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.
As Vice President of High-throughput Biology 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 (bio-data factory) which consists of functional genomic, disease modeling, automation/process engineering and proteomic teams.
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 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 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.
Selected Publications:DRUG-seq: A Miniaturized High-Throughput Transcriptome Profiling Platform for Drug Discovery. Ye C, Ho DJ, Neri M, Yang C, Kulkarni T, Randhawa R, Henault M, Mostacci N, Farmer P, Renner S, Ihry R, Mansur L, Gubser Keller C, McAllister G, Hild M, Jenkins J, and Kaykas A. In Press, Sept; 2018 Nat. Comm. https://www.nature.com/articles/s41467-018-06500-x p53 inhibits CRISPR-Cas9 engineering in human pluripotent stem cells. Ihry RJ, Worringer KA, Salick MR, Frias E, Ho D, Theriault K, Kommineni S, Chen J, Sondey M, Ye C, Randhawa R, Kulkarni T, Yang Z, McAllister G, Russ C, Reece-Hoyes J, Forrester W, Hoffman GR, Dolmetsch R, Kaykas A. Nat Med. 2018 Jul;24(7):939-946. https://www.nature.com/articles/s41591-018-0050-6 A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development. Yao Z, Mich JK, Ku S, Menon V, Krostag AR, Martinez RA, Furchtgott L, Mulholland H, Bort S, Fuqua MA, Gregor BW, Hodge RD, Jayabalu A, May RC, Melton S, Nelson AM, Ngo NK, Shapovalova NV, Shehata SI, Smith MW, Tait LJ, Thompson CL, Thomsen ER, Ye C, Glass IA, Kaykas A, Yao S, Phillips JW, Grimley JS, Levi BP, Wang Y, Ramanathan S. Cell Stem Cell. 2017 Jan 5;20(1) https://www.cell.com/cell-stem-cell/fulltext/S1934-5909(16)30340-X?code=cell-site Genetic Ablation of AXL Does Not Protect Human Neural Progenitor Cells and Cerebral Organoids from Zika Virus Infection. Wells MF, Salick MR, Wiskow O, Ho DJ, Worringer KA, Ihry RJ, Kommineni S, Bilican B, Klim JR, Hill EJ, Kane LT, Ye C, Kaykas A*, Eggan K.* Cell Stem Cell. 2016 Dec 1;19(6):703-708. *Co-corresponding author https://www.cell.com/cell-stem-cell/fulltext/S1934-5909(16)30407-6 Functional genomic analysis of the Wnt-wingless signaling pathway. DasGupta R*, Kaykas A*, Moon RT, Perrimon N. Science. 2005 May 6;308(5723):826-33. *Co-first authors https://science.sciencemag.org/content/308/5723/826
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.
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 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 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.
As principal scientist / manager, Chu leads insitro’s functional genomics 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 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.
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 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 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.
Eilon Sharon is a senior data scientist and computational biologist with extensive experience in applying machine learning to decipher various biological questions. Eilon’s work at insitro integrates observations from large population-level studies, such as GWASs, with results from various high throughput in-vitro assays to identify potential drug targets.
After completing a dual major B.Sc. in biology and computer science at TAU, Eilon joined Rosetta genomics, where he worked on discovering miRNA genes in human 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 outdoor with his family.
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.
Selected Publications:Single-cell in situ RNA profiling by sequential hybridization https://www.nature.com/nmeth/journal/v11/n4/full/nmeth.2892.html In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus https://www.sciencedirect.com/science/article/pii/S0896627316307024 Dynamics and Spatial Genomics of the Nascent Transcriptome by Intron seqFISH https://www.sciencedirect.com/science/article/pii/S0092867418306470
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.
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 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.
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 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.
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.
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 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.
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.
Selected Publications:Werner Syndrome Helicase is Required for the Survival of Cancer Cells with Microsatellite Instability https://www.cell.com/iscience/fulltext/S2589-0042(19)30040-9 USP7 small-molecule inhibitors interfere with ubiquitin binding https://www.nature.com/articles/nature24006
Dr. Mary Rozenman 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, Dr. Rozenman 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. Dr. Rozenman 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.
Dr. Rozenman 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, Dr. Rozenman likes to cook, enjoys hiking, going to the theater and hanging out with family — including her husband, toddler son, and newborn daughter.
Matthew Albert is Vice President of Immunology & Infectious Diseases 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.
