her BSc from the University of Waterloo.

In her spare time, Amy enjoys playing the piano, solo traveling, visiting museums, and eating 90% dark chocolate.

Anna Shcherbina

Anna works with insitro’s Data Science and Machine Learning team, developing machine learning approaches to study the role of noncoding variation in disease. Her current work focuses on building deep learning capabilities to uncover additional candidate drug targets from imputed GWAS studies across several cohorts.

Anna recently completed her PhD in Biomedical Data Science from Stanford, where she was a BioX and NVIDIA Fellow. Her PhD work focused on developing deep learning models to study gene regulation and to functionally characterize non coding variation. She also worked on statistical analysis methods for wearable and mobile health data, such as accelerometry data. Prior to completing her PhD, Anna worked on metagenomic data analysis at MIT Lincoln Laboratory.

In her free time, Anna likes to read science fiction and fantasy novels, spend time with her cat, and go hiking.

Anne Baldwin

Anne is an automation engineer with experience developing methods and the tools needed to scale them. As a member of the Process Engineering team at Insitro, Anne works to enable the production of high quality biological data for downstream machine learning analysis and data science. She is frequently engaged in system development, process development, and developing the tools and methods that ensure the automated systems are producing the highest quality data.

Anne worked early in her career in GMP assay development for potency testing of antibody therapies, then scaled the assay development and testing through the use of automation. She transitioned into laboratory automation engineering full time when she became the lead system specialist in the nucleic acid sample management group in gRED at Genentech. There she managed many different integrated automated systems to transform, purify, store and deliver plasmids, proteins and other nucleic acid collections to the research organization. After that she transitioned to Synthego to lead their automation group to scale CRISPR oligo manufacturing and within 1 year built the integrated cell handling platforms to support nation scale cell line engineering services.
Anne holds a B.S. in Biological Sciences from the University of California, Davis.

Outside of work Anne enjoys long walks on the beach, sipping pina coladas and getting caught in the rain. She also enjoys cooking, baking, playing games and Dungeons and Dragons.

Baris Ungun

Baris works within insitro’s Data Science and Machine learning team, where he applies his dual training in medicine and convex optimization to problems in bioinformatic modeling of disease states and scalable algorithmic approaches to interpreting petabyte-scale genomic and imaging datasets.

Baris grew up in the Bay Area. In a previous life, he studied Chemical Engineering at Princeton and worked in research and development at Gilead Sciences. He then spent the majority of the last decade in an MD-PhD program at Stanford, where he worked with Lei Xing and Stephen Boyd on large-scale computing problems in radiation therapy treatment planning. His research focus was on developing high-performance convex approximations to components of the massive, nonconvex problems arising in medicine and biomedicine.

Outside of work life interests include: the ocean, reading (mostly fiction), and seeing as much live music as possible.

Bobby Leitmann

Bobby is a research associate that supports the development and integration of image-based assays to further insitro’s drug discovery.

Bobby got his B.S. in Biological Engineering at the University of Georgia (UGA) and did some hands on research focusing on stem cell therapies. He became a double Dawg when he got his M.S. in Engineering at UGA with a focus on Cell Manufacturing Research using high content imaging in the Mortensen lab.

In his free time Bobby likes to spend time with his partner and two crazy kitties, hike, dance, gardening and practice jiu jitsu.

Bowen Liu

Bowen Liu is a computational chemist with experience working at the interface of chemistry, drug discovery, and machine learning.

Bowen grew up in New Zealand and received his dual BSc/BCom undergraduate degrees at The University of Auckland majoring in Chemistry, Applied Mathematics, Finance and Accounting. Afterwards, he moved to the Bay Area and completed his Ph.D in Chemistry at Stanford under the supervision of Jure Leskovec and Vijay Pande. At Stanford, Bowen focused on developing machine learning methods for problems in small molecule drug discovery and lead optimization, namely molecular property prediction, molecule generation, and chemical reaction prediction.

In his spare time, Bowen enjoys reading, playing video games, and going on staycations.

Britt Huber

Britt Huber is the Vice President of People at insitro. She brings with her over 15 years of experience in People Operations / Human Resources, Organizational Development and business management leadership roles, in
the life sciences and technology industries, both in California and in Switzerland. Britt is passionate about developing mission-driven companies and coaching its people to evoke excellence.

Prior to joining insitro, Britt served as VP, People & Organizational Development at PaxVax, Inc., a fully-integrated specialty vaccines company, which she helped build and scale from start-up to a global, commercial stage company that was acquired by Emergent BioSolutions in 2018. Before then, Britt was the VP of People at Kiva, the world’s first personal micro-lending platform, where she supported the organization’s doubling in size, internationalization, and creation of an awesome culture.

Britt holds an MBA from St. Mary’s College, Moraga, California and a Senior Professional in Human Resources (SPHR)-Certification. She’s also a Certified Professional Coach from New Ventures West, San Francisco, California. She speaks English, German, French, Italian, and Spanish.

When Britt is not cheer-leading the people she serves, she loves to explore the world traveling, enjoys the great outdoors while running, biking, hiking, swimming, skating,painting or striking a yoga pose somewhere.

Carlota Pereda

Carlota is a research associate developing in vitro disease models for neurological disorders to generate large-scale data for machine learning-enabled drug discovery.

Carlota previously worked on scaling high-throughput 3D models for neurodegenerative disorders using automation. She led drug discovery screens on the platform and performed target identification experiments with hit drug candidates. She also has experience setting up lab operations from the ground up and managing grants. Carlota received her B.S. with Honors in Biotechnology at Brown University, with research in cardiac tissue engineering and her M.S. in Biomedical Engineering at Columbia University with mechanical engineering research in medical device design and fabrication.

In her spare time, Carlota likes to spend time helping entrepreneurs, gardening and dancing to any type of music.

Chelcy Hedgspeth

Chelcy serves as the Recruiting Coordinator at insitro where she combines her experience in recruiting with her passion for efficiency and organization.

Chelcy has always had an interest in health and science and attended Virginia Commonwealth University, where she completed her Bachelors of Science in Kinesiology. Previous to insitro, she served as a Recruitment Consultant building strong relationships throughout the biotech industry.

Outside of work, Chelcy can be found befriending unwitting dogs and soaking up any sun she is given. She enjoys the outdoors, good food, good music, and good company.

Chengyun Lee

As a Scientific Specialist, Chengyun contributes to iPSCs differentiation and disease modeling projects.

Chengyun received his B.S. in Clinical Laboratory Sciences and Medical Biotechnology at the National Taiwan University, Taiwan and participated in a number of research in the stem cell biology field. He pursued his M.S. in Stem Cell Biology at the University of Minnesota.
After graduation, Chengyun joined Ben Barres’s lab at Stanford University as a Life Science Research Professional.

Prior to joining insitro, Chengyun worked at Neucyte where he performed compound screening and dosing experiments and participated in iPS-based neurological platform upgrade program and drug discovery efforts.

In his spare time, Chengyun enjoys reading and listening to audiobooks.

Chris Probert

Chris Probert is a computational biologist and computer scientist with extensive experience building deep learning models for genomic data. His current work at insitro is focused on enabling large-scale deep learning on functional genomic data produced by the high throughput biology platform.

Chris is a PhD candidate in Computational Biology (Genetics) at Stanford working with Anshul Kundaje and Christina Curtis where he was an NSF Fellow and an Accel Innovation Scholar. His PhD work focused on large-scale machine learning analysis of functional genomics datasets, including imputation and superresolution of genome-wide epigenomic signals, unsupervised methods for learning differentiation lineages in single-cell RNA-seq, and tissue of origin inference from cell-free DNA fragmentation patterns. He has extensive engineering experience building scalable infrastructure and data architectures to support distributed training of deep learning models from petabyte-scale functional genomic datasets. He also holds an MS and BS in Computer Science, and experience working in both research and product focused software engineering roles at Google, Illumina, and Counsyl.

