Akang Wang

Operations Research

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Hello, I’m Akang Wang. I’m working as a Research Scientist at Shenzhen Research Institute of Big Data (SRIBD). I received my PhD in Process Systems Engineering from Carnegie Mellon University in 2020. My current research focuses on integer programming, learning to optimize, and grid optimization. My research is supported by National Natural Science Foundation of China, Guangdong Basic and Applied Basic Research Foundation, Shenzhen Science and Technology Program, and National Key R&D Program of China. I have published journal/conference papers in EJOR, ICLR, ICML, NeurIPS, etc. I won the first place in the primal track of NeurIPS 2021 ML2CO competition and the second place in the 2022 RAS Problem Solving Competition of INFORMS. Besides, I serve as reviewers for NeurIPS, ICLR, MPC, etc.

In this website, you can know more about my research and experience. Also, please feel free to check out my Google Scholar and LinkedIn.

news

Oct 23, 2024 Our paper entitled “A Novel Mixed-Integer Linear Programming Formulation for Continuous-Time Inventory Routing” is accepted by Computers & Operations Research.
Sep 27, 2024 Our papers entitled “IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs” and “SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization” are accepted by NeurIPS 2024.
May 01, 2024 Our paper entitled “PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming” is accepted by ICML 2024.
Apr 23, 2024 Our paper entitled “An Approximate-and-Optimize Method for Security-Constrained AC Optimal Power Flow” is accepted by LION 2024.
Apr 19, 2024 Our paper entitled “A Q-learning-based Multi-timescale Resilience Enhancement Approach for Power Grids with High Renewables” is accepted by ICPST 2024.
Apr 02, 2024 Our paper entitled “Routing and scheduling of platform supply vessels in offshore oil and gas logistics” is accepted by Computers & Operations Research.
Dec 10, 2023 Happy to give a talk entitled “Solving Large-Scale Optimization Problems via Learning-Based Methods” at YSSEC 2023.
Dec 05, 2023 My project “Solving Stochastic Mixed-Integer Programs via Enhanced Benders Decomposition Methods” is funded by Guangdong Basic and Applied Basic Research Foundation.

latest posts

Apr 19, 2023 Mixed-Integer Linear Programming
Jan 01, 2023 Mathematical Programming Computation Seminar Series
Jul 20, 2019 Operations Research