Xiang Li

Xiang Li

Ph.D. Student in Mechanical Engineering

The University of Texas at Austin

I study decision-making under competition, with a focus on mechanism design, information structure, and team-based design behavior. My work combines experimental methods, game-theoretic modeling, and optimization-based thinking to better understand how individual efficiency translates — or fails to translate — into collective outcomes.

Austin, Texas SiDi Lab, UT Austin

About

I am a Ph.D. student in the Mechanical Engineering area at The University of Texas at Austin, with research interests spanning decision analysis, game theory, mechanism design, and team-based design under competition.

More specifically, I am interested in how information-sharing mechanisms, incentives, and strategic interaction shape both individual behavior and system-level outcomes. My recent work studies when individual efficiency aligns with collective performance, and when such alignment breaks down under different competitive structures.

Methodologically, my work combines behavioral experiments, theoretical modeling, and optimization-based analysis. I am particularly interested in building clean theoretical frameworks that can explain empirical patterns observed in competitive design environments.

Research Interests

Decision analysis, mechanism design, game theory, experimental design, team competition, information structure

Methods

Behavioral experiments, theoretical modeling, optimization, statistical analysis, oTree-based research platforms

Current Focus

Information sharing, efficiency misalignment, and strategic externalities in competitive team-based design

Research

Competitive Team-Based Design Decisions

I study how teams make design decisions under competition, and how different information-sharing mechanisms influence search behavior, resource use, and final outcomes.

Team Competition Design Decisions Information Sharing

Efficiency Misalignment

A central theme in my recent work is the potential misalignment between individual-level efficiency and system-level performance. I examine when stronger individual outcomes do — and do not — aggregate into better collective results.

Efficiency Collective Outcomes Misalignment

Mechanism Design and Information Structure

I am developing a broader research agenda around how information disclosure, strategic incentives, and institutional rules shape behavior in interactive decision systems.

Mechanism Design Game Theory Information Design

Experimental Research Platforms

I build and deploy oTree-based experimental platforms to study behavior in structured decision environments, with an emphasis on rigorous design and replicable implementation.

oTree Behavioral Experiments Research Platform

Publications

Conference Proceedings

X. Li, S. Chen, A. E. Bayrak, Z. Sha, “A Game-Theoretic Research Platform for Team-based Design Decisions under Competition”

Proceedings of the 25th International Conference on Engineering Design (ICED 25), 2025

Submitted Manuscripts

X. Li, E. Bickel, A. E. Bayrak, Z. Sha, “When Individual Efficiency Fails to Translate: Mechanism-Dependent Misalignment in Competitive Design”

Submitted to the ASME International Design Engineering Technical Conferences (IDETC), 2026

Working Papers

Ongoing theoretical modeling on information sharing, efficiency alignment, and inequality in competitive team systems

In preparation

Teaching

Teaching Assistant

Information and Analysis (06260), UT Austin McCombs School of Business

Served as a Teaching Assistant for the Fall 2024 semester, supporting coursework, student learning, and instructional delivery in an analytically oriented business course.

Contact

I am always happy to connect regarding research, academic collaboration, or related opportunities.