We are building a platform to unlock early detection of disease. Destruction of healthy and diseased cells is a hallmark of all disease. Our interpretable artificial intelligence technology utilizes epigenomic profiles to detect these events in cell-free DNA.
953 Indiana St, San Francisco CA, 94107
415-322-3343
info@ravel.bio
Nathan co-founded Ravel and secured its Seed funding in 2019. Nathan was the VP of Technology at Driver where he led the software engineering and R&D teams to develop a cfDNA assay for the identification of somatic variants. He was a contributing computational biologist in the Data Analysis group for the ENCODE and modENCODE projects resulting in publications in Science and Nature. Nathan received his PhD from UC Berkeley in biostatistics where he developed statistical methods for the analysis of functional genomic data under Peter Bickel. As a postdoc in Anshul Kundaje’s lab at Stanford, he developed deep learning models for the analysis of DNA-protein binding events. In his free time, he enjoys spending time with his family.
Paul is the Chief Scientific Officer at Ravel and is leading efforts to commercialize our diagnostic products for early disease detection, including devising strategies to address regulatory and stakeholder requirements. Paul has over two decades of experience developing epigenomic technologies and analytic tools for improving human health in both industry and academia. These technologies have been widely adopted across a variety of research efforts, including international consortia formed to investigate the epigenome. As an American Cancer Society fellow at Stanford University he invented ATAC-seq, which has rapidly become the standard for measuring the epigenome. He also was a co-founder of Epinomics, which was based on this technology, and was acquired by 10x Genomics. In his free time, Paul enjoys spending time with family and friends.
Erik leads the implementation of bioinformatics and machine learning software for production and R&D. Before Ravel, Erik was a computational biology and machine learning consultant. He was an early employee and top technical contributor at Invitae, now one of the world’s largest clinical DNA sequencing companies, where he developed novel NGS clinical assays, bioinformatic and probabilistic models, and production bioinformatic software systems. He spent several years as a Senior Research Associate in the Lab for Personalized Medicine at Harvard Medical School, where he developed methods and software to analyze NGS data in the context of translational medicine. He holds two bachelors degrees, one in Computer Science and one in Physiology. Erik enjoys cooking, staying active, and keeping up to date with the latest in Machine Learning.
Adam is responsible for NGS Assay Development and oversees the cfDNA sample processing Laboratory. He has experience in all stages of clinical and non-clinical development/optimization, technical transfer, and laboratory automation. Before joining Ravel, Adam developed a targeted cfDNA assay for somatic variant detection, which was the initial CLIA-validated product at Driver. Adam also led assay development efforts that were critical to launching colorectal cancer detection test at Freenome Inc. Adam attended UC Berkeley for his undergraduate degree in Biochemistry and Molecular Biology and earned a MSc in Biotechnology at San Francisco State University.
Adam likes spending time in Central America with family and friends, enjoying nature and everything the ocean has to offer.
Jane is responsible for Clinical Operations at Ravel, including oversight of research and development programs and integration with academic and commercial partners. She has experience building and managing technical teams in a regulated environment, and has extensive knowledge of next-generation sequencing technologies and applications. Prior to joining Ravel, Jane worked in various roles with increasing responsibilities at Pacific Biosciences and Lawrence Berkeley National Laboratory. She was a contributing scientist in the ENCODE and modENCODE projects to map all functional elements in the human and drosophila genomes. In her spare time, Jane enjoys making science kits with her kids, biking, and spending time outdoors.
Omid is a Senior Machine Learning Research Scientist at Ravel Bio. He received his PhD in Statistics from UC Berkeley, under Prof. Peter Bickel’s supervision, where he wrote his thesis on interpretable multi-view learning models applied to high-dimensional multi-omic datasets, which resulted in the packages MuLe, BLOCCS, and SparKLe. In his postdoc with Prof. Bin Yu and Dr. Ben Brown from LBNL, he worked on interpretable AI technologies, specifically interpretable generative models. Prior to his Ph.D., he received his Masters’ degree in Applied Mathematics from UC Berkeley. He has also worked as a freelance statistical consultant for a handful of companies and academics. Statistics, genomics, plants, motorcycles, and world literature are his main passions.
