Hanqing Yang

I am a Ph.D. student in Electrical and Computer Engineering at Carnegie Mellon University, advised by Prof. Carlee Joe-Wong in the LIONS research group.

I study collaboration among intelligent decision-making entities: what defines collaboration, how to represent it, and what becomes computationally possible once collaboration itself is represented. Rather than assuming a known organizational structure, I examine how collaboration unfolds as agents interact, tasks are transformed, interdependencies emerge, and individual contributions become collectively consequential. My current work focuses on these questions through LLM-based multi-agent systems.

Before CMU, I worked on machine learning for healthcare in CPSL at Washington University in St. Louis, advised by Prof. Chenyang Lu.

Education

Ph.D. Student: Electrical and Computer Engineering, CMU (2025–Present)
M.S.: Artificial Intelligence Engineering, Electrical and Computer Engineering, CMU (2024)
B.S.: Computer Engineering and Computer Science, WashU (2023)

Research Interests

Definition: What constitutes collaboration among intelligent entities, and which primitives distinguish it from mere group behavior?
Representation: What representational structure can capture emergent collaboration across tasks, teams, and scales, and under what assumptions?
Computation: Once collaboration is represented, what can be explained, evaluated, guaranteed, repaired, or optimized, and at what computational cost?

Teaching Experience

I really enjoy working with students. I’ve been a TA for a mix of undergrad and grad courses in systems and machine learning.

Carnegie Mellon University
- 18-613: Foundations of Computer Systems — Spring 2025
- 18-661: Introduction to Machine Learning — Spring 2024 and Spring 2026
Washington University in St. Louis
- CSE 422: Operating Systems and Organization — Fall 2022 and Spring 2023
- CSE 361: Introduction to System Software — Spring 2022
- CSE 132: Introduction to Computer Engineering — Spring 2021