Andrew Bae

Andrew Bae

AI Researcher

Snorkel AI

I am a researcher at Snorkel AI. I was previously a PhD student at Carnegie Mellon University. I recieved my BS from Stony Brook University.

Outside of work, my hobbies include playing cello and powerlifting. I also used to solve Rubik’s cubes competitively.

CV

Interests
  • Machine learning
  • Optimization
  • Information science
  • Agentic AI
Education
  • PhD (Incomplete)

    Carnegie Mellon University

  • MS, Artificial Intelligence, 2026

    Carnegie Mellon University

  • BS, Applied Mathematics & Statistics, 2024

    Stony Brook University

Work Experience

 
 
 
 
 
[Snorkel AI](https://snorkel.ai/)
Research Intern
May 2026 – Present San Francisco, CA
 
 
 
 
 
[Cloudflare](https://www.cloudflare.com/)
Research Intern
Feb 2026 – May 2026 Austin, TX
 
 
 
 
 
[MIT Lincoln Laboratory](https://www.ll.mit.edu/)
Research Intern
Jun 2024 – Aug 2024 Lexington, MA
 
 
 
 
 
[Lawrence Berkeley National Laboratory](https://www.lbl.gov/)
Research Intern
May 2023 – Aug 2023 Berkeley, CA

Research Experience

 
 
 
 
 
Independent Researcher
May 2026 – Present No Affiliation
 
 
 
 
 
Independent Researcher
Nov 2025 – May 2026 Carnegie Mellon University
 
 
 
 
 
Advisor: [Prof. Sean Qian](https://www.cmu.edu/cee/people/faculty/qian.html)
Graduate Student Researcher
Aug 2024 – Oct 2025 Carnegie Mellon University
 
 
 
 
 
Advisor: [Prof. Susu Xu](http://susu-xu.com/)
Undergraduate Student Researcher
Advisor: Prof. Susu Xu
Oct 2021 – Dec 2023 Stony Brook University
 
 
 
 
 
Advisor: [Prof. Benjamin S. Hsiao](https://www.hsiaoglobal.org/)
Undergraduate Student Researcher
Jan 2021 – Sep 2021 Stony Brook University

Conference Publications

Naomi Panjaitan, Ling Jin, Caitlin Brown, Anna Spurlock, Thomas Wenzel, Alina Lazar, Qianmiao Chen, Andrew J. Bae. Large Scale Integrated Simulation of Household Vehicle Fleet Composition with Geographically Explicit Synthetic Population. The 13th IEEE International Conference on Big Data (IEEE BigData). 2025.
Paper Code Presentation
Andrew J. Bae, Susu Xu. Discovering and Understanding Algorithmic Biases in Autonomous Pedestrian Trajectory Predictions. Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (ACM SenSys). 2022.
Paper Code

Teaching Experience

Teaching Assistant:

  • 12760 - Fundamentals of Programming, Carnegie Mellon University, Spring 2025
  • AMS 341 - Linear Programming, Stony Brook University, Fall 2023
  • CSE 214 - Data Structures, Stony Brook University, Spring 2023
  • HON 101 - Honors College Freshman Seminar, Stony Brook University, Fall 2022
  • AMS 326 - Numerical Analysis, Stony Brook University, Summer 2021

Awards and Honors

Selected Awards:

Other Awards:

Honor Societies:

Contact