Outside of work, Chris enjoys running, cycling, backpacking, and backcountry skiing.

Ci Chu

As the Associate Director of Functional Genomics, Chu leads insitro’s genetic screening and phenotyping efforts.

Chu has over a decade of molecular phenotyping and profiling experiences in academia and industry. Before Insitro, Chu was the genomics tech lead for the Immune Profiler platform developed at Verily Life Sciences (an Alphabet company in healthcare). Verily and Gilead are employing this platform to understand inflammatory autoimmune diseases. During his postdoc, Chu set up a single cell RNAseq platform at Genome Institute of Singapore to map the human immune atlas. During his graduate training with Dr. Howard Chang at Stanford University, Chu invented an RNA-interactome analysis method, “ChIRP,” to study the mechanism of X-chromosome inactivation by the famous long noncoding RNA “Xist”, among many other projects, via genomics, imaging and protein mass spec assays.

In his spare time, Chu tests sneakers for Puma, and reads books to his two young kids.

Claire Jeong

Claire Jeong is a Scientist with various experiences and expertise in human cell-based complex in vitro models (i.e. 3D bioprinting, organs-on-chip, organoids) for drug discovery. At insitro, Claire is a Senior Scientist in the Disease Modeling Group and works on developing and implementing human relevant models and assays to generate more disease relevant data that enables machine-learning based drug discovery.

Prior to joining insitro, Claire was trained as a biomedical engineer and earned her B.S. from Johns Hopkins University and her M.S./Ph.D. from the University of Michigan-Ann Arbor, majoring in Biomedical Engineering with cartilage/bone tissue engineering and biomaterials focus. After her postdoctoral work at Duke University exploring stem cells and cell delivery for disc regeneration, she joined GSK for a collaborative project between GSK and Wake Forest Institute of Regenerative Medicine, and continued working as an investigator for the Complex In Vitro Models group part of the Platform Technology & Sciences division of GSK Pharma R&D.
She also did a secondment with the Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium and served as co-lead on a safety integrated project team and as a complex in vitro models expert, to build integrated predictive safety, efficacy, and PK computational models for cancer drug discovery.

In her spare time, Claire enjoys playing the cello, yoga, hiking, reading, live music and performances and exploring new places and unique cuisines.

Craig Fredrickson

As Scientific Specialist at Insitro, Craig will be working with the Disease Modeling group to help develop robust, scalable and highly reproducible in vitro models of human disease. Craig will also focus on integrating these models into high throughput, automated platforms to eliminate variability and provide large, trustworthy data sets to the Machine Learning team.

After graduating from the University of California Santa Barbara, Craig has supported various research and development efforts in Neuroscience, Stem Cell and Cancer Biology. Throughout his career, Craig has acquired an extensive research experience from institutions such as the Neuroscience Institute, UC San Diego, California Stem Cell Inc., and Memorial Sloan Kettering Cancer Center. Craig hopes to use his experience and ideas to help advance the exciting programs at Insitro to the next level of drug discovery.

Craig enjoys an occasional escape to the wilderness for fishing, camping, exploring and basically just having fun with family. Favorite author: Bertrand Russell.

Daphne Koller, Board Member

Daphne Koller is the CEO and Founder of insitro.

Daphne was the Rajeev Motwani Professor of Computer Science at Stanford University, where she served on the faculty for 18 years. She was the co-founder, co-CEO and President of Coursera for 5 years, and the Chief Computing Officer of Calico, an Alphabet company in the healthcare space. She is the author of over 200 refereed publications appearing in venues such as Science, Cell, and Nature Genetics, and has an h-index of 130. Daphne was one of TIME Magazine’s 100 most influential people and is a MacArthur Fellow, a member of the National Academy of Engineering, and a Fellow of the American Academy of Arts and Sciences and the International Society of Computational Biology.

In her spare time, Daphne enjoys spending time with her family, especially while traveling to exotic destinations (62 countries so far and counting), where they enjoy hiking, sailing, scuba diving, and eating fresh local food.

Deirdre O’Sullivan

Deirdre is a research associate supporting several different aspects of lab work including cloning, iPSC culture, automation, and pretty much anything else needed around the lab!

Deirdre graduated in May 2018 from Cornell University with a BSc. in Biology, concentrating in Genetics, Genomics, and Development. Deirdre is a veteran of lab work having worked in 6 different labs starting at age 15 – most recently as a member of Dr. Kristy Richard’s lab at Cornell University College of Veterinary medicine, and intern at Pfizer in the functional genomics group. She grew up in Nyack, New York and spent many summers in Castle Island, Ireland with her extended family.

In her free time Deirdre enjoys live music, podcasts, painting, and fashion design.

Donald Naegely

Donald is a Senior Lead Engineer, primarily working on developing strategies for internal pipelines, data provenance, and cloud infrastructure. As part of the data engineering team, Donald is working with the other teams to scale and automate internal pipelines and improve the common infrastructure to support future analyses.

Previously, he was a principal engineer at Counsyl (acquired by Myriad) working across many teams helping to develop a new LIMS system, a platform for variant curation, bioinformatics pipelines, and moving to a cloud infrastructure from on premises.

Donald received a BS and MS in Computer Science from Drexel University.

In his free time, Donald enjoys backpacking, skiing, biking, and reading.

Duane Valz

As General Counsel, Duane is responsible for managing risk and structuring opportunities for insitro.

Duane has led the legal and IP functions at prominent Silicon Valley companies operating at a variety of scales and growth stages. He joins insitro from Zymergen, a company applying laboratory automation and machine learning to engineer microbial strains for industrial fermentation applications and new product development, where he served as the company’s first in-house lawyer and general counsel. Prior to Zymergen, Duane was a senior member of the patent team at Google, where he led strategic IP initiatives bearing on mobile, cloud, web and open source technologies. Before that, he served as associate general counsel in charge of patent development at Yahoo!

Mr. Valz began his career at Howard Rice Nemerovski Canady Falk & Rabkin (now combined with Arnold & Porter LLP). Over his career, Duane has been named multiple times to the IAM Strategy 300, recognizing the world’s leading IP strategists. He holds B.A. and J.D. degrees from the University of California, Berkeley, and serves on the boards of directors for the Level Playing Field Institute and the Berkeley Law Alumni Association.

In his free time, Duane enjoys cooking, traveling, live jazz, yoga, the outdoors and quality time with his family.

Eilon Sharon

As Director of Data Science, Eilon is leading the development of cutting edge machine learning, computational biology and statistical genetics approaches to improve drug development.

His team uses machine learning to integrate observations from large population-level studies with results from various high throughput in-vitro assays to identify potential drug targets.

Eilon has extensive experience in applying machine learning to decipher various biological questions. After completing a dual major B.Sc. in biology and computer science at Tel Aviv University, Eilon joined Rosetta genomics, where he worked on discovering miRNA genes in humans and predicting their targets. He then earned a PhD from the Weizmann Institute of Science under the supervision of Prof. Eran Segal. During his PhD, he developed synthetic biology Massively Parallel Reporter Assay (MPRA) and statistical and thermodynamic models, which he applied to decipher the encoding of transcriptional regulation in yeast. Following graduation, Eilon transitioned to a postdoc at Profs Jonathan Pritchard and Hunter Fraser labs in Stanford Medical school department of genetics. At stanford, Eilon worked on a diverse set of projects including: detection and fine mapping of genetic associations with T cell receptor V-genes expression; software for transplant health monitoring using cell-free DNA sequencing (which was commercialized by Stanford); and detection of functional genetic variants using a novel high throughput CRISPR editing. Eilon is the author of over 20 refereed publications appearing in venues such as Cell, Nature Biotechnology and Nature Genetics.

