This event is part of the DCI Network Webinars on COVID-19 Data Platforms and Telemedicine event series.
How engineers and biologists worked together to create a large-scale study for detecting infectious diseases such as COVID-19
Amir Bahmani, PhD
Director of Stanford Deep Data Research Computing Center
Lecturer at Stanford University
We are currently at the beginning stages of a generation-defining revolution in biology. For the past two decades, breakthroughs in our understanding of genetics and genomics, coupled with those in AI and machine learning, have presented us with opportunities to radically improve healthcare around the world. Data is now a digital specimen, but as more and more data is collected, often in different formats and on disparate platforms, new solutions are needed to successfully integrate, store, compute, and secure data. This talk provides a short set of examples for how to handle large-scale medical studies in a secure and scalable fashion. It assesses contemporary realities, identifies potentially promising research directions, and investigates potential impact on the field of bioinformatics from a Computer Science perspective.
Dr. Amir Bahmani has been working on large-scale parallel computing and cloud computing applications since 2008. Amir’s research draws on computationally intensive medical applications, cloud computing, data privacy in medical applications, database management systems, and pervasive and ubiquitous computing. As a computer scientist, he is very passionate about bridging the gap between computer scientists and biologists/physicians. Amir is an active researcher in the VA Million Veteran Program (MVP), Human Tumor Atlas Network (HTAN), the Human BioMolecular Atlas Program (HuBMAP), Stanford Metabolic Health Center (MHC) and Stanford Integrated Personal Omics Profiling (iPOP). In 2018, Amir successfully launched the first graduate internship program at Stanford School of Medicine for training Computer Science students at the Genetics department. Amir also successfully created and launched Stanford’s first Cloud Computing course for Biology and Healthcare, offered to students in Biology, Computer Science, Genetics, and Biomedical Data Science departments. In addition to his teaching activities, Amir leads a large team of computer scientists bioinformaticians and his team has designed and developed several notable cloud-scale frameworks such as Personal Health Dashboard (PHD) and cloud-based cost saving platforms like Hummingbird and Swarm that are now being used at Stanford and is rapidly spreading to other labs (in several universities (e.g., UPenn, UCLA) to accelerate otherwise-infeasible research studies. His team also created Stanford Data Ocean (SDO), another innovative platform for educating engineers and biologists. SDO is the first serverless multi-omics and wearables data platform to be used for education and training.
Learn more at: https://web.stanford.edu/~abahman/