Research
(alphabetical authorship marked with )
Interactive demos of key ideas from my papers. Try them →Journal Papers and Preprints
- High-Probability Polynomial-Time Complexity of Restarted Primal-Dual Hybrid Gradient Method for Linear Programming Mathematics of Operations Research, 2026 journal arXiv pdf demo
- Accessible Complexity Bounds for Restarted PDHG on Linear Programs with a Unique Optimizer Mathematics of Operations Research, 2026 journal arXiv pdf code slides demo ⭐ Winner, 2025 INFORMS Optimization Society Student Paper Prize
- Computational Guarantees for Restarted PDHG for LP based on "Limiting Error Ratios" and LP Sharpness Mathematical Programming, 2026 journal arXiv pdf slides additional results ⭐ Honorable Mention, 2024 INFORMS Optimization Society Student Paper Prize
- Function-Free Optimization via Comparison Oracles Under revision arXiv pdf poster video demo animation
- Symmetry-dependence in Rounding of a Convex Body Under review arXiv pdf demo
- The Role of Level-Set Geometry on the Performance of PDHG for Conic Linear Optimization A subsequent version is under review arXiv pdf slides ⭐ Finalist, 2024 George Nicholson Student Paper Competition
- From an Interior Point to a Corner Point: Smart Crossover INFORMS Journal on Computing, 2025 journal arXiv pdf code slides
- A Practical GPU-Enhanced Matrix-Free Primal-Dual Method for Large-Scale Conic Programs Under revision arXiv pdf code
- The Impact and Insights of Hidden City Ticketing: Analysis of a Choice-Based Network Revenue Management Model Under revision for resubmission SSRN
- Using Taylor-Approximated Gradients to Improve the Frank-Wolfe Method for Empirical Risk Minimization SIAM Journal on Optimization, 2024 journal arXiv pdf slides additional results
- Low-rank Traffic Matrix Completion with Marginal Information Journal of Computational and Applied Mathematics, 2022 journal pdf
Papers Published at Conferences
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Fair Wasserstein Coresets
Preliminary version appeared in NeurIPS 2023 Workshop SyntheticData4ML (Oral Presentation)
Neural Information Processing Systems (NeurIPS 2024) proceedings arXiv pdf workshop version - FairWASP: Fast and Optimal Fair Wasserstein Pre-processing AAAI Conference on Artificial Intelligence (AAAI 2024) proceedings arXiv pdf demo
- Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion European Conference on Computer Vision (ECCV 2022) proceedings arXiv pdf code
- Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem Neural Information Processing Systems (NeurIPS 2019) proceedings arXiv pdf code slides
PhD Dissertation
- New Theory and New Practical Methods for Solving Large-Scale Linear and Conic Optimization PhD Dissertation DSpace@MIT pdf ⭐ Second Place, 2025 George B. Dantzig Dissertation Award
Technical Reports
- A Technical Note on the Implementation and Use of PDCS arXiv pdf
- On the Relation Between LP Sharpness and Limiting Error Ratio and Complexity Implications for Restarted PDHG arXiv pdf
Software
- PDCS A GPU-enhanced matrix-free primal-dual solver for large-scale conic programs, with JuMP and CVXPY interfaces. code
- Smart Crossover A Python package that finds optimal basic solutions from interior-point solutions. code
- PDLP Complexity Bound A Julia toolkit that computes the accessible iteration bounds of restarted PDHG for LP. code
- MAAIPM A MATLAB solver for exactly solving Wasserstein barycenter problems using interior-point methods. code
Patent Applications
- Method and System for Generating Fair Synthetic Representative Data via Optimal Transport U.S. Patent Application Publication No. US 2025/0181999 A1, pending, 2025 Google Patents
- Method and System for Pre-processing Data for Algorithmic Fairness via Optimal Transport U.S. Patent Application Publication No. US 2025/0173389 A1, pending, 2025 Google Patents