In his free time, Eilon enjoys hiking and camping outdoors with his family.

Elaine Higashi

As a member of the Process Engineering team at insitro, Elaine is working to develop and scale high quality systems and processes to enable the production of high quality biological data for machine learning.

Elaine started her career as a Systems Engineer at Roche developing in vitro diagnostic instruments. At Roche, she was responsible for the design, integration, and lifecycle management of different complex systems. She later moved into the world of biotech startups at Synthego as an Automation Engineer, where she was involved in everything from system qualifications, new process development, to continuous improvement. Some of her projects included developing robust automated processes to enable new CRISPR oligo products and building an automated platform to allow for rapid iteration in scaling engineered cells. Elaine holds a B.S. and M.Eng in Biomedical Engineering from Cornell University with a minor in Music.

In her free time, Elaine enjoys traveling to new places, playing the violin, and building cardboard forts for her two cats.

Ellie Javid

As Head of Financial Operations at instiro, Ellie brings over 15 years of progressive accounting and finance operations experience, including managing cross-functional projects and scaling teams for growth within the life science industry.

Prior to joining insitro, Ellie was an independent consultant for early-stage Bay Area life science companies and worked on various accounting projects, including the development of systems and infrastructure to support growing businesses. Before then, she was Controller at Invitae, a leading genetic testing company offering diagnostic testing for hereditary conditions. Ellie helped the Company prepare for IPO in 2015 and built the team to scale as a public company. Prior to Invitae, Ellie worked at Genomic Health, a publicly-traded global provider of genomic-based diagnostic tests, where she managed the US accounting operations and teams. Ellie also spent time at Ironwood Pharmaceuticals during phase III clinical trials of Linaclotide (FDA approval 2012). During her time at Ironwood Ellie supported the company’s 2010 IPO, ERP transformation and plans for commercialization.

Ellie is Certified Public Accountant and holds an active license in the state of California.

Ellie received a Master’s in Healthcare Administration and Management from City University in London where she focused on finance and delivery of healthcare services across UK and US healthcare systems. During her studies, she also worked at the University of Cambridge, Research Services Division, to support coordination of Medical School research contracts with industry sponsors, budgets and funding.

In her spare time, you can find Ellie mountain biking off the trails in Marin or sailing in the Bay with her husband.

Eric Lubeck

Eric utilizes microscopy to extract quantitative information from cells. His research is focused on developing in situ genomics technologies through a combination of bioengineering, optics, and image analysis. As a member of the functional genomics team, Eric is dedicated to delivering novel assays and datasets to further insitro’s drug discovery pipeline.

Eric earned his Ph.D. in biophysics from Caltech where he developed a new generation of microscopes capable of capturing transcriptomic information from human cells and tissue. Following graduation he transitioned to a postdoc in bioengineering at UCSF/Stanford where he developed synthetic biology tools using CRISPR screens.

In his free time Eric enjoys bicycles, hiking, and spending time with his family.

Fiorella Ruggiu

Fio is a cheminformatics scientist in the drug discovery team focusing on supporting the design and generation of massive datasets to enable machine learning driven drug discovery.

She obtained her Ph.D. in theoretical chemistry at the laboratory of cheminformatics in Strasbourg. Afterwards, she joined the Computer-Aided Drug Design team at Novartis Institutes for BioMedical Research as a postdoctoral scholar. Following that, she worked at DiCE Molecules, a DNA-encoded library start-up.

Fio enjoys running and hiking in the beautiful redwood forests and is passionate about arts and crafts.

Flora Yi

Flora is an Associate Scientist in the Functional Genomic team and she is working on building the CRISPR-based genomic discovery platform, focusing on developing novel CRISPR screening technologies and assays.

Prior to joining insitro, Flora was working on high-throughput genomic engineering in various microbes using automation at a biotech startup. Before then she was working on epigenetic studies on Arabidopsis thaliana with focus on DNA repair and environmental stress response at Salk Institute. She also gained her experience in studying the mechanisms controlling the early steps in organogenesis in the vertebrate embryo at Gail Martin Lab, UCSF. Flora has a background in molecular biology and obtained her B.Sc. in Human Biology from UC San Diego.

In her spare time, Flora enjoys swimming, traveling internationally, and trying new cuisines.

Francesco Paolo Casale

At Insitro, Paolo works within the Data Science and Machine Learning Team, where he applies his academic training in statistical genetics, computational biology and machine learning to identify and characterize functional mechanisms in human disease.

Previously, he was a postdoctoral researcher at Microsoft Research New England, working on automated machine learning and on deep learning models for imagining genetics. Before that, he obtained a PhD in statistical genetics from the University of Cambridge and the EMBL-European Bioinformatics Institute, where he developed new methods for genetic association studies and contributed to international projects such as the last phase of the 1000 Genomes Project and the Blueprint initiative. Previously, he obtained a bachelor’s and master’s degree in physics from the University of Naples, Italy.

In his spare time, Paolo enjoys playing soccer, powerlifting, motorcycling and travelling.

Gabriel Dreiman

Gabriel grew up in Boulder, Colorado. He received his BS in Biological Engineering from Cornell University, and his MSc in Machine Learning from University College London. He completed his master’s thesis at Alzheimer’s Research UK’s Drug Discovery Institute where he studied applications of ML to High Throughput Screening.

In his free time, Gabriel competes in triathlons in addition to skiing and climbing. He also enjoys cooking and backpacking.

Gina Farrugia Ortega

As Executive Assistant, Gina provides administrative and organizational support to insitro’s senior leadership team and collaborates with everyone in aligning and executing on top priorities across the rapidly growing organization.

Gina brings with her over 27 years of experience as an Executive Assistant. Prior to insitro, Gina served as Senior Executive Assistant to the CEO and all C-suite executives at Electronics For Imaging, a global company specializing in digital printing technology, based in Silicon Valley. Furthermore, Gina is fluent in Spanish and an active member of the Administrative Center of Excellence, and she won the Silicon Valley Admins Loyalty Award in 2016, in recognition of her many achievements.

When she is not working, Gina plays percussion musical instruments, enjoys fishing, running, traveling and cooking.

Haoyang Zeng

Haoyang Zeng is a computational biologist with extensive experience in building machine learning models for functional genomics and therapeutic design.

Haoyang grew up in Sichuan, China, home to most of the panda bears in the world. He earned his BE in Electrical Engineering at Tsinghua University, and his MS and Ph.D. in Computer Science at the Massachusetts Institute of Technology under the supervision of David Gifford. His Ph.D. research focused on developing statistical and deep learning methods for learning the regulatory function of DNA sequences, predicting the binding affinity of peptides to the Major Histocompatibility Complex (MHC) for effective neo-antigen vaccine formulation, and designing novel antibody sequences with improved binding affinity and specificity. Haoyang has co-authored 16 publications appearing in venues such as Nature Biotechnology, Nature Genetics, Cell Systems, Genome Research, and Nucleic Acid Research.

During his free time, Haoyang enjoys playing acoustic guitar, drone photography and traveling.

