Jin Li

Jin Li

Machine Learning Researcher and Engineer

University of Chicago

Biography

Hey I’m Jin! Broadly, I aspire building useful, safe, and ethical AI that improves the lives of everyday people. As a person, I strive towards making myself better than I was yesterday, understand the value of tenacity, grit, and focus for achieving great things, and aim to challenge existing ideas and find new ways to think about problems. I take initiative to find problems that are important to solve and I care deeply about building things that empower my team and deliver value to the community.

Currently, I’m a machine learning researcher and engineer at PathAI, where I do everything from conducting applied research to productionizing ML algorithms to building AI powered products for consumers. Previously, I spent three and a half amazing years at the University of Chicago where I studied pure math and both theoretical and practical computer science. In my spare time, I play soccer, play the piano, read philosophy, and practice martial arts. If I get the chance, I also camp in forests and go on hikes.

Interests
  • Artificial Intelligence
  • Foundational Vision and Language Models
  • AI Safety and Ethics
Education

  • MSc in Computer Science, 2022

    University of Chicago

  • BSc in Math, 2021

    University of Chicago

  • BSc in Computer Science, 2021

    University of Chicago

Experience and Education

 
 
 
 
 
Machine Learning Engineer
PathAI
April 2022 – Present Boston

At PathAI, I work on applying AI research to improve patient outcome with AI powered pathology. I currently lead a project on building a promptable vision foundational model that can understand pathology and provide biological insights for drug development and disease diagnosis. I’ve done research and engineering on knowledge distillation, domain generalization, ML assisted annotations, self-supervised training, and foundational models.

I also help maintain and improve PathAI’s massive AI codebase that powers the business by productionizing AI research, implementing new tools used through the entire ML lifecycle, reviewing the design and implementation of novel AI algorithms by other engineers, optimizing legacy code, and pushing for best coding practices.

I also contributed to the entire lifecycle development of an AI product for predicting colon disease that is used by pathologists in clinical trials and research.

 
 
 
 
 
Machine Learning Research Assistant
Toyota Technological Institute at Chicago
August 2019 – June 2021 Chicago
At TTIC, I built AI models for protein structure prediction and published research in top journals like Nature Machine Intelligence and Bioinformatics. I also did some initial work on building foundational protein language models for drug discovery.
 
 
 
 
 
Machine Learning Research Assistant
UChicago Medicine
February 2019 – April 2021 Chicago
At UChicago Medicine, I built AI models to improve vaccine targets, predict cardiac arrests, and quantify pandemic risks. I published research in top biology journals like the Journal of the American College of Cardiology and JAMA Network Open.
 
 
 
 
 
Student
University of Chicago
October 2018 – March 2022 Chicago
I completed a BSc in Math, BSc in Computer Science, and MSc in Computer Science at UChicago in three and a half years. I spent most of that time studying pure math and both theoretical and practical computer science. UChicago’s core curriculum taught me how to discuss and debate complex ideas from fields ranging from social sciences and humanities to hard sciences. I pushed myself outside my comfort zone and took the most challenging courses, like completing the honors analysis sequence and taking graduate level machine learning courses in my first year of college. But much more importantly than all of that, I learned the value of a life long journey of pursuing intellectual growth and knowledge. “Crescat scientia; vita excolatur.”

Contact

If your mission aligns with mine, please reach out! Maybe we can make some dreams come true.