High-Performance Data, Signal and Network Optimization Group

Contact Information

6-109 Keller Hall
University of Minnesota - Twin Cities
Minneapolis, MN 55455
TEL: (612)-625-3505
Email: mhong at umn.edu

Research Interests

Our research focus on designing and analyzing large-scale optimization methods for problems arise in various domains such as data science, machine learning/AI, signal processing and networking.

Below is a list of (more or less) theoretical topics that we have worked on.

  • Design and Analysis for first-order/zeroth-order, stochastic, convex and nonconvex algorithms

  • Design and Analysis for Momentum-Based Methods

  • Distributed convex and nonconvex optimization

  • Bi-level, Min-Max optimization problems

  • Analysis of equilibrium solutions for noncooperative games

Our theoretical works are greatly empowered by their applications in various engineering fields.

  • Alignment for Large Language Models, and Diffusion Models

  • Robust (Adversarial) Machine Learning

  • Inverse Reinforcement Learning, and Structural Estimation Problems

  • Differential Privacy

  • High-dimensional machine learning

  • Distributed decision making in multi-agent heterogeneous networks

Group Photos


iangyi Graduation, May 2022


Xiangyi Graduation Dinner, May 2022


Group Hiking, Oct. 2022


Group Escape Room, Dec. 2022


Group Kayak, Sept 2023


Xinwei Graduation Dinner, Nov. 2023


Xinwei Defense, Nov. 2023