Hervé Marie-Nelly

Hervé is a very enthusiastic applied mathematician with strong research interests in molecular and cell biology. His current work at insitro is focused on the development of new computational methods to generate and extract valuable insight from imaging experiments.

Hervé earned a Master of Machine Learning, Computer Vision and applied mathematics from the Ecole Normale Supérieure in Paris before pursuing a PhD at the Pasteur Institute, where he spearheaded the development of FISH-Quant, a software to quantify 3D microscopy images of single RNA molecules, and GRAAL, a Bayesian genome assembler using HiC data. As a postdoc in Robert Tjian’s lab at UC Berkeley, he developed computational methods to improve the quantification of high resolution microscopy data for insight into transcription regulation and spatial genomic organization.

During his free time, Hervé enjoys hiking and giving autographs pretending he is a famous NBA player.

Ilya Kovalenko

Ilya is a cell biologist with industrial and academic expertise in cellular metabolism and high throughput imaging screening in drug discovery and target identification. As a Scientist at insitro he will develop imaging based screening assays that are highly interfacing with machine learning.

Ilya completed his undergraduate studies at Moscow State University where he learned the basics of industrial high-throughput screening. For his PhD Ilya worked on tumor metabolism and hypoxia projects at Bayer Healthcare focusing on the role of ion channels and transporters as regulators of cellular bioenergetics. He completed his Postdoc in the laboratories of Costas Lyssiotis and Jonathan Sexton at the University of Michigan in Ann Arbor, where he developed several image-based screening assays to study cellular metabolism.

In his spare time, Ilya is an avid marathon runner and travels off the beaten path.

James Warren

James is a Senior Lead Data Engineer, primarily working with distributed systems and big data applications. As part of the Data Engineering team, his goal is to facilitate the development of machine learning pipelines, focusing on scalability, efficiency and repeatability.

James was previously a Ph.D. candidate at Stanford University, where he devised robot motion strategies for the Honda Asimo and Mars rover prototypes. He holds a M.Sc. in Scientific Computing from Stanford and a B.Sc. in Mathematics From Texas A&M University. Prior to joining Insitro, James worked on creating bioinformatics tools at Roche and Helix, and he co-authored a book on big data architectures.

In his free time, he chases after his dog and three cats, enjoys playing board games, travels internationally, and hacks on open-source software projects.

Jason Ravenel

Jason is responsible for building and optimizing insitro’s Research Operations function. He also manages insitro’s internal discovery programs as well as partnered programs with external collaborators.

Prior to joining insitro, Jason spent 15 years at the Novartis Institutes for BioMedical Research in both Oncology and Infectious Diseases groups. His roles spanned portfolio strategy, program management, and scientific operations. During his time in Oncology, Jason helped lead the team that discovered and developed Encorafenib, approved as BRAFTOVI for the treatment of B-Raf mutant melanoma. Prior to NIBR, Jason worked for McKinsey & Company serving primarily Boston area biotech companies. He earned his PhD in Oncology from The Johns Hopkins University School of Medicine.

Jason enjoys the balance of Art with Science and TIG welds steel sculptures.

Jeevaa Velayutham

Jeevaa is a Computer Science masters student from University of Toronto. At insitro, Jeevaa focuses on building machine/deep learning models to improve the effectiveness of our high-resolution cellular microscopy platform.

He completed a BSc. in Applied Physics at the University of Toronto before continuing MSc. in Applied Computing at the same institution. He developed an interest in ML during his bachelors which motivated him to pursue it further. During his masters, he worked on various deep learning projects ranging from biomedical image quality enhancement to accent style transfer.

Jeevaa enjoys playing and watching soccer, traveling and spending time with friends.

John Cesarek

As the Director of Process Engineering, John is responsible for leading the development and deployment of lab automation for high-throughput, effective production of high-quality data sets to use in machine learning. John’s team also will focus on building out the tools and capabilities for implementing operational excellence across all of insitro’s laboratories.

Prior to joining insitro, John spent the last 20 years designing, building and managing automation solutions across biotech and pharmaceutical industries. He has significant expertise with early-stage startups, helping to develop, implement and support automation technologies as they scale. John has an M.Eng. in Systems Engineering from Penn State University.

He is an avid outdoor enthusiast who enjoys backpacking, road biking, landscape photography, and travel.

Jordan Mancuso

Jordan is an automation engineer with experience in developing and optimizing custom automated solutions to advance high-throughput biological workflows.

At insitro, Jordan works to enable the production of high quality biological data for downstream machine learning analysis and data science. She is involved in the translation of manual workflows to automated systems, as well as the continuous improvement and optimization of existing processes.

Prior to insitro, Jordan was an automation engineer with Notable where she developed hardware and software systems to improve their high-throughput automated screening capabilities to accelerate the discovery of personalized cancer treatments. Jordan holds a PhD in Materials Science & Engineering from UC Davis, and a BS in Bioengineering from Syracuse University.

When not in the office, Jordan likes to play with other people’s dogs, climb rocks, and create tiny embroidered creatures.

Joseph Marrama

Joe Marrama is a software engineer with background in heathcare data and distributed systems. At Insitro, Joe is focused on ensuring that the large amount of data we generate is effectively processed and stored.
Joe is a native of Oakland. He attended Stanford where he graduated with a BS in Symbolic Systems and a MS in Computer Science. Prior to Insitro, Joe worked at Nuna Health, where he worked with the federal Medicare program to build a system that evaluated healthcare providers on quality of service and cost-effectiveness. He loves to tackle complex engineering problems in the service of helping others.

Outside of work, Joe enjoys surfing, skiing, mountain biking, cooking, and reading.

Joyce Yang

Joyce Yang is a scientist with extensive experience developing novel technologies at the intersection of CRISPR genome engineering, stem cells, and in situ sequencing. To enable machine-learning based drug discovery, her current work at insitro is focused on building CRISPR perturbation platforms in relevant cellular model systems to produce high-quality data from functional genomic screens and disease modeling.

Joyce earned her B.A. from UC Berkeley majoring in Molecular Cell Biology and minoring in Music. She then pursued her passion for science and earned her Ph.D. from Harvard in Biological & Biomedical Sciences. Her graduate work with Dr. George Church focused on developing a novel in situ RNA sequencing technology as well as CRISPR/Cas9 genome engineering strategies to improve efficiency in human induced pluripotent stem cells (iPSCs). Next, she dived into the exciting world of biotech startups at Synthego, contributing to the growth and commercialization of the new Cell Engineering division as one of the foundational scientists.

Joyce loves to sing and experiment on the piano, traveling, backpacking, taking long walks, and trying all things chewy.

June Jung-Eun Shin

June Jung-Eun Shin is a computational biologist with experience in developing statistical models for protein design and antibody discovery. June is a graduate student at Harvard University pursuing her PhD in Systems Biology in Debora Marks’ lab. Her graduate research is focused on developing computational models to accelerate antibody discovery: designing high fitness libraries for screening, learning sequence determinants of developability such as stability and poly-reactivity, and improving the affinity of specific antibody sequences.

In her spare time, June enjoys playing sports, taking a stroll in the park, and just being outside when the weather is nice.

Kara Liu

Kara Liu is a computer scientist with an interest in applying machine learning methods towards biology and healthcare systems. At insitro, her research focuses on generalizable modeling and uncertainty estimation.

She obtained her BA in Computer Science at UC Berkeley, where she conducted research at Berkeley Artificial Intelligence Research (BAIR) Laboratory under Professor Pieter Abbeel. Her prior research experience was in robotic manipulation using visual planning, data generalization, and deep generative models.

When she’s not coding, Kara enjoys going on runs, exploring the outdoors, reading, and learning to play the guitar.

