Speakers Knowledge Support Reviewers Organizers.
John is a UC Berkeley grad. who majored in film. He has suffered from a life-long unknown condition characterized by chronically low body weight, weakness, GI issues, and pain. He is an advocate for rare and undiagnosed disease and actively works on connecting the field. John lives in Los Angeles and will be joining us for the weekend.
SVAI Team Member
Organizer - SVAI Welcoming Talk
Annabelle participated in SVAI’s first patient genomics hackathon and joined the SVAI team shortly after. She was a critical part of organizing our second patient research case and recently helped run Stanford’s first Health AI hackathon. She studied molecular, cell and developmental biology at UC Santa Cruz and has held positions at Natera, Gaurdant Health and Facebook.
Ben Busby, PhD
Computational Biology Branch, NCBI, NLM, NIH
MC - Knowledge Support - Reviewer
Ben leads the NIH's efforts to partner with Genomics hackathons. His research interests include generation of clustering algorithms for analysis of large gene families and whole genomes and Phylomic Analysis of Gene Transfer Events. Ben holds a PhD in Biochemistry and Molecular Biology from University of Maryland, Baltimore.
Co-Founder and Head of Organizational Development, Invitae
In 2010, Alex Furman co-founded Invitae, one of the fastest growing genetic testing companies. The company is executing a novel business model focused on reducing the cost of genetic testing and making it affordable and accessible to all in order to help usher in the era of genetic medicine. For Invitae, Alex initially worked on software development and bioinformatics, and now currently leads the company’s efforts to create a collaborative culture that delivers innovation at scale. Prior to founding Invitae, Alex led software engineering at Navigenics, overseeing the design and implementation of the company’s technology platform. Alex also has experience developing automated trading systems and financial planning software.
Ed Esplin MD PhD
Clinical Geneticist, Invitae
Specialties: Medical Genetics, Preventional Genetics, Cancer Genomics, Genomic Medicine, Internal Medicine
Ed recieved his M.D. and Ph.D. at The University of Texas Southwestern Medical Center at Dallas with a focus on Genetics. He completed a Residency/Fellowship in the Field Of Study Human/Medical Genetics at Stanford University School of Medicine.
SVAI Team Member.
Technical Development Engineer, Individualized Neoantigen Specific Therapeutics, Genentech.
[Co-MC, Knowledge Support, Analysis Reviewer]
"Ryan is a Technical Development Engineer at Genentech working on individualized neoantigen specific therapeutics, an mRNA-based platform for mobilizing an immune response against cancer based on an individual patient's tumor mutations. Prior, his experience spanned biologics process development, bioinformatics, cell therapy and tissue engineering. Ryan is motivated by the promise of personalized healthcare, particularly through the convergence of proactive patient monitoring, dynamic data exchange and individualized medicine."
MSc candidate, Vector Institute
Amy is a MSc candidate at Vector Institute where she works on applying weakly supervised deep learning methods for understanding genomic functions. Amy was previously a researcher at Harvard Medical School where she was using deep learning to understand the genomic underpinnings of disease phenotypes. Her work also focused on interpreting important model features to seek novel disease-associated gene variants for clinical treatment. She graduated from University of Waterloo with a BS in Science and Bioinformatics.
Jason Chin PhD
Sr. Director, Deep Learning in Genomics, DNAnexus
Jason is an experienced researcher and senior director level manager with a demonstrated history of working in the biotechnology industry. He is a strong research professional skilled in algorithm development, DNA sequencing, biotechnology, sequencing, research and development (R&D), and life sciences. He previously served as Scientific Fellow, Sr. Director, Bioinformatics at Pacific Biosciences. Jason graduated from Tsing Hua University, completed his PhD at University of Washington and then did a Postdoc at UCSF.
Ankita Das, PhD
Marketing Manager, MEDGENOME.
Ankita specializes in studying Epigenetic mechanisms that regulate stem and progenitor cell differentiation during development. She has extensive experience in studying various vertebrate organisms including zebrafish and mice to study in vivo developmental processes, using imaging & genetic strategies. She is enthusiastic about entrepreneurship, and has designed a mentoring program serving Hopkins fellows considering careers in entrepreneurship / start-ups and venture capital strategists. She also serves on the board of Innovation Factory at JHU Carey School of Business to facilitate team building and peer mentoring between business school and science students interested in Entrepreneurship.
CTO at doc.ai.
Akshay’s interests are in developing and applying poly-omics data combinations to healthcare and life sciences. Building the Real-World-Evidence based data collection and sharing tools to empower users to take control of their health. The natural extension to these interests are applied towards Clinical trials and Observational trials and Personalized health predictions He had developed:
doc.ai’s Medical research companion app, crestle.ai: Deep learning platform with prediction machine (for life sciences) and MyWobble/Genewall, a Bioinformatics app to understand your genome. “I am attracted to the magnetic allure of biology and healthcare.”
