Biography

Research Focus
My main research aim is to better predict and prevent complications in surgical patients using advanced machine learning techniques.
My work includes:
Real-Time Risk Assessment: Creating models to predict acute kidney injury (AKI), pain, delirium, and blood loss during surgeries in real-time.
Model Validation: Ensuring these models are reliable with the eventual goal of pursuing regulatory approval.
I strive to build models that I would want to use when caring for patients. Additionally, my research explores the space of computer-human interfaces related to artificial intelligence (AI) to seamlessly integrate these models into clinical workflows.

Clinical Practice
As an anesthesiologist, I am committed to providing safe and effective patient care in the operating room. My clinical work is closely linked with my research, fostering an environment where new insights directly benefit patient outcomes.

Commitment to Progress
I value the opportunity to contribute to meaningful advancements in healthcare. By integrating innovative technology into clinical practices, I seek to improve patient outcomes and advance the field of perioperative medicine.

Education

06/2022 - Diversity, Equity, and Inclusion Champion Training, University of California
06/2020 - Medical Informatics and Artificial Intelligence, Bakar Computational Health Sciences Institute at University of California, San Francisco (UCSF)
D.ABA., 05/2019 - Anesthesiology, University of California, San Francisco (UCSF)
MD, 05/2014 - Medicine, Harvard Medical School (HMS)
BSE, 06/2009 - Mechanical Engineering, Massachusetts Institute of Technology (MIT)

Publications