Katalin Janos

As the Office Manager/Administrative Assistant at insitro, Kate brings with her extensive knowledge and experience in Office Management and Executive Assistant roles in the finance and life sciences industries in the Bay Area. She is passionate about supporting and motivating mission-driven team members in a culture based on integrity and optimism.

Prior to joining insitro, Kate was a Sr. Executive Assistant at Immune Design, a small late stage immunotherapy company, acquired by Merck in 2019, where she helped with daily operations and workflow along with vendor and investor relations. Before then, Kate was an Office Manager at Northwestern Mutual, an investment services company, where she held roles of increasing responsibility, while supporting the organization’s tripling in size and creating an amazing culture and environment.

Kate holds a bachelor’s degree in Law, Transportation and Mobility Management from Romania and completed multiple Fred Pryor courses for Management, Supervision & Leadership.

In her free time, Kate enjoys and participates in all kinds of activities that keep her active. She loves to travel with a preference to exotic and tropical destinations. She speaks English, Hungarian, Romanian (born and raised in Transylvania) and is conversational in Spanish and Italian.

Kathryn Iverson

Kathryn is a data engineer with a background in the microbiome and cloud computing. At insitro Kathryn is working with the data engineering, and data science and machine learning teams to build and scale data analysis pipelines in the cloud.

Before joining insitro, Kathryn worked at Second Genome building metagenomics pipelines and analyzing microbiome data. Kathryn received her Master’s in Bioinformatics from the University of Michigan and worked in Pat Schloss’ lab on projects in microbial ecology, clostridium difficile, and colorectal cancer.

In her free time, Kathryn enjoys playing and watching hockey, traveling, and scuba diving.

Keith James

As Senior Vice-President of Drug Discovery, Keith is responsible for machine learning-enabled drug discovery programs at insitro. Keith and his team are both establishing new drug design capabilities, exploiting the power of machine learning models, and undertaking drug discovery programs on molecular targets derived via the insitro-human (ISH) target discovery platform.

Keith has over three decades of drug discovery experience, building and leading research enterprises ranging from handfuls to hundreds of scientists, tackling programs across a wide range of therapeutic areas, and employing a panoply of therapeutic modalities. During his career, Keith, and the organizations he has led, have delivered over thirty clinical candidates, across fifteen therapeutic areas, many of which have reached Phase 2, and two of which are in the hands of physicians treating patients today – eletriptan (Relpax®) for migraines and maraviroc (Selzentry®) for HIV infections.

Before joining insitro, Keith was President of the Ferring Research Institute in San Diego, engaged in the discovery of peptide therapeutics. Before joining Ferring, Keith had a long career at Pfizer, leading discovery research at three different sites across the US and UK, heading the company’s R&D strategy team, and running a laboratory as a visiting investigator at The Scripps Research Institute.

Keith completed his academic and postdoctoral studies at Imperial College London, The University of Cambridge (Raphael lab), Stanford University (Johnson lab), and Columbia University (Stork lab).

In his free time, Keith enjoys cycling, jogging, reading, writing and mechanical watches.

Kelly Haston

Kelly Haston is a stem cell biologist with broad experience in human stem cell-based models of development and disease. She is a Sr. Scientist in the disease modeling group helping guide the team as they build biological model systems that will interface with the genetic, data science and machine learning modules of insitro’s unique approach to discover novel human therapeutics.

Kelly was born in Ottawa and grew up in central British Columbia and Toronto, Canada. She did her undergraduate and masters work at the UC Berkeley studying the effects of pesticides on frog gonad development. She then began working in the stem cell field during her Ph.D. with Dr. Renee Rejio Pera at UC San Francisco and Stanford University. Kelly performed postdoctoral positions briefly with Dr. Lee Rubin at Harvard and then with Dr. Steven Finkbeiner at UCSF’s Gladstone Institutes where she focused on building stem cell based models of neurodegeneration. She transitioned to industry in 2017, taking a position with a small start up, Scaled Biolabs, as Lead Scientist where she used the company’s novel discovery platform to optimize the production of many different cell types from human stem cells.

Kelly uses her spare time to be outside as much as possible, mainly trail running or fastpacking. She also loves reading, traveling to new places and attending live music and performances.

Lauren Lau

Lauren is part of the Automation & Process Engineering team. She helps develop and implement lab processes, oversees the purchasing and inventory management of lab supplies, and manages shipping and receiving.

After obtaining her B.S. in Pharmaceutical Chemistry from UC Davis, Lauren decided to explore the operations side of science and worked at Calico Life Sciences, an Alphabet company, as a member of the lab operations team.

In her spare time, Lauren enjoys doing puzzles, playing volleyball, baking, and spending time with her border collie who doesn’t know what sleep is.

Lauren Schiff

As a Scientist, Lauren’s career extends across cross-functional teams that encompass research biology, engineering, and data science. Her expertise ranges across biological and software technology toolchains including designing experiments, creating novel engineering tools, building induced pluripotent stem cell (iPSC) models at scale and developing large disease-relevant biological datasets using high-throughput automation platforms. Her work focuses on key aspects of iPSC technology including generation, engineering, differentiation, and phenotyping.

Prior to joining insitro, Lauren was a Cellular Biology Research Consultant at Google, in which she developed a high-throughput target-binder assay. Additionally, she was the biological lead focused on developing diagnostic tools assisted by machine learning.

Lauren received her B.S. from the University of Michigan followed by her M.S. from the University of Sydney in the field of human genetics. Lauren received her Ph.D. in biomedical sciences from the Icahn School of Medicine at Mount Sinai in the lab of Dr. Timothy Blenkinsop in which she focused on stem cell biology and human disease models.

In her free time, Lauren enjoys hiking with her dog, Penny and trying out any and every new ramen restaurant.

Lorn Kategaya

Lorn Kategaya is a cell biologist with small molecule drug discovery experience. At insitro, Lorn will develop relevant disease assays and utilize genetic/chemical screens to identify key biological players that modulate disease outcomes.

Lorn has a PhD in pharmacology from the University of Washington, a post-doc from UCSF and industry experience at Genentech and IDEAYA Biosciences.

Away from the bench, Lorn follows politics and enjoys live music, theatrical performances, and french fries.

Maisha Rashid

Maisha is a Scientist engineering cell lines for high-throughput biology workflows and screening, and developing cell line engineering production processes.

Her PhD work focused on identifying novel pathways in the cancer cell cycle and characterization of chemotherapeutics for drug discovery. She worked full-time as a Scientist, Assay Development at Cayman chemicals as well during her PhD. Following a postdoc at UCSF, Helen Diller Cancer Centre, she joined Synthego as Scientist, Engineered Cells. At Synthego she was in charge of cell line engineering, SOP development, production for immortalized and iPSCs. Motto at Synthego “Any cell line, any edit”.

During her free time, Maisha likes reading, hiking, playing basketball or just hanging out with friends.

Mary Rozenman

Dr. Mary Rozenman is insitro’s CFO/CBO and maintains responsibility for a number of strategic and operational functions at insitro including strategic and operational finance and accounting, strategy, business development, investor relations and corporate communications as well as project and portfolio management.

Mary brings to insitro more than 15 years of scientific expertise, company building and transactions leadership in the biotechnology industry.

Prior to joining the insitro team, she served as the senior vice president of corporate development and strategy at Aimmune Therapeutics, leading business development and partnerships with companies such as Regeneron/Sanofi and Nestlé Health Science, and supporting the company’s strategic finance and investor relations efforts. In her time at Aimmune, she raised more than $650 million in capital through a range of private and public transactions including leadership of the company’s 2015 IPO.

