Bio
I received my B.S. & M.S. in Mathematics from Beihang University, Beijing, in 2007 and 2009, respectively, and Ph.D. degree from the Industrial and Systems Engineering Department, Lehigh University, Bethlehem, PA, USA in 2015. I was with ExxonMobil Corporate Strategic Research Lab in 2012, Mitsubishi Electric Research Lab in 2014, and GroupM R&D in 2015. Since 2016, I was a tenure-track assistant professor in the School of Information Science and Technology at ShanghaiTech University, and promoted to associate professor in 2023.
Research Interests
My research revolves around the area of nonlinear optimization as well as its applications in various disciplines, such as operations research, computer science, and statistics. The majority of my work involves designing algorithms, analyzing convergence, and developing software. I am currently working on the following topics.
- Stochastic nonlinear optimization algorithms
- Sparse regularization techniques in machine learning
- Low-rank matrix completion
- Nonlinear optimization algorithms for potentially infeasible problems
Papers under review
Kexin Li, Luwei Bai, Xiao Wang, Hao Wang*, “ Anderson Acceleration in Nonsmooth Problems Local Convergence via Active Manifold Identification”, submitted to SIAM Journal on Optimization, under first review.
Hongying Liu, Hao Wang∗, Haoran Chu, Yibo Wu, “ Towards Convexity in Anomaly Detection: a New Formulation of SSLM with Unique Optimal Solutions”, submitted to Journal of Machine Learning Research, under first review.
Luwei Bai, Yaohua Hu, Hao Wang*, Xiaoqi Yang, “ Avoiding Strict Saddle Points of Nonconvex Regularized Problems”, submitted to SIAM Journal on Optimization, under first review.
Xiangyu Yang, Hao Wang*, Yichen Zhu, Xiao Wang, “ Minimization Over the Nonconvex Sparsity Constraint Using A Hybrid First-order method”, submitted to Journal of Scientific Computing, under second review.
Publications
Published Journal Papers
- Qiankun Shi, Xiao Wang*, Hao Wang, “ A momentum-based linearized augmented Lagrangian method for nonconvex constrained stochastic optimization ”, accepted by Mathematical Operations Research, 2024.
- Wengqing Ouyang,Yuncheng Liu,TingKei Pong,Hao Wang, “ Kurdyka-Lojasiewicz Exponent via Hadamard Parameterization”, accepted by SIAM Journal on Optimization, 2024.
- Hao Wang, Ye Wang, Xiangyu Yang, “ Iteratively Reweighted Nuclear Norm Methods for Low-Rank Minimization with Rank Identification”, accepted by Journal of Machine Learning Research, 2024.
- Hao Wang*, Yining Gao, Jiashan Wang and Hongying Liu, “ Constrained Optimization Involving Nonconvex Norms: Optimality Conditions, Algorithm and Convergence”, Pacific Journal of Optimization, 2023.
- Hao Wang∗, Hao Zeng, Jiashan Wang, “Convergence Rate Analysis of Proximal Iteratively Reweighted l1 Methods for lp Regularization Problems”, Optimization Letters, vo. 17, no. 2, pp. 413-435, January, 2023.
- Xiangyu Yang, Hao Wang∗, Jiashan Wang, “Towards an efficient approach for the nonconvex lp ball projection: algorithm and analysis”, Journal of Machine Learning Research, no. 101, pp. 1-31, April, 2022.
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Hao Wang∗, Hao Zeng, Jiashan Wang, “An Extrapolated Iteratively Reweighted l1 Method with Complexity Analysis," Computational Optimization and Applications, October, 2022.
- Yuyan Zhou, Yang Liu∗, Ming Li, Qingqing Wu, Hao Wang. “Joint Sensor Selection, Beamforming and Phase Control in Reconfigurable Intelligent Surface Aided IoT Networks”, IEEE Wireless Communications Letters, vol. 11, no. 2, pp. 401-405, February, 2022.
- Hao Wang∗, Fan Zhang, Yaohua Hu, Yuanming Shi. “Nonconvex and Nonsmooth Sparse Optimization via Adaptively Iterative Reweighted Methods”, vol. 81, no. 3, pp. 717-748, October, 2021, Journal of Global Optimization.
- Hejie Wei, Zhihai Qu, Xuyang Wu, Hao Wang, Jie Lu, “Decentralized Approximate Newton Methods for In-Network Optimization," IEEE Transactions on Control of Network Systems, vol. 8, no. 3, pp. 1489-1500, Semptember, 2021.
- Xiangyu Yang, Hao Wang∗, Yuanming Shi, Jun Lin, “A Proximal Iteratively Reweighted Approach for Efficient Network Sparsification,” IEEE Transactions on Computers, vol. 71, no. 1, pp. 185-196, April, 2022.
