Ph.D., Stanford Lecturer and Director of Stanford Deep Data Research Computing Center, Stanford University
Biography
Dr. Amir Bahmani is the Director of Stanford Deep Data Research Computing Center. He has been working on large-scale distributed and parallel computing applications since 2008. He 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), Stanford Integrated Personal Omics Profiling (iPOP) and Stanford Healthcare Innovation Lab. As a computer scientist, he is passionate about bridging the gap between computer scientists and biologists/physicians. He successfully launched Stanford University’s first Cloud Computing for Healthcare course, offered to students in Biology, Computer Science, Genetics, and Biomedical Data Science departments. His research draws on computationally intensive medical applications, cloud computing, data privacy in medical applications, database management systems, and pervasive and ubiquitous computing.
Talk
Deep Data in Precision Medicine
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 the potential impact on the field of bioinformatics from a Computer Science perspective.
Session Abstract – PMWC 2022 Silicon Valley
The value of data in healthcare is undeniable and realized when raw information is successfully converted into knowledge that changes clinical practice. To drive value improvements and ensure that the right patient receives the right care requires the right data in combination with the right data analytics. This session will cover various aspects and challenges of data science in hospitals and health systems that drive healthcare with better outcomes.
Sessions:
- Data Sharing Application: Needs, Advancements, and Challenges
- Russ Cucina, UCSF
- Removing Data Sharing Barriers; Expectations for the Healthcare Industry
Session Chair: Riddhiman Das, TripleBlind
- John Halamka, Mayo Clinic
- David Albert, AliveCor Inc. - Next-Generation Data Sharing: Discoverable, Accessible, Interoperable Data (PANEL)
Session Chair: John F. Kalafut, Asher Orion Group
- Joel Sevinsky, Theiagen Genomics
- Ittai Dayan, Rhino Health
- Sharmila Majumdar, UCSF
- Rajan Wadhwa, Anthem - Sustainable Data Systems via FAIR Data Principles
Session Chair: Alex Sherman, MGH
- Multi-Factor Data Science to Inform Clinical Research
Session Chair: Charlotte Nelson, MATE Bioservices
- Gundolf Schenk, UCSF - Translational AI: Innovation to Clinical Implementation and Reimbursement (PANEL)
Session Chair: John J. Sninsky, Translational Consultant
- Katy Wack, PathAI
- Steve Anderson, LabCorp
- Nigam Shah, Stanford
- Rachael A Callcut, UCD - Leveraging Multiomic Data to Advance Rare Disease Drug Discovery and Development (PANEL)
Session Chair: Justin Bingham, CENTOGENE
- Purvesh Khatri, Stanford
- Michael Hund, EB Research Partnership - AI/ML in Hospitals and Clinics / Digital Health Transformation / Predicting Clinical Outcomes
Session Chair: Robert Hauser, Vidence
- Alan Kaplan, LLNL
- Peter Yu, Hartford Healthcare
- Amir Bahmani, Stanford
- Andrew Le, Buoy Health - PMWC 2022 Showcase
- Kelly Hall, InheRET, Inc.
- Calum Macrae, Harvard
