Welcome!
My name is Shuaicheng (Allen) Tong. I am a third-year PhD student in Machine Learning at Georgia Tech ISyE advised by Prof. Pascal Van Hentenryck. I completed my B.S. in Mathematics of Computation at University of California, Los Angeles (UCLA) with a minor in Data Science Engineering. During my undergraduate studies, I worked with Prof. Samy Wu Fung on deep learning for image recovery.
My research lies at the intersection of Machine Learning and Optimization. I develop methods for making high-quality decisions under uncertainty when solving optimization problems at scale. My interests center on:
- Optimization proxies, using machine learning to exploit problem structure and accelerate decision-making while preserving solution quality, feasibility, and interpretability.
- Combinatorial and mixed-integer optimization, designing heuristics that navigate discrete decisions efficiently and reliably, with numerical stability and feasibility guarantees under hard constraints.
- Optimization for energy systems, including voltage control and Volt/VAR optimization for operational planning.
My goal is to contribute methodologies that combine the structure of mathematical optimization with the speed and scalability of machine learning, motivated by applications in energy and sequential decision-making.
Publications
X. Li et al. (including S. Tong). SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks. NeurIPS 2026.
S. Tong and P. Van Hentenryck. Improving Stability and Economic Operation in Transmission Systems through Volt/VAR Optimization. The 60th Hawaii International Conference on System Sciences (HICSS-60).
S. Tong, M. A. Boateng, M. Tanneau, and P. Van Hentenryck. Volt/VAR Optimization in Transmission Networks with Discrete-Control Devices. International Power Systems Computation Conference (PSCC 2026).
T. Ye, S. Tong, C. Guan, B. Basciftci, and P. Van Hentenryck. Learning Optimization Proxies for Sequential Contextual Stochastic Programs: An Order Fulfillment Application. arXiv preprint.
T. Ye, S. Tong, C. Guan, B. Basciftci, and P. Van Hentenryck. Deep Learning-Driven Contextual Stochastic Optimization for Real-Time Order Fulfillment. NeurIPS 2025 Workshop MLxOR.
L. Liu, S. Tong, and L. Zhao. Training Implicit Networks for Image Deblurring using Jacobian-Free Backpropagation. SIAM Undergraduate Research Online.
Download my CV here.