Josh has spent his career focused on the intersection of machine learning, product, and life sciences/healthcare. Prior to Inductive, Josh was the Director of Product for the ML and data curation organizations at Flatiron Health, where his teams worked to generate real-world evidence (RWE) at scale across Flatiron’s network of over 2 million active cancer patients for use by researchers in pharma, academia, and government. Prior to Flatiron, Josh was at MIT studying computer science and working with researchers at Massachusetts General Hospital to use ML and NLP to predict patient response to cardiac resynchronization therapy.
Ben has more than a decade of experience leading teams applying state-of-the-art machine learning to real-world problems. Before Inductive, Ben was a Senior Director of Engineering at Flatiron Health, where he led the company’s development of ML algorithms and infrastructure to make sense out of hundreds of millions of electronic health records. Previously he was at Google, where he built ML systems for natural language understanding in Search. He has a Ph.D. in Computer Science from the University of Washington, where he researched and published on topics in the mathematical theory of algorithms and in applied machine learning and human-computer interaction.
Paul is an accomplished medicinal chemist in the neuroscience area, having led multidisciplinary scientific teams that delivered 8 clinical candidates. After 28 years at Eli Lilly, he joined the Roosevelt University College of Pharmacy, and after 5 years, he moved to the Medical College of Wisconsin Pharmacy School. His research efforts resulted in 57 issued US patents, 121 peer-reviewed publications, and 55 invited lectures on his research around the world. He has a Ph.D. in synthetic organic chemistry from the University of Wisconsin, Madison.
Gunjan was previously at Google Research where she focused on genomics and multimodal machine learning. Her work on DeepConsensus for PacBio sequencing data was published in Nature Biotechnology, and the method now runs on the latest Revio sequencer. Her contributions to DeepVariant have been published in Nature and the New England Journal of Medicine. Gunjan holds a master's degree in computer science and a bachelor’s degree in computer science and molecular & cell biology from UC Berkeley.
Bryce brings 10+ years of experience applying state-of-the-art machine learning to highly technical domains. Bryce most recently was a Principal Machine Learning engineer at Butterfly Network, a major medical ultrasound vendor, where he led a successful collaboration with the Gates Foundation and UNC to develop groundbreaking AI-enabled prenatal screening tools for low-resource settings. Bryce has previously built and led product-focused data science and machine learning teams at several startups in radiology, legaltech, and financial services, and has an MBA from Oxford University.
Will focuses on application and infrastructure development at Inductive. Previously, he worked at Palantir Technologies, where he founded and led the Network Infrastructure team, which wrote and operated security, scalability, and performance-critical software across all of Palantir's commercial and government customers. Prior to the Network Infrastructure team, Will led Palantir's Apollo product, a continuous delivery and management tool used by every software team at the company. Will also served as a hiring manager for the infrastructure group at Palantir.
Patrick has extensive experience building high-performance machine learning models for scientific problems. Prior to Inductive, he was a Principal Deep Learning Engineer at Butterfly where he built FDA-approved computer vision models for reading medical ultrasound images in real-time on mobile hardware. He has a PhD in experimental condensed matter physics from Columbia University, where he studied quantum transport in organic semiconductors. His work has been published in top journals and conferences including ICLR, Science, and Nature.
Alex's experience spans the theory and practice of building trustworthy and robust machine learning systems. Before Inductive, Alex was a Staff Data Scientist at Flatiron Health, where he built ML models for patient risk stratification and electronic health records research, as well as frameworks for model evaluation and bias correction. He has a Ph.D. in Cognitive Psychology from New York University, where his research in the shared statistical biases of human and machine learning was published in journals such as Nature Machine Intelligence.
Ariel is a software engineer at Inductive Bio. Before Inductive, she was a software engineer at Palantir Technologies, where she focused on developing greenfield data analytics products with machine learning integrations. She also has experience as a forward deployed engineer at Palantir, leading teams that created data operations platforms for healthcare customers. Previously she conducted research at CSAIL, where she built applications and published work at the intersection of healthcare, machine learning, and human-computer interaction. Ariel holds a bachelor's degree in Computer Science from MIT.
Wendy is a biotechnology, pharma, and life science executive with more than 30 years of experience in the discovery and development of novel therapeutics. She was formerly the Senior Vice President at Genentech, where she actively built and led the small molecule drug discovery organization and co-led research. Under her leadership, more than 25 clinical candidates, in the areas of oncology, immunology, neurology, and anti-infectives, progressed into development. Additionally, Wendy led the BTK discovery program and is co-inventor of fenebrutinib. Prior to Genentech she held senior drug discovery leadership roles at J&J and Celera Genomics. She currently serves as an advisor to Google Ventures and is an associate editor of the Journal of Medicinal Chemistry. She received her Ph.D. in chemistry from Princeton University and was an American Cancer Society Postdoctoral Fellow at Sloan Kettering Cancer Center.
Andrew has served in multiple senior scientific roles, including VP of Computational Chemistry at Expansion Therapeutics, Senior Director of CADD / cheminformatics at C4 Therapeutics, and Distinguished Scientific fellow at Genzyme. Andrew is a co-inventor on 14 projects that have led to IND candidate nomination including the HCV drugs Daclatasvir and Asunaprevir, resulting in a 2017 ACS heroes of chemistry award. He has pioneered several widely applied CADD techniques, including pharmacophore constraint usage, 3D pharmacophore fingerprints and Gaussian function approximations for molecular similarity calculations. Andrew has authored over 100 research articles and is a co-inventor on more than 50 patents.
Ankit Mahadevia, MD, is a co-founder and Chairman of Spero Therapeutics, where he previously served as CEO. Prior to Spero, he was a Venture Partner at Atlas Venture. He has co-founded nine therapeutics companies, including Nimbus Therapeutics, Arteaus Therapeutics (acquired by Lilly), and Translate Bio (acquired by Sanofi). Ankit served as CEO for several of these, including Synlogic (Nasdaq: SYBX) and Rodin Therapeutics (acquired by Alkermes). Prior to Atlas, he worked at Arcion Therapeutics, Genentech, Vanda Pharmaceuticals, McKinsey & Company, and Monitor Group. His career began in health care policy, with roles at the U.S. Senate Health, Education, Labor, and Pensions Committee, and the Government Accountability Office.
Mark is a leader in applying computational and statistical techniques to biomedical challenges in genomics and biochemistry. He is currently CEO and Co-Founder of BigHat Biosciences. Prior to that, he founded the Genomics team in Google Brain, was VP of Informatics at SynapDx, and was Co-Director of Medical and Population Genetics at the Broad Institute. He has a BA in CS and Math from Northwestern, a PhD in Biochemistry from Cambridge as a Marshall Scholar, and was a Damon Runyon Cancer Research Fellow at Harvard. Dr. DePristo's academic articles are widely published with more than 110,000 citations.