معرفی
Tong Ma is an Assistant Professor in the Department of Mechanical and Industrial Engineering at Northeastern University. He joined the university in July 2022 and specializes in research areas such as nonlinear systems and control, stochastic control and optimization, and data-driven methodologies. His work integrates machine learning and partial differential equations (PDEs) to address complex control challenges.
Education: PhD in Mechanical Engineering from the University of Connecticut (2018) and BS in Electrical Engineering and Automation from Harbin Institute of Technology (2013). Prior to his faculty role, he served as a Postdoctoral Research Associate at Pacific Northwest National Laboratory (2019–2022) and completed an internship at Mitsubishi Electric Research Laboratories (MERL, 2018).
Research focuses on advancing adaptive control strategies, Gaussian process-based stochastic predictive control, and PDE-driven systems. Recent publications emphasize methodologies for constrained tracking, uncertainty quantification, and energy grid optimization. His team actively explores applications in power systems, robotics, and advanced manufacturing.
Advising includes mentoring three PhD students: Mengxu Xie (2023), Ali Mashhadireza (2024), and Siyi Yu (2024). Research collaborations extend to labs like Automation, Control, and Intelligence, with ongoing work on predictive control frameworks and physics-informed machine learning.
Lab activities prioritize interdisciplinary projects combining control theory, AI, and energy systems. Future directions include scalable stochastic MPC algorithms and real-time adaptive systems for industrial applications.