- Hao Wang∗, Hao Zeng, Jiashan Wang, Qiong Wu, “Relating lp regularization and reweighted l1 regularization,” Optimization Letters, vol. 15, no. 8, pp. 2639-2660, January, 2021.
- Hongying Liu, Hao Wang∗, Mengmeng Song. “Projections onto the Intersection of l1 and l2 balls or spheres,” Journal of Optimization Theory and Applications, vol. 187, pp. 520-534, October, 2020.
- James V. Burke, Frank E. Curtis, Hao Wang∗, Jiashan Wang. “Inexact Sequential Quadratic Optimization With Penalty Parameter Updates Within The QP Solver”, SIAM Journal on Optimization, vol. 30, no. 3, 2020.
- Xiangyu Yang, Sheng Hua, Yuanming Shi, Hao Wang, Jun Zhang, B. Letaief, Khaled, “Sparse Optimization for Green Edge AI Inference,” Journal of Communications and Information Networks, vol. 5, no. 1, 2020.
- Zhihua Zhao, Hao Wang∗, Xiangyu Yang, Fengmin Xu, “CVaR-Cardinality Enhanced Indexation Optimization with Tunable Short-selling Constraints”, Applied Economics Letters, March, 2020.
- Hao Wang∗, Fan Zhang, Jiashan Wang, Yuyang Rong. “An Inexact First-Order Method for Constrained Nonlinear Optimization”, Optimization Methods and Software, pp. 1-34, January, 2020.
- Fan Zhang, Hao Wang∗, Jiashan Wang, Kai Yan, “Inexact Primal-Dual Gradient Projection Methods for Nonlinear Optimization on Convex Set”, Optimization, pp. 1-27, December, 2019.
- Yang Liu, Jing Li, Hao Wang. “Robust Beamforming in Wireless Sensor Networks”, IEEE Transactions on Communications, vol. 67, no. 6, pp. 4450-4463, June, 2019.
- Qiong Wu, Fan Zhang, Hao Wang∗, Jun Lin, Yang Liu. “Parameter-free lp-Box Decoding of LDPC Codes”, IEEE Communications Letters, vol. 22, no. 7, pp. 1318-1321, July, 2018.
- James V. Burke, Frank E. Curtis, Hao Wang∗, J. Wang. “Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets”, SIAM Journal on Optimization, vol. 25, no. 1,
pp. 261-294, 2015.
- James V. Burke, Frank E. Curtis, Hao Wang∗. “A Sequential Quadratic Optimization Algorithm with Fast Infeasibility Detection”, SIAM Journal on Optimization, vol. 24, no. 2, pp. 839-872, 2014.
- Hao Wang∗, Hongying Liu, Yong Xia. “Two-point Step Size Iterative Soft-thresholding Method for Sparse Reconstruction”, International Journal of Computer Mathematics, vol. 88, no. 12, pp. 2527-2537, April, 2010.
- Hao Wang∗, Hongying Liu, Yong Xia. “Two-step Version of the Fixed Point Continuation Method for Sparse Reconstruction”, Frontiers of Mathematics in China, vol. 5, no. 3, pp. 575-588, May, 2010.
Published Conference Papers
- Yanjie Chen, Likun Cai, Wei Cheng, Hao Wang, “ Super-Resolution Coding Defense against Adversarial Examples ,” ICMR 2020: Proceedings of the 2020 International Conference on Multimedia Retrieval. June 2020 pp.189–197.
- S. Hua, X. Yang, K. Yang, G. Yin, Y. Shi and H. Wang, “Deep Learning Tasks Processing in Fog-RAN,” 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, HI, USA, 2019, pp. 1-5.
- T. Jiang, X. Yang, Y. Shi and H. Wang, “ Layer-wise Deep Neural Network Pruning via Iteratively Reweighted Optimization,” ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, 2019, pp. 5606-5610.
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Jie Lu, Xuyang Wu, Hejie Wei, Hao Wang, “Distributed Second-Order Methods for Convex Optimization Over Networks,” the proceedings of the 15th International Conference on Control, Automation, Robotics and Vision, (ICARCV), Singapore, 2018.
- Fan Zhang, Qiong Wu, Hao Wang, Yuanming Shi. “Topological interference alignment via generalized low-rank optimization with sequential convex approximations,” in Proc. IEEE Int. Workshop Signal Process. Adv. Wireless Commun. (SPAWC), Kalamata, Greece, Jun. 2018.
- Fan Zhang, Qiong Wu, Hao Wang, Yuanming Shi. “lp-Box Optimization for Green Cloud- RAN via Network Adaptation," in Pro. IEEE Veh. Technol. Conf. (VTC), Chicago, USA, Aug. 2018.
