Ph.D., Chief Technology Officer, Pangea Biomed
Biography
Ranit is an AI researcher and expert with two decades of handson experience. She works to advance Pangeas machinelearning tumor intelligence platform, enabling deeper understanding of how a tumor would respond to therapy. Prior to her role with Pangea, Ranit worked at IBM Research AI where her team developed Project Debater, the first AI system capable of debating humans on complex topics. In February 2019, the AI system won the Edison Award in Social Innovation Artificial Intelligence. Ranit continued at IBM Research managing Natural Language Processing (NLP) teams before transitioning to become CTO of Pangea. For almost a decade before joining IBM, Ranit served as the Vice President of R&D at Rosetta Genomics (NASDAQ: ROSG). Rosetta Genomics developed microRNAbased molecular diagnostics. The company won the Wall Street Journal Technology Innovation award in 2008 while Ranit led the R&D efforts, including directly supervising all computational biology, software development and IP.
Talk
AI and Data Sciences Showcase:
Pangea Biomed
Pangea Biomed created ENLIGHT, the world’s most advanced multi-cancer, multi-therapy response predictor. By combining machine learning and deep RNA analysis, the company analyzes tumor molecular signatures to uncover cancer vulnerabilities missed by standard molecular profiling, for effective personalized cancer care and accelerated drug development.
Using AI to Democratize Precision Oncology
How genetic interaction analysis advances the utility and accessibility of precision oncology.
Session Abstract – PMWC 2023 Silicon Valley
Showcase Track S1 - January 25 9.00 A.M.-1.15 P.M.,Showcase Track S1 - January 26 11.30 A.M.-1.15 P.M.,Showcase Track S1 - January 27 11.00 A.M.-1.15 P.M.
The PMWC 2023 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
