Projects
Online Throughput SchedulingJul 2025 - Present
Topics: Online Algorithms, Competitive Analysis
This individual research investigates online throughput scheduling problem under various preemption models. Currently exploring the results for randomized algorithms for the preemption-revoke model. Additionally, I consider the discrete-time perspective, where all the parameters of jobs are integers and the scheduler makes decisions at discrete time steps.
Supervised by Professor Allan Borodin at the University of Toronto.
A. Borodin, C. He, N. Mottu. arXiv preprint (2026). arXiv: 2607.16163.
C. He. arXiv preprint (2025). arXiv:2510.15318.
Poster presented at the CSSU Undergraduate Research Conference, University of Toronto (2026). [View Poster]
Nonogram Puzzle Difficulty Analysis Sep 2025 - Aug 2026
Topics: Human-Perceived Difficulty, SAT Solvers
This research investigates how computational measures of difficulty align with human perceptions in Nonogram puzzles. We formulate Nonograms as Boolean satisfiability (SAT) problems and analyze solver-derived metrics such as decisions, propagations, and conflicts. Using these metrics, we generate and select puzzles across a range of computational difficulty levels.
To evaluate human difficulty, we conduct a web-based human-subject study measuring solving time, actions, hints, and subjective difficulty ratings. By comparing solver-based metrics with human performance, this work aims to identify computational indicators that better reflect human puzzle difficulty and support the generation of human-aligned Nonogram puzzles.
Co-supervised by Professor Alice Gao and Professor Jonathan Calver at the University of Toronto.
C. He, Y. Ju., A. Gao, J. Calver. arXiv preprint (2026). arXiv: 2608.23300.
Poster presented at the CSSU Undergraduate Research Conference, University of Toronto (2026). [View Poster]
Designing and Evaluating AI Agents for Othello Jan 2025 - Aug 2025
Topics: Artificial Intelligence, Game AI, Search Algorithms
I developed a modular Othello (Reversi) engine and a suite of game-playing agents, beginning with minimax search and alpha-beta pruning using parity, mobility, stability, and corner heuristics. I then extended the project with Monte Carlo Tree Search agents, comparing rollout policies, expansion strategies, and exploration constants through large-scale performance evaluations.
Supervised by Professor Alice Gao at the University of Toronto.
Poster presented at the Undergraduate Summer Research Showcase, University of Toronto (2025). [View Poster]