Before Aimmune, Mary was a vice president at Longitude Capital, where she focused on biotechnology investments and participated in multiple therapeutics investments and boards of directors, including observing on Aimmune’s board. Mary was also previously a junior partner at McKinsey & Company, focused on pharmaceuticals and corporate finance. Her scientific work has been published in premier scientific journals, and she is a named inventor on several patents.

Mary holds a doctorate in organic chemistry and chemical biology from Harvard University and a bachelor of arts in biochemistry and Russian literature from Columbia University.

In her spare time, Mary likes to cook, enjoys hiking, going to the theater and hanging out with family — including her husband and young son and daughter.

Matthew Albert

Matthew Albert is Senior Vice President, Biology & Translational Genetics at insitro.

Prior to joining insitro, Matthew worked as Principal Scientist in the Department of Cancer Immunology at Genentech (2015 – 2019); and served as Professor (2003 – 2015), Founder and Director of the Center for Human Immunology (2007 – 2015) and Director of the Immunology Department at Institut Pasteur, Paris France (2010 – 2015).
Matthew is an immunologist and clinical pathologist, with a long-standing interest in immune regulation and tumor immunity. His research embraces the power of a “human-first” approach to scientific discovery, driven by a commitment to understand how to achieve effective response to cancer immunotherapy, autoimmunity and chronic infection while limiting adverse effects of treatment. As this requires a deep insight into health and disease pathogenesis, he has developed several areas of investigation over the last two decades, which has included a deep commitment to bladder diseases (incl. cancer and UTI); and liver diseases (incl. HCV, HBV, HCC and NASH). He has also been a leader in the Milieu Intérieur Consortium, a 30-team academic / industrial partnership that aims to define the genetic, microbiome and environmental determinants of variable immune responses in healthy persons.

Matthew trained at The Rockefeller University, Cornell University Medical College and did his residency at New York Presbyterian Hospital. He is the author of more than 100 peer-reviewed scientific papers and has made major contributions to the understanding of antigen cross-priming and the impact of post-translational modification of chemokines as determinants of effective tumor immunity. In his spare time, he and his family enjoy cooking together, traveling and exploring the world’s ecology under the sea (marvelling at Ostracod mating practices in the Carribean), in jungles (visits to the Sarawak Biodiversity Centre in Borneo), and in ecology parks (riding dolphins in Tunisia). The have traveled together to over 35 countries, with a strong belief that knowing and engaging with diverse communities and cultures help them be better contributors to the world.

Matthew Chen

Matthew is a computer scientist with experience in developing and deploying machine learning models. His focus is on applying deep learning models to gain insights from imaging data.

Prior to insitro, Matthew acquired his M.S. in computer science from Stanford University. His graduate research focused on applying machine learning methods to infer diagnostic information from medical imaging, and applying natural language processing to efficiently gather data from unstructured reports. Additionally, he has extensive experience building scalable data infrastructure to support computationally intensive analysis of large datasets. He has worked in both an academic research setting and industry setting for companies such as Google and several startups.

In his free time, Matthew likes to catch up on reading, spend time with friends and family, and continue the unending quest to find a third hobby.

Matthew Rasmussen

As VP of Data Engineering, Matt is responsible for leading the development of data pipelines, data storage systems, provenance tracking, and engineering infrastructure to support the high-throughput biology and Machine Learning teams at insitro.

Previously, as VP of Engineering for Myriad Genetics, Matt led engineering teams focused on software automation and genomic data pipelines to make high complexity genetic testing routine in clinical practice. During his time at Counsyl, Matt developed and scaled the software behind several successful prenatal genetic testing products.

Matt holds a Ph.D in Computer Science from MIT, where he developed efficient bioinformatic algorithms with applications in evolutionary genomics and population genetics.

In his spare time, Matt enjoys running, drawing, programming for fun and playing with his kids.

Max Salick

As Disease Modeling Scientist, Max is focused on using pluripotent stem cells, CRISPR, and a range of differentiation and transcriptomics approaches to model human diseases in in vitro platforms. Max and his team will model devastating human diseases using the relevant cell types, and will produce high-throughput / high-quality imaging and transcriptomic datasets for insitro’s machine learning platform to mine for phenotypes.

Max is an engineer by training, gaining a B.S. in Engineering Mechanics and Astronautics and a Ph.D. from the Materials Science Program of the University of Wisconsin – Madison. By combining dry lab engineering with wet lab disease modeling, Max has frequently used the newest technologies to gain insights into the mechanisms by which various genetic diseases affect human health. Max spent his time in graduate school developing micropatterned differentiation techniques and computational analysis tools to improve stem-cell-based heart modeling methods. Prior to joining insitro, Max spent 4 years as a postdoc in the Novartis Neuroscience department, where he developed single cell characterization platforms to discover disease mechanisms of tuberous sclerosis, uncovered novel mechanisms of disease progression in certain dementias, and conducted genome-wide screens to elucidate potential Zika virus receptors.

Max’s free time is spent with his border collie, Coda, along with playing piano/guitar, and poorly-but-enthusiastically playing various sports.

Meiliang Pan

Mei is a Research Associate in High-Throughput Biology and her work primarily focuses on differentiate human pluripotent stem cell (iPSC) into desired cell types for in vitro human disease modeling and generate datasets for insitro’s machine learning platform.

Prior to joining insitro, Mei was a CIRM (California Institute for Regenerative Medicine) Scholar at the Gladstone Institute working on iPSC neurodegenerative diseases modeling. Mei obtained her B.Sc. in Biology with an emphasis on cellular/molecular biology and a minor in chemistry from Humboldt State University.

In her spare time, Mei enjoys photography, visit art exhibits, live music and performances, reading, hiking, exploring new places and try different cuisines.

Michael Bereket

Michael is a computer scientist with a strong interest in the development and application of computational techniques for scientific discovery. His current work at insitro is focused on deriving insights from patient data to help guide disease modeling efforts.

Michael studied computer science at Stanford University, where he had the opportunity to contribute to research across machine learning and medicine.

In his free time, Michael loves to dance, run, learn new things, and joke around with friends.

Mohammad "Muneeb" Sultan

Mohammad “Muneeb” Sultan is a computational chemist with experience working at the interface of computational biophysics, free-energy methods, machine learning, and statistical mechanics. His current work at insitro is focused on building up the machine learning platform, and designing novel methods for analyzing the outputs of various high throughput assays.

Muneeb is a native of Pakistan and grew up in the city of Rawalpindi. He got his undergraduate degree in Chemistry at Yale, and his PhD in Physical Chemistry at Stanford under Vijay Pande. At Stanford, Muneeb focused on studying oncogenic kinases using the Folding@home distributed computing platform, collecting and analysing some of the largest simulation datasets of their kind. Simultaneously, he also worked on developing new Machine learning algorithms for accelerating free-energy calculations and molecular simulations. Muneeb has co-authored 17 publications appearing in venues such as PRE, PNAS, Nature Scientific Reports, and Nature Chemistry.

During his free time, Muneeb likes to powerlift, do yoga, explore the bay area, create digital art, cook, and listen to music.

Nav Ranu

Nav has extensive experience working at the intersection of next generation sequencing, microfluidics, and single cell technologies. His focus at insitro involves designing and analyzing high throughput sequencing experiments in order to support indication specific drug discovery pipelines and the functional genomics team.

