Welcome to my website! I am a fourth-year Ph.D. candidate in Computer Science at the University of Southern California, advised by Prof. Bistra Dilkina. I am affiliated with the USC Center for Artificial Intelligence in Society (CAIS) and the Artificial Intelligence Institute for Advances in Optimization (AI4OPT). During my studies, I spent time at Microsoft Research and the Pacific Northwest National Laboratory as a Ph.D. intern. Before joining USC, I received my bachelor’s and master’s degrees from the University of Toronto.
My research interests lie in machine learning, mathematical optimization, and data-driven decision-making. I develop scalable, efficient algorithms that exploit the structure of the problem and patterns in historical solution data, with applications to large-scale, real-world decision-making.
Availability
I am looking for internship positions for Spring/Summer 2027.
@article{huang2026acots,title={Machine learning-guided real-time AC optimal transmission switching},author={Huang, Weimin and Yang, Weiwei and Dilkina, Bistra and Mellou, Konstantina and Menache, Ishai and Molinaro, Marco and White, Chris and Zhang, Baosen},journal={arXiv preprint arXiv:2610.38180},year={2026},doi={10.48550/arXiv.2610.38180},}
SoCS
ML-Guided Primal Heuristics for Mixed Binary Quadratic Programs
Weimin Huang, Natalie M. Isenberg, Ján Drgoňa, Draguna L. Vrabie, and Bistra Dilkina
In Proceedings of the International Symposium on Combinatorial Search, 2026
Presented at the NeurIPS 2025 Workshop on Differentiable Learning of Combinatorial Algorithms
@inproceedings{huang2026mlmbqp,title={ML-Guided Primal Heuristics for Mixed Binary Quadratic Programs},author={Huang, Weimin and Isenberg, Natalie M. and Drgo{\v{n}}a, J{\'a}n and Vrabie, Draguna L. and Dilkina, Bistra},booktitle={Proceedings of the International Symposium on Combinatorial Search},volume={19},number={1},pages={74--83},year={2026},doi={10.1609/socs.v19i1.43075},note={Presented at the NeurIPS 2025 Workshop on Differentiable Learning of Combinatorial Algorithms}}
@article{huang2026wildfire,title={Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk},author={Huang, Weimin and Piansky, Ryan and Dilkina, Bistra and Molzahn, Daniel K.},journal={Electric Power Systems Research},volume={262},pages={113687},year={2027},note={Presented at the Power Systems Computation Conference (PSCC 2026)},doi={10.1016/j.epsr.2026.113687},}
arXiv
Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints
Junyang Cai, Weimin Huang, Brendan Long, Matthew Cleaveland, Jyotirmoy V. Deshmukh, Lars Lindemann, and Bistra Dilkina
@article{cai2025motionplanning,title={Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints},author={Cai, Junyang and Huang, Weimin and Long, Brendan and Cleaveland, Matthew and Deshmukh, Jyotirmoy V. and Lindemann, Lars and Dilkina, Bistra},journal={arXiv preprint arXiv:2508.07515},year={2025},doi={10.48550/arXiv.2508.07515},}
SoCS
Efficient Primal Heuristics for Mixed Binary Quadratic Programs Using Suboptimal Rounding Guidance
Weimin Huang, Natalie M. Isenberg, Ján Drgoňa, Draguna L. Vrabie, and Bistra Dilkina
In Proceedings of the International Symposium on Combinatorial Search, 2025
@inproceedings{huang2025mbqp,title={Efficient Primal Heuristics for Mixed Binary Quadratic Programs Using Suboptimal Rounding Guidance},author={Huang, Weimin and Isenberg, Natalie M. and Drgo{\v{n}}a, J{\'a}n and Vrabie, Draguna L. and Dilkina, Bistra},booktitle={Proceedings of the International Symposium on Combinatorial Search},volume={18},number={1},pages={74--82},year={2025},doi={10.1609/socs.v18i1.35978},}
arXiv
Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP Methods
Weimin Huang, Taoan Huang, Aaron M. Ferber, and Bistra Dilkina
@article{huang2024dmiplib,title={Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP Methods},author={Huang, Weimin and Huang, Taoan and Ferber, Aaron M. and Dilkina, Bistra},journal={arXiv preprint arXiv:2406.06954},year={2024},doi={10.48550/arXiv.2406.06954},}
AAAI
Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto
Weimin Huang and Elias B. Khalil
In Proceedings of the AAAI Conference on Artificial Intelligence, 2023
@inproceedings{huang2023walkability,title={Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto},author={Huang, Weimin and Khalil, Elias B.},booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},volume={37},number={12},pages={14249--14258},year={2023},doi={10.1609/aaai.v37i12.26667},}
ECCV
On Transferability of Histological Tissue Labels in Computational Pathology
Mahdi S. Hosseini, Lyndon Chan, Weimin Huang, Yichen Wang, Danial Hasan, Corwyn Rowsell, Savvas Damaskinos, and Konstantinos N. Plataniotis
@inproceedings{hosseini2020transferability,title={On Transferability of Histological Tissue Labels in Computational Pathology},author={Hosseini, Mahdi S. and Chan, Lyndon and Huang, Weimin and Wang, Yichen and Hasan, Danial and Rowsell, Corwyn and Damaskinos, Savvas and Plataniotis, Konstantinos N.},booktitle={Computer Vision -- ECCV 2020},series={Lecture Notes in Computer Science},pages={453--469},year={2020},publisher={Springer International Publishing},doi={10.1007/978-3-030-58526-6_27},}
Microsoft Research. 
Pacific Northwest National Laboratory. 
