AI Applications
I'm building tools to track fast-moving biotech, starting with GLP-1 clinical trials at glp1.bio1up.com. Read more about why I'm building this.
Most recently, in my career at Harvard Medical School, I specialized in applying machine learning and large language models to analyze educational data, with a particular focus on understanding student learning patterns in online environments. My research combined quantitative analysis of structured learning data with AI-powered analysis of unstructured content like student comments, video transcripts, audio, images, and quiz question text.
I also founded and led HMX, an online learning product from Harvard Medical School. I built an interdisciplinary team, developed the product vision, and led the creation of an online learning platform and a range of unique, interactive online courses, from immunology to genetics to AI in medicine, with an emphasis on active learning and applying learning science to help people optimize their experience. I also have a strong technical background (originally computer science from MIT).
Using large language models to analyze thousands of student feedback comments in online learning environments
Learn more →Updating our understanding of how people engage with educational videos based on factors like length, type, and course context like assessment questions
Learn more →Creating dynamic visualizations of educational data to find temporal patterns
Learn more →Modeling drug diffusion with partial differential equations to enable computer control of drug delivery via intravenous infusion
Learn more →I’m excited to announce the launch of my new biotech project: glp1.bio1up.com, a site dedicated to tracking GLP-1 clinical trials. I wanted to share some thoughts on what inspired this endeavor.
I recently launched an open-access, interactive online textbook on respiratory physiology: Respiratory Physiology: A Clinical Approach. This post outlines some of the background and development process behind this project.
When you write a paper, so much gets left on the cutting room floor. There’s a wealth of insights, backstory, and reasoning behind the decisions that shape a research project—things that don’t always make it into the final version but might still be valuable to others working in the space....