Hanqing Yang

Hanqing Yang

PhD Student in ECE at CMU

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. That work connected patient-level prediction to decisions over scarce clinical resources.

Education

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

Research Interests

My work seeks to make collaboration itself a first-class computational object: something that can be defined through the relations and dynamics that constitute it, represented without assuming a fixed organization, and computed over to explain, evaluate, and improve collective outcomes. This problem develops along three connected directions:

  • Definition: identifying the relational or structural objects—and the emergent dynamics—that distinguish collaboration from parallel activity.
  • Representation: making communication, events, task-induced dependencies, obligations, and grounded agent traces explicit without prescribing an organization.
  • Computation: using collaborative structure for evaluation, guarantees, failure attribution, repair, scalability, and optimization.

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
    • 18-661: Introduction to Machine Learning
  • Washington University in St. Louis
    • CSE 422: Operating Systems and Organization
    • CSE 361: Introduction to System Software
    • CSE 132: Introduction to Computer Engineering