FrontierCS: Evolving Challenges for Evolving Intelligence
Published in ICML 2026, 2026
Open-ended, verifiable computer science challenges for evaluating frontier language models.
Adapted and refined an existing LLM-assisted research problem generation pipeline for theoretical computer science, with a focus on online algorithms. Designed domain-specific criteria for problem formulation and evaluation.
Published in ICML 2026, 2026
Open-ended, verifiable computer science challenges for evaluating frontier language models.
Published in SODA 2026, 2026
Robust flow time scheduling.
Published in WINE 2025, 2025
A dynamic-locking approach that improves on LPT for online makespan minimization with any fixed number of identical machines.
Published in ICALP 2025, 2025
Optimal competitive ratios for online p-mean welfare maximization across the full range of p.
Manuscript, 2026
Robust flow-time scheduling in the related-machines setting.
arXiv preprint, 2026
Polylog-round distributed approximation algorithms for load balancing on unrelated machines in the CONGEST model.