Deep Genomics was founded by Professor Brendan Frey of the University of Toronto. The founding team has made fundamental contributions to the fields of machine learning and genome biology, and has published extensively in Science, Nature, and Cell.
Our small and growing team includes silicon valley entrepreneurs, machine learning researchers, clinical geneticists, computational biologists, and software engineers from all over the world. What unites our ambitious and diverse team is the belief that the convergence of machine learning and genome biology will transform how we understand and make use of our personal genomes. If this sounds like something you’d like to be a part of, please don't hesitate to contact us.
We Are Deep Genomics
Brendan Frey, PhD, FRSC
President & Chief Executive Officer
Brendan has made fundamental contributions to the fields of machine learning and genome biology, both in research and in industry. He led the team that developed a deep learning method for identifying the splicing-related genetic determinants of disease, which was published in the January 9, 2015 edition of Science Magazine. In the past twenty years, he has co-authored over 12 papers in Science, Nature and Cell, including one of the first papers on deep learning (Science, 1995). Brendan is a co-inventor of the affinity propagation algorithm and of the factor graph notation for graphical models. He has consulted for over a dozen machine learning-powered companies, has served on the technical advisory board of Microsoft Research, holds seven patents, and has served as an expert witness in patent litigation. Brendan’s former team members include entrepreneurs, industrial researchers, and professors at highly recognized centers in Canada, the United States, England and Europe.
Andrew Delong, PhD
Science & Technology
Andrew is a research scientist and software developer. He holds a PhD in Computer Science for which he received the 2011 Doctoral Dissertation Award from the Canadian Image Processing and Pattern Recognition Society. He came to Toronto on an NSERC Postdoctoral Fellowship to study genomics and deep learning with the world's best, going on to publish the first deep learning paper to ever appear in Nature Biotechnology. He his a co-recipient of an Invention of the Year Award from the University of Toronto. Previously, Andrew has been a computer science instructor, a computer vision researcher, and has worked several years as a professional software engineer in the computer graphics industry, including work on Autodesk Maya.
Hui Yuan Xiong, PhD
Science & Technology
Hui is an engineer, researcher and entrepreneur. He studied in the Engineering Science division and the machine learning group at University of Toronto. Hui specializes in discovering and building accurate mathematical models for real world data by running computer algorithms. His models have outperformed the state-of-the-art systems on a wide range of applications including image recognition, stock markets, and genomic and disease cataloguing. These discoveries have led to top-tier academic publications as well as high-impact commercial applications, and have been featured in Wired, Scientific American, Quanta, CBC, and the National Post.
Hannes Bretschneider, MSc
Engineering & Science
Hannes is a software developer and a researcher in computational biology and machine learning. He holds BSc and MSc degrees from Humboldt-Universität zu Berlin. Hannes works on alternative splicing and end-to-end feature learning for DNA sequences. He has published in leading journals such as Science and Nature Methods. Hannes is the creator of the popular open source projects Hebel and cudnn-python-wrappers and has a wide range of technical skills including GPU programming, cloud computing, and Linux system administration.
Daniele Merico, PhD
Daniele is a computational biologist specializing in the discovery and annotation of disease-causing variants. He received a PhD in Molecular and Cell Biology from the University of Milano in 2009, and developed pathway analysis techniques as a post-doctoral fellow with Dr. Gary Bader at the University of Toronto. For five years he was Informatics Core Facility Manager of The Centre for Applied Genomics at the Hospital for Sick Children, reporting to Dr. Stephen Scherer and supervising >10 analysts working on next generation sequencing, genome copy number variation, and large-scale human genetics research with a focus on autism and developmental congenital disorders.
Jinkuk Kim, PHD
SciencE & Technology
Jinkuk is a research scientist specializing in RNA and cancer genomics. Jinkuk received his PhD in Bioinformatics and Integrative Genomics from MIT, where he studied small RNA genomics with David Bartel on a fellowship. He also studied glioblastoma genomics for five years at Samsung Medical Center in South Korea as part of his military service. His research has led to high impact publications in journals including Science, Nature Biotechnology, and Cancer Cell.
Matt Cahill, PhD, JD, MBA
Matt began his career in microbial genomics, earning his PhD from the University of Cambridge and working several years as a post-doctoral researcher. He has degrees in both law (JD) and business (MBA), and is pursuing the commercialization of “-omic" biology.
Troy earned his Bachelor of Computer Science from the University of Waterloo in 2006 and has been passionately engaged in entrepreneurship ever since. As both a founder and early team member at several companies, he has helped them move from prototype to high growth. Troy has led teams of engineers to develop data-driven business solutions for both social and mobile marketing. Specializing in scalable backends, he has built complex systems to understand and to extract value from big data. Troy is also an outdoors enthusiast, and is pursuing a black belt in Brazilian Jiu-Jitsu.
Alice Gao, MASc
Engineering & Science
Alice is an engineer, machine learning researcher, and software developer. She holds BASc and MASc degrees from the University of Toronto, and started her PhD in the machine learning group on an NSERC Scholarship. She works on machine learning systems that predict the effects of protein coding mutations, and has expertise working with NGS bioinformatics pipelines.
Khalid Zuberi, MSc
Khalid is a software developer specializing in scientific computing and data processing systems. He was responsible for building the computational engine and data pipeline for GeneMANIA, a gene function prediction system developed at the University of Toronto. Khalid has also developed software for the geomatics industry, and has extensive production experience with backend data systems supporting commercial SaaS applications. Khalid holds a BMath degree from the University of Waterloo, and an MSc from the University of Toronto.
Some team photos courtesy of Christian Senger