Nav acquired his undergraduate degree in Chemical Engineering at UC Berkeley followed by a PhD in Biological Engineering at MIT. His graduate research focused on developing novel targeted sequencing technologies to make single cell genomic experimental more feasible and to understand patterns of DNA damage. While completing his PhD, Nav also served as a Communication Fellow at the Broad Institute where he mentored scientists through the process of written, verbal, and visual presentations of science.

In his free time, Nav is an avid proponent of indoor and outdoor sports ranging from lounging on a couch to climbing up and skiing down mountains.

Olivia Warren

Olivia is a data engineer with a background in automating the analysis of biochemical data to enable timely, high-quality insights.

At insitro, Olivia is collaborating with the data engineering, machine learning, and process engineering teams to develop data pipelines and software to support wet lab and computational experimentation at scale.

Prior to insitro, Olivia designed and developed custom production data pipelines at Synthego Corporation, including an image processing pipeline to automate the analysis of live-cell microscopy images. She also held positions within Deloitte Consulting’s Life Sciences practice and at Medtronic Diabetes. Olivia earned her B.S. in Materials Chemistry from Harvey Mudd College, where she was a recipient of the Lewis Research Fellowship in Chemical Engineering. Her fellowship research focused on modeling membrane transport to inform the development of novel transdermal drug delivery systems.

While not at work, Olivia enjoys hiking and running in the Bay Area hills, playing her cello, analyzing NBA basketball statistics, and trying to keep her houseplants alive.

Owen Chen

Owen spent four and a half years as a member of Dr. Jonathan Weissman’s Lab at UCSF, where he supported the development RNAi-based and CRISPR-based mammalian genome-scale functional genomics screening platforms, successfully identifying new targets for grants and publications. He cloned and maintained ultracomplex shRNA/sgRNA screening libraries as well as generated stable cell lines with gene repression or activation. Additionally, he conducted numerous functional genomic screens in cancer cell lines challenged by various toxins, drugs, and chemicals.

After his time at UCSF, he spent two and a half years at Driver, where he developed NGS assays and validated tumor-normal and cfDNA manual assays under CAP and CLIA guidelines. He also had fun acquiring a new set of skills in converting these manual assays into fully automated processes.

Panagiotis "Panos" Stanitsas

Panagiotis “Panos” Stanitsas is a computer scientist with experience in developing and deploying computer vision models in diverse application domains. At insitro, Panos focuses on the research and development of inference schemes for imaging data.

Prior to insitro, Panos worked at 3M as a Senior Data Scientist, where he focused his research and development efforts at the intersection of material science with computer vision for problems and products spanning the transportation safety space. Panos received his PhD in Computer Science and Engineering from the University of Minnesota, advised by Nikos Papanikolopoulos and Vassilios Morellas at the Center of Distributed Robotics. During his PhD, Panos derived amalgamations of deep learning models with uncertainty sampling schemes and metric learning methodologies, with emphasis on the problem of cancerous tissue recognition from hematoxylin and eosin stained tissue slides.

In his free time, Panos enjoys playing basketball, cooking, weightlifting, and feverishly trying to find the best food spots in the Bay Area.

Perry Palmedo

Perry is the Director of Strategy and Corporate Development at insitro. He supports the executive team on initiatives at the intersection of machine learning and corporate strategy, including business development and the formulation of machine learning problems relevant to drug discovery and development.

Perry completed his Ph.D. in the Bioinformatics and Integrative Genomics program at Harvard Medical School where his research focused on using statistical models to predict protein structure from sequence variation. Prior to graduate school he spent five years working in finance for Morgan Stanley and BMGI, the investment office of Bill and Melinda Gates and the Bill and Melinda Gates Foundation. He majored in physics at Princeton University where his senior thesis focused on modeling viral gene regulatory circuits.

Having grown up in Sun Valley, ID, Perry is excited to be back west and enjoys spending as much time as possible outside, whether on foot, bike, or skis.

Pooja Prasad

Pooja is an Associate Scientist for the Process Engineering team and she is working on developing and scaling various genomics assays and QC protocols.

Prior to joining insitro, Pooja worked on developing a robust, high-throughput NGS library preparation protocol for engineered strain genotyping at a biotech startup. Before then she was a graduate student researcher at the Buck Institute for Research on Aging, where she worked on developing a protocol for generating three-dimensional retinal organoids using mouse embryonic stem cells. Pooja has a background in molecular biology and obtained her B.S. and M.S. from Dominican University of California.

In her free time, Pooja enjoys cooking, traveling, and spending time with her dog.

Rachel Groth

As the Director of Neuroscience, Rachel leads insitro’s therapeutic strategy in neuroscience-related indications in collaboration with her talented colleagues.

Rachel joined insitro from Biogen, where she helped to build a Neurodevelopmental Disorders drug discovery group and pipeline. Prior to Biogen, Rachel worked at Pfizer’s Centers for Therapeutic Innovation. There, Rachel led drug discovery project teams spanning multiple therapeutic areas and led a team that advanced a candidate into early phase clinical studies.

Before joining Pfizer, Rachel was a postdoctoral fellow in Dr. Richard Tsien’s lab at Stanford University in the Department of Molecular and Cellular Physiology. Rachel received a Ph.D. in Neuroscience from the University of Minnesota and a B.A. in Biology and Neuroscience from Macalester College.

In her spare time, Rachel enjoys spending time with her family.

Ralph Ma

Ralph Ma is a software engineer experienced in developing, maintaining and serving machine learning models. His current work at insitro is focused on improving experimentation and serving platforms to better accommodate the scale and uniqueness of the biological data collected.

After graduating with a B.S. in Computer Science from Stanford, Ralph worked at Google using machine learning to improve labeling of places with low impressions. Also at Google, he constructed embedding models to assist efforts in automating web actions by better understanding semantics of UI elements.

In his free time, Ralph enjoys rock climbing, fishing, and winning his fantasy football league.

Robin Betz

Robin is passionate about working at the interface of biological and computational problems. She studied Bioinformatics as an undergraduate at UC San Diego, and recently completed her doctorate in Biophysics from Stanford, where she was a NSF and NVIDIA Fellow. Her PhD work focused on molecular dynamics simulation of protein-ligand binding, integrating computational methods development with interesting discoveries about specific proteins and drugs. During the course of her research, Robin worked on parallel algorithms, online analysis of large datasets, visualization methods, and contributed to the development of multiple related software packages, including AMBER and VMD.

In her free time, Robin likes to race bicycles, contribute to open source software, and scuba dive.

Roey Baror

Roey Baror is a neuroscientist and glial biologist with expertise in developing primary adult mammalian cell cultures and transcriptomics analysis. As a Scientist in the Disease Modeling group at insitro, Roey focuses on building robust in vitro platforms to reliably model human diseases.

Roey earned his B.Sc. in Biology and Psychology (neuroscience pathway) at the University of Tel Aviv (Israel). He then worked at the Berenson-Allen Center for Noninvasive Brain Stimulation (Boston, MA) where he used TMS (Transcranial Magnetic Stimulation) as an experimental treatment for Alzheimer’s disease.

Roey received his PhD in Clinical Neurosciences from the University of Cambridge (UK). His research focused on methods to enhance regeneration of myelin in the central nervous system, with emphasis on the effects of aging. His work uncovered new mechanisms by which aging processes alter the activity of stem cells and immune cells in the brain, allowing the development of new therapeutic interventions. Following his PhD, he continued to a postdoc at UCSF (San Francisco, CA), where he studied metabolic pathways in adult CNS stem cells in search for new ways to promote the activation of these cells in pathological settings and promote regeneration of myelin.

In his free time, Roey enjoys rock climbing, hiking, snowboarding, cooking and discovering new craft beers and breweries.

