I am a Director and AI Lead in the Digital Sciences & Translational Imaging group within Pfizer R&D. I am interested in medical imaging, machine learning, and drug R&D.
I received a Bachelor’s degree in Chemistry from Nankai University, a Master’s degree in Computer Science (specialization in Machine Learning) from Georgia Institute of Technology, and a PhD from Washington University in St. Louis. My PhD thesis focused on cancer imaging:
During my PhD, I did an internship at Schlumberger, where my research focused on spin physics simulation and virtual prototyping for oil well logging.
Following PhD, I did my postdoctoral research on cardiovascular imaging at Beth Israel Deaconess Medical Center and Harvard Medical School. Before I joined Pfizer in 2019, I had a stint at Invicro, working as a Study Director to support imaging programs for pharma/biotech clients.
I currently lead the development and deployment of novel ML/AL-based solutions to support drug R&D programs across therapeutic areas. Some recent projects include:
- A fully automated AI system for analyzing echocardiography videos. This project won Pfizer’s Breakthrough Science & Innovation award in 2021, the highest honor that can be bestowed to an R&D colleague.
- Using AI to assess solid tumor treatment response in clinical trials and unlock novel endpoints for early decision making that can accelerate drug discovery and development, in collaboration with Vysioneer.
- Representing Pfizer in the FNIH Mucosal Healing in Ulcerative Colitis consortium, a public-private collaborative effort to define the best practice for measuring mucosal healing, including a machine learning method for scoring of mucosal healing that can be used in clinical trials, regulatory approvals, and clinical practice.
I am also responsible for the development of AI and Data strategy for clinical imaging across the organization.