- Q. Wu, F. Zhang, H. Wang and Y. Shi, “ Generalized Low-Rank Matrix Completion via Nonconvex Schatten p-Norm Minimization,” 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), Chicago, IL, USA, 2018, pp. 1-5.
Ph.D. Dissertation
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"Infeasibility Detection and Matrix-free Methods for Large-Scale Nonlinear Optimization," Ph.D. Dissertation, Lehigh University, May 2015.
Research Funding
- "High performance algorithms for large-scale nonconvex regularized machine learning,'' Natural Science Foundation of Shanghai, No. 21ZR1442800, budget 200,000 CNY, effective from July 2021 to June 2024, PI.
- "Cubic regularization algorithms for large-scale machine learning problems,'' the Young Scientists Fund of the National Natural
Science Foundation of China, No. 12001367, budget 240,000 CNY, effective from July 2020 to June 2023, PI.
- "Model Reduction Based Tensor Recovery Methods for Partial Differential Equations with High-Dimensional Random Inputs,'' NSFC, No.12071291, budget 510,000 CNY, effective from January 2021 to December 2024, co-PI with Prof. Qifeng Liao.
- "Data Driven Physics-Informed Uncertainty Quantification for Atmospheric Aerosols,'' Shanghai 2020 Scientific and Technological Innovation Program, No.20JC1414300, 500,000 CNY, effective from October 2020 to
September 2023, co-PI with Prof. Qifeng Liao.
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Shanghai Eastern Youth Scholar, 2017, Shanghai Municipal Education Commission.
Students
Former PhD Students
Graduation: 2022
- Xiangyu Yang (杨翔宇): Current Position: 河南大学数学学院 讲师 (Math Department, Henan University). 本科院校：郑州大学.
Graduation: 2021
- Fan Zhang (张帆): Current Position: 宁德时代. 本科院校：福州大学.
Former Masters Students
Graduation: 2019
- Qiong Wu (吴琼，MS): Excellent Graduate Student Award (2019). Current Position: 阿里菜鸟 (Alibaba Group). Cainiao-CTO-Department of AI-Warehouse Intelligence & VRP & Optimization Algorithm Engineering-fulfillment & globalization algorithm. 本科院校：浙江工商大学.
Graduation: 2020
- Yanjie Chen (陈彦洁，MS): Current Position: 字节跳动 (Bytedance-Speech), algorithm Engineer, Audio & Music Intelliegence (SAMI). 本科院校：北京航空航天大学.
Graduation: 2021
- Xin Deng (邓鑫，MS): Current Position: 阿里菜鸟 (Alibaba Group)-> 蚂蚁金服（Ant Group）.
Algorithm Engineering-fulfillment & globalization algorithm. 本科院校：哈尔滨工业大学.
- Wei Jiang (蒋微，MS): Current Position: 荣数信息 (银联数据). 本科院校：大连理工大学.
Graduation: 2022
- Hao Zeng (曾昊). Current Position: 阿里菜鸟 (Alibaba Group)-> 墨芯（Moffett AI）. 本科院校：上海科技大学.
- Yining Gao (高亦宁). Current Position: 中国银行保险监督管理委员会嘉兴监管分局 (China bank and insurance regulatory commission (Jiaxing, Zhejiang). 本科院校：上海科技大学.
- Song Mao (毛松). Current Position: Shanghai AI Lab. 本科院校：北京理工大学.
Graduation: 2023
- Ye Wang (王野). Current Position: 上海思朗科技有限公司（Smart Logic）软件生态部，算法工程师. 本科院校：河南大学.
- Qiankun Shi (石乾坤). Current Position: 中山大学，博士在读. 本科院校：四川大学.
- Tiange Li (李天戈). Current Position: 北京玻色量子科技有限公司，算法工程师. 本科院校：云南大学.
Graduation: 2024
- Luwei Bai (白璐伟). Current Position: PhD student at Arizona State University. 本科院校：中南大学.
- Kexin Li (李可鑫). Current Position: visiting intern at Pengcheng Lab. 本科院校：福州大学.
Current Masters Students
- Kexin Li (李可鑫) ，本科院校：福州大学.
- Luwei Bai (白璐伟) ，本科院校：中南大学.
- Chuanqi Ma (马传琪) ，本科院校：安徽大学.
- Shiji Zuo (左世纪) ，本科院校：上海科技大学.
- Yichen Zhu (朱亦辰)，本科院校：上海科技大学.
- Haoran Chu (褚浩然) ，本科院校：上海科技大学.
- Aike Yang (杨艾可) ，本科院校：上海大学.