Santiago Akle

Santiago is passionate about developing computational methods to enable science. He holds a Doctorate degree in Computational Mathematical Engineering from Stanford University, where he worked with Michael Saunders and Yinyu Ye. His PhD work focused on extending interior-point methods to efficiently solve new convex problems, and was awarded the Gene Golub dissertation award for his innovations.
Before joining Insitro Santiago was a senior machine learning researcher at Apple Inc. Where, amongst other things, worked on methods to accelerate DNN training.

In his free time Santiago enjoys spending time with his family, running, trying out different cuisines and flying around in a small plane.

Serafim Batzoglou

Dr. Serafim Batzoglou is insitro’s Chief Data Officer (CDO).

Serafim joins insitro from Illumina, where he recently served as the company’s Vice President of Applied and Computational Biology. There, he led research and technology development of AI and molecular assays to make genomic data more interpretable in human health. His computational team developed deep learning methods for image processing across sequencing instruments, as well as for classification of patient genomic variants according to their molecular cellular effects and pathogenicity, facilitating diagnostic ability for genetic disease patients.

During his tenure at Stanford from 2001 to 2016, Serafim focused on the application of algorithms and machine learning, the study of large scale genomic and biomedical data, and the development of widely used tools in genomics. His research has spanned sequence assembly, genome alignment, identification of functional elements including gene coding regions, splice sites and transcription factor binding sites, folding of RNA structures, population genomics, cancer genomics, sequencing technologies and their use in personal genome and metagenome reconstruction, and single cell transcriptomics, among other topics.

Serafim is also the co-founder of DNAnexus, a secure cloud platform and global network for scientific collaboration and accelerated discovery, and previously served on the company’s board of directors. He has served on many scientific advisory boards, including at 23andMe, Moleculo and NextBio. He is the recipient of numerous awards, including being named one of the top 100 young innovators by MIT Technology Review, The International Society of Computational Biology’s inaugural Innovator Award and one of the top 25 voices in Precision Medicine by Insight Monk. Dr. Batzoglou holds a Ph.D. in Computer Science, a Master’s in Electrical Engineering, and a B.S. in Mathematics and Computer Science from MIT. In his Ph.D. work, he focused on computational biology and was involved in the assembly and comparative analysis of the first mammalian and human genomes.

Shahin Mohammadi

Shahin is passionate about the challenges and promises of interdisciplinary research. He is a firm believer in collaborative research and teamwork, and he advocates for the open-science/open-source movement. His primary interest is to build robust, reproducible, and interpretable models inspired by, grounded in, and driven by core biological knowledge. He develops computational models and methods, mathematical formulations, and rigorous statistical techniques for problems at the intersection of computational, biological, and clinical sciences, including single-cell analysis.

Shahin is an LGBTQIA right activist and works hard to educate himself and others on gender expression, identity, and equality. Additionally, he seeks to challenge the current, unfair, view(s) on mental health issues and improve support and understanding for affected individuals.

Sheetal Modi

Sheetal’s work at insitro blends project and product management to support cross-functional projects spanning internal technology development and therapeutic discovery.

Before joining insitro, Sheetal helped other early stage companies deliver on their scientific projects and scale operations for industrial biotech and health tech applications. Sheetal did her postdoctoral work at the Wyss Institute for Biologically Inspired Engineering and received her PhD from Boston University in Biomedical Engineering where she studied how bacteria adapt to stress. Upon leaving academia, Sheetal was motivated to apply her experimental and computational learnings to analyze industrially relevant dynamic and high-throughput data sets to garner novel biological insights.

In her spare time, Sheetal is actively interested in scientific engagements for non-scientific audiences and also enjoys consuming as much pizza as possible.

Shengjiang Tu

Shengjiang is a biochemist with interests in stem cell biology, transcription regulation, epigenetics, and CRISPR technologies. At insitro, he works on the functional genomics and phenotyping team to help build the CRISPR-based genomic discovery platform, focusing on developing novel CRISPR screening technologies and assays.

As a chemist by training, Shengjiang obtained his Ph.D. in biochemistry at Ohio State University. While working in Dr. Ming-Daw Tsai’s lab, his graduate studies focused on de novo chromatin modifying enzyme discovery and enzyme targeting on the genome. During that process, he appreciated the power of chemistry, yeast genetics, and proteomics. Afterwards Shengjiang conducted his postdoc with Dr. Danny Reinberg at Howard Hughes Medical Institute / New York University School of Medicine on chromatin biology, where he combined proteomics, genomics, as well as CRISPR knock-in, knock-out, and genetic screen techniques in cells and mice to tackle exciting stem cell and germ cell biology questions. In 2017, he joined a regenerative medicine startup Surrozen, where he worked on adult stem cells differentiation and function assays related to Wnt signaling, as well as bi-specific antibody engineering.

In his spare time, Shengjiang enjoys hiking with his family, watching football with his son and following NFL and NCAA football news.

Srinivasan Sivanandan

Srinivasan is an MSc in Applied Computing candidate in the Department of Computer Science at the University of Toronto. His research interests are machine learning and image processing for computer vision and healthcare applications. His work at insitro involves developing learning models for the efficient analysis of our high-throughput microscopy platform.

During his Master’s program at the University of Toronto, he has worked on various machine learning projects, such as early prediction of sepsis onset and adversarial imitation learning by planning. Prior to this, he was a Lead Engineer in the Medical Imaging team at Samsung Research, India working on ultrasound imaging applications. Srinivasan holds a dual degree (Bachelors + Masters) in Biotechnology and Biochemical Engineering from the Indian Institute of Technology, Kharagpur.

In his free time, Srinivasan enjoys singing, hiking and reading books.

Stephen Meadows

As Executive Assistant to the CEO, Steve performs an extensive array of administrative tasks and sets a foundation for the smooth business operations of the company, making the entire team more effective and successful.

Steve spent his first nine years in Bay Area biotech at Amyris, moving from receptionist to executive support roles for the CEO and the President of R&D. He then moved to Calico to support Daphne Koller in her role as Chief Computing Officer. Steve has an M.A. in French from the University of Louisville and a B.A. in Foreign Languages/International Studies from Bellarmine University.

Steve used to have many hobbies but now has three young daughters.

Thomas "Tom" Soare

Tom is a statistical geneticist and data scientist excited about integrating genomic and deep
phenotypic data to impact human health.

Prior to joining insitro, Tom was a statistical geneticist and computational biologist at Goldfinch
Bio, conducting genetic association studies in large-scale sequencing cohorts to identify
common and rare variants that associate with a rare kidney disease, focal segmental
glomerulosclerosis (FSGS). To enable target identification and validation at Goldfinch, he also
analyzed scRNAseq data of human organoids and tissues, and analyzed image data for cellular
assays. Before that, he examined the effect of early-life adversity on psychopathology and DNA
methylation, as well as conducted genetic association studies of depression and cortical
thickness at the Center for Genomic Medicine at the Massachusetts General Hospital. Tom
holds a PhD in Psychology with a focus on Population Genetics from the University of
Washington where he studied the effect of satellite image-derived landscape features on
dispersal of an ant species.

In his spare time, Tom enjoys hiking, camping, sailing, and traveling with his family.

Thomas Liao

Thomas is a machine learning researcher interested in developing empirical methods to better understand when and why deep learning approaches fail.
As an intern with the machine learning team, he works on characterizing distribution shifts in imaging problems. His undergraduate research at UC Berkeley in Ben Recht’s lab focused on similar problems for deep sequence models in the context of machine translation.

Away from the keyboard, Thomas can be found in the outdoors, or at home, reading