Hari Singhal, PhD
Lead Data Scientist, Diagnostics Information Solutions at Roche.
“I have experience in leading projects that apply big data, machine learning and artificial intelligence techniques for understanding molecular mechanisms that promote cancer. My research interests are to investigate the regulatory networks that drive cancers and to deploy the generated knowledge for improvement of healthcare. More recently I have been researching the immunotherapeutic basis of blocking PDL1 for treating patients with advanced solid tumors of lung, renal and urothelial tissues.” previously, Hari was a cancer genomics scientist at Harvard Medical School. He completed his PhD in cancer oncology at University of Chicago.
Avantika Lal, PhD
Deep Learning Genomics Scientist at NVIDIA.
Avantika recently joined NVIDIA - Previously she was a BRCA Foundation Young Investigator at Stanford University. Her scientific accomplishments include discovering clinically relevant subtypes of 21 cancers by developing CIMLR, a novel clustering algorithm for multi-mic data, while working as a Postdoctoral Researcher at Stanford University. Avantika also developed a machine learning algorithm to identify mutational process active in cancer and neural networks to identify potential antimalarial drug targets. Avantika received her Ph.D. in Genomics from the National Centre for Biological Sciences in India.
Avantika led one of the winning teams form our NF2 Research Hackathon.
Alexandre Colavin PhD
Alexandre is the cofounder of Jungla, which seeks to maximize the impact of genomic information across healthcare and lifesciences through advanced experimental and computational innovations in a transparent, actively learning platform. As the Lead of Technical Development at Jungla, Alex is chiefly responsible for architecting Jungla's Unified Computational Platform, which leverages a unique workflow-first architecture for accessibility, scalability and reproducibility of computational biology spanning biophysics, genomics and clinical genetics. Alex is the coauthor of numerous academic manuscripts and patent applications, and is passionate about technology development that enables teams to fulfill their full potential. Alexandre received PhD in Biophysics from Stanford University.
PhD Candidate at Stanford University.
“I'm a graduate student in Bioengineering interested in precision health, drug discovery/repurposing, understanding the biology underlying disease, and predicting health outcomes. I apply statistics and machine learning to population genomics data. I'm also involved in consulting projects and teaching experiences encompassing technology transfer and regulatory processes.”
"My current interests are primarily in deep learning for computer vision, image search, and visual similarity search. I am also particularly interested - both from a research perspective as well as a productization perspective - in intelligent systems that allow users to express search intentions or information-needs in nuanced ways that are otherwise difficult to express by language or classical search tools." Clay complted his graduate studies at Stanford University with a dual focus in Human-Computer Interaction and Artificial Intelligence. Prior to joining Google, he worked on Computer Vision and Machine Learning Team at Yahoo on many topics, including scaling deep learning and computer vision technologies for Yahoo products, product integrations, large-scale approximate nearest neighbor search, deep learning for visual similarity search, and visualization tools."
Orion Buske PhD
CEO at Gene42
TORONTO SITE LEAD
Orion Buske is CEO of Gene 42, where he works on structured data for precision medicine. Previously he was an instructor of computer science at University of Toronto. Orion studied Bioengineering and Biomedical Engineering at University of Washington then completed a MSc in Computer Science and PhD in Computational Biology from the University of Toronto. He has worked on developing algorithms for analyzing human genomic data, including matching algorithms behind the scenes of Phenome Central, a patient-matching hub to help clinicians solve rare and undiagnosed diseases.
Co-Founder & CEO at Mendelian.co
LONDON SITE LEAD
Rudy’s work with Mendelian contributes to diagnosing rare diseases faster. Mendelian is continuously adding, curating and analysing conditions, symptoms, and genes along with clinical tests in order to build the most comprehensive Rare Disease Knowledge Base. Rudy graduated from Imperial College London where he studied computer engineering.
Dmytro Lituiev PhD
Postdoctoral Scholar, Computational Health Science, UCSF School of Medicine
Dmytro is working on a range of projects in digital pathology and radiology aiming at data mining, predictive modeling, and AI-assisted diagnostics. He Previously developed a Inference Algorithm for Genetic Mapping with High-Throughput Sequencing,which is aimed to facilitate and accelerate the procedure of genetic mapping for experimentalbiology and breeding by using a probabilistic model to reduce sequencing noise and accountfor stochastic variation.
Jennifer P. PhD
Principal Genome Scientist at QIAGEN
“With 17 years of training and experience, I am a geneticist with expertise spanning clinical and research applications, in both academic and commercial settings. With curiosity and self-motivation, I’ve made contributions to the cancer genetics field, identifying novel therapeutic targets and generating models for disease. In my current role, I have been responsible for managing QIAGEN's clinical exome product and a carrier screening solution, while also assisting the sales team through meeting with KOLs, and forging my own relationships to better understand genetic testing needs. I am passionate about building relationships to initiate collaborations, and translating customer feedback into new product development. I am a consummate professional, with a sense of deep responsibility to the customer above anything else.”