Artur is the Senior Computational Biologist at Ravel. He is a long-time UCLA Bruin, beginning with his B.S in Math and Computational & Systems Biology. Afterwards, he completed his PhD in Bioinformatics with Dr. Jason Ernst, during which Artur developed novel machine learning methods to study epigenomic controls of gene regulation. He has presented this research at various conferences, including NIPS and ISMB. Artur’s years at UCLA culminated as a mathematics lecturer. After a research internship and consultantship at Freenome, Artur joined Ravel to continue the fight against cancer. In his free time, Artur enjoys climbing, martial arts, petting dogs, and crafting cocktails.
Anshul Kundaje is an Assistant Professor of Genetics and Computer Science at Stanford University. His primary research area is large-scale computational regulatory genomics. The Kundaje lab specializes in developing statistical and machine learning methods for large-scale integrative analysis of heterogeneous, high-throughput functional genomic and genetic data to decipher regulatory elements and long-range regulatory interactions, learn predictive regulatory network models across individuals, cell-types and species and improve detection and interpretation of natural and disease-associated genetic variation.
Dr. Jeffrey is the Chief of Surgical Oncology Research in the Department of Surgery at Stanford University School of Medicine. Dr. Jeffrey was a founding member of the Stanford-Norway team that pioneered the molecular classification of breast tumors into distinct subtypes, including luminal and basal-like/triple-negative breast cancers. Her research expertise is on molecular profiling, technology development, and liquid biopsy, including investigations of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and targeted extracellular vesicles (EVs/exosomes) from patient samples and patient-derived models of breast and metastatic colorectal cancer. Dr. Jeffrey is a thought leader, serving as Co-Chair to the Gordon Research Conference on Liquid Biopsy for Cancer, and authoring perspective pieces in high-profile journals such as Science.
We are building a platform to unlock early detection of disease. Destruction of healthy and diseased cells is a hallmark of all disease. Our interpretable artificial intelligence technology utilizes epigenomic profiles to detect these events in cell-free DNA.
953 Indiana St, San Francisco CA, 94107
415-322-3343
info@ravel.bio
Nathan co-founded Ravel and secured its Seed funding in 2019. Nathan was the VP of Technology at Driver where he led the software engineering and R&D teams to develop a cfDNA assay for the identification of somatic variants. He was a contributing computational biologist in the Data Analysis group for the ENCODE and modENCODE projects resulting in publications in Science and Nature. Nathan received his PhD from UC Berkeley in biostatistics where he developed statistical methods for the analysis of functional genomic data under Peter Bickel. As a postdoc in Anshul Kundaje’s lab at Stanford, he developed deep learning models for the analysis of DNA-protein binding events. In his free time, he enjoys spending time with his family.
Paul is the Chief Scientific Officer at Ravel and is leading efforts to commercialize our diagnostic products for early disease detection, including devising strategies to address regulatory and stakeholder requirements. Paul has over two decades of experience developing epigenomic technologies and analytic tools for improving human health in both industry and academia. These technologies have been widely adopted across a variety of research efforts, including international consortia formed to investigate the epigenome. As an American Cancer Society fellow at Stanford University he invented ATAC-seq, which has rapidly become the standard for measuring the epigenome. He also was a co-founder of Epinomics, which was based on this technology, and was acquired by 10x Genomics. In his free time, Paul enjoys spending time with family and friends.
Erik leads the implementation of bioinformatics and machine learning software for production and R&D. Before Ravel, Erik was a computational biology and machine learning consultant. He was an early employee and top technical contributor at Invitae, now one of the world’s largest clinical DNA sequencing companies, where he developed novel NGS clinical assays, bioinformatic and probabilistic models, and production bioinformatic software systems. He spent several years as a Senior Research Associate in the Lab for Personalized Medicine at Harvard Medical School, where he developed methods and software to analyze NGS data in the context of translational medicine. He holds two bachelors degrees, one in Computer Science and one in Physiology. Erik enjoys cooking, staying active, and keeping up to date with the latest in Machine Learning.