Selected Publications:Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration. Lim YW, Chen-Harris H, Mayba O, Lianoglou S, Wuster A, Bhangale T, Khan Z, Mariathasan S, Daemen A, Reeder J, Haverty PM, Forrest WF, Brauer M, Mellman I, Albert ML. Proc Natl Acad Sci U S A. 2018 Dec 11;115(50):E11701-E11710. doi: 10.1073/pnas.1804506115. Epub 2018 Nov 21 Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors. Patin E, Hasan M, Bergstedt J, Rouilly V, Libri V, Urrutia A, Alanio C, Scepanovic P, Hammer C, Jönsson F, Beitz B, Quach H, Lim YW, Hunkapiller J, Zepeda M, Green C, Piasecka B, Leloup C, Rogge L, Huetz F, Peguillet I, Lantz O, Fontes M, Di Santo JP, Thomas S, Fellay J, Duffy D, Quintana-Murci L, Albert ML; Milieu Intérieur Consortium. Nat Immunol. 2018 Mar;19(3):302-314. doi: 10.1038/s41590-018-0049-7. Epub 2018 Feb 23 Genetic Adaptation and Neandertal Admixture Shaped the Immune System of Human Populations. Quach H, Rotival M, Pothlichet J, Loh YE, Dannemann M, Zidane N, Laval G, Patin E, Harmant C, Lopez M, Deschamps M, Naffakh N, Duffy D, Coen A, Leroux-Roels G, Clément F, Boland A, Deleuze JF, Kelso J, Albert ML, Quintana-Murci L. Cell. 2016 Oct 20;167(3):643-656.e17. doi: 10.1016/j.cell.2016.09.024 RIPK1 and NF-κB signaling in dying cells determines cross-priming of CD8⁺ T cells. Yatim N, Jusforgues-Saklani H, Orozco S, Schulz O, Barreira da Silva R, Reis e Sousa C, Green DR, Oberst A, Albert ML. Science. 2015 Oct 16;350(6258):328-34. doi: 10.1126/science.aad0395. Epub 2015 Sep 24
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.
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.
Selected Publications:Genetic ablation of AXL does not protect human neural progenitor cells and cerebral organoids from Zika virus infection https://www.ncbi.nlm.nih.gov/pubmed/27912091 Micropattern width dependent sarcomere development in human ESC-derived cardiomyocytes https://www.ncbi.nlm.nih.gov/pubmed/24582552 p53 inhibits CRISPR-Cas9 engineering in human pluripotent stem cells https://www.ncbi.nlm.nih.gov/pubmed/29892062/
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 is an MS candidate in computer science at Stanford University, where he has also received a bachelor’s degree in computer science. In his time at Stanford, Michael has completed numerous ML projects, including computer vision work to improve diagnosis from medical images and automated liquid-handling robots. In high school, he was introduced to medical research through internships at a Stanford allergy lab. Michael is excited to combine his passions for computer science and medicine to work on problems with significant human impact at insitro.
In his free time, Michael loves to dance, trail run, learn new things, and joke around with friends.
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 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.
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.
Academic affiliations and titles: Core Institute Member, Broad Institute of Harvard and MIT; Karl Van Tassel
(1925) Career Development Associate Professor of Biological Engineering, Massachusetts Institute of
Technology; Extramural Faculty Member, Koch Institute for Integrative Cancer Research at MIT
Dr. Blainey took degrees in mathematics and chemistry at the University of Washington before joining Professors Gregory L. Verdine and X. Sunney Xie in the Department of Chemistry and Chemical Biology at Harvard University for Ph.D. study in Physical Chemistry. There, Dr. Blainey developed single-molecule biophysics techniques for the study of DNA repair. In 2007, Dr. Blainey shifted his focus to single-cell genomics in Professor Stephen R. Quake’s group at Stanford University. A faculty member in Biological Engineering at MIT and a Core Member of the Broad Institute since 2012, Dr. Blainey’s group integrates microfluidic, molecular, and imaging tools to create robust and scalable solutions to major challenges in the life sciences and biomedicine.
Perry is a Special Projects Manager and member of the Data Science team 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.
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.
As part of the Functional Genomics team at insitro, Tina generates libraries for screening using the latest molecular biology techniques.
Tina spent the last thirteen years working in all facets of yeast strain engineering, first at Amyris and then at Lygos and Calico. She received a B.S. in Chemical Engineering from UC-Berkeley and was an undergraduate researcher in the Keasling lab.
Tina used to play ice hockey but now focuses her energy into knitting or crocheting toys for her three kids.