Adam is responsible for NGS Assay Development and oversees the cfDNA sample processing Laboratory. He has experience in all stages of clinical and non-clinical development/optimization, technical transfer, and laboratory automation. Before joining Ravel, Adam developed a targeted cfDNA assay for somatic variant detection, which was the initial CLIA-validated product at Driver. Adam also led assay development efforts that were critical to launching colorectal cancer detection test at Freenome Inc. Adam attended UC Berkeley for his undergraduate degree in Biochemistry and Molecular Biology and earned a MSc in Biotechnology at San Francisco State University.
Adam likes spending time in Central America with family and friends, enjoying nature and everything the ocean has to offer.
Jane is responsible for Clinical Operations at Ravel, including oversight of research and development programs and integration with academic and commercial partners. She has experience building and managing technical teams in a regulated environment, and has extensive knowledge of next-generation sequencing technologies and applications. Prior to joining Ravel, Jane worked in various roles with increasing responsibilities at Pacific Biosciences and Lawrence Berkeley National Laboratory. She was a contributing scientist in the ENCODE and modENCODE projects to map all functional elements in the human and drosophila genomes. In her spare time, Jane enjoys making science kits with her kids, biking, and spending time outdoors.
Omid is a Senior Machine Learning Research Scientist at Ravel Bio. He received his PhD in Statistics from UC Berkeley, under Prof. Peter Bickel’s supervision, where he wrote his thesis on interpretable multi-view learning models applied to high-dimensional multi-omic datasets, which resulted in the packages MuLe, BLOCCS, and SparKLe. In his postdoc with Prof. Bin Yu and Dr. Ben Brown from LBNL, he worked on interpretable AI technologies, specifically interpretable generative models. Prior to his Ph.D., he received his Masters’ degree in Applied Mathematics from UC Berkeley. He has also worked as a freelance statistical consultant for a handful of companies and academics. Statistics, genomics, plants, motorcycles, and world literature are his main passions.
Artur is the Senior Computational Biologist at Ravel. He is a long-time UCLA Bruin, beginning with his B.S in Math and Computational & Systems Biology. Afterwards, he completed his PhD in Bioinformatics with Dr. Jason Ernst, during which Artur developed novel machine learning methods to study epigenomic controls of gene regulation. He has presented this research at various conferences, including NIPS and ISMB. Artur’s years at UCLA culminated as a mathematics lecturer. After a research internship and consultantship at Freenome, Artur joined Ravel to continue the fight against cancer. In his free time, Artur enjoys climbing, martial arts, petting dogs, and crafting cocktails.
Anshul Kundaje is an Assistant Professor of Genetics and Computer Science at Stanford University. His primary research area is large-scale computational regulatory genomics. The Kundaje lab specializes in developing statistical and machine learning methods for large-scale integrative analysis of heterogeneous, high-throughput functional genomic and genetic data to decipher regulatory elements and long-range regulatory interactions, learn predictive regulatory network models across individuals, cell-types and species and improve detection and interpretation of natural and disease-associated genetic variation.
Dr. Jeffrey is the Chief of Surgical Oncology Research in the Department of Surgery at Stanford University School of Medicine. Dr. Jeffrey was a founding member of the Stanford-Norway team that pioneered the molecular classification of breast tumors into distinct subtypes, including luminal and basal-like/triple-negative breast cancers. Her research expertise is on molecular profiling, technology development, and liquid biopsy, including investigations of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and targeted extracellular vesicles (EVs/exosomes) from patient samples and patient-derived models of breast and metastatic colorectal cancer. Dr. Jeffrey is a thought leader, serving as Co-Chair to the Gordon Research Conference on Liquid Biopsy for Cancer, and authoring perspective pieces in high-profile journals such as Science.
953 Indiana St, San Francisco CA, 94107
415-322-3343
info@ravel.bio
© 2020 Ravel Biotechnology
953 Indiana St, San Francisco CA, 94107
415-322-3343
info@ravel.bio
© 2020 Ravel Biotechnology