Biography

Tony Shi is an Assistant Professor of Industrial and Systems Engineering, and a joint Assistant Professor of Mechanical and Aerospace Engineering at the University of Tennessee, Knoxville. He is also an Affiliated Faculty of Machine Tool Research Center and Institute of Advanced Materials and Manufacturing. He is the director of Manufacturing Intelligent Dynamics Laboratory.

Prior to joining UT Knoxville in 2022, he was an Assistant Professor of Engineering Management at UT Space Institute. He was a Postdoctoral Research Associate in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison from 2017 to 2019. He received his Ph.D. degree in Management Science and Engineering from Peking University in 2017.

His research interests are manufacturing processes and systems innovations by establishing the mathematical relationships of machines, tools, processes and materials, with a focus on solid-state additive manufacturing, machining, hybrid manufacturing and smart machines, to enable next-generation design and manufacturing. His work has made fundamental contributions to advance machine tool vibration theory from machining to additive friction stir deposition (AFSD).

For machining, he has established an accurate and scalable framework of bifurcation and stability analysis, ChatterStabilizer, that advances the well-renowned stability map generation methods developed for chatter suppression over the past sixty years. For AFSD, he is pioneering the AFSD machine tool vibration theory and extending it to materials behaviors to achieve machine-tool-process-materials convergence.

His research vision is to establish a systems approach of machine-tool-process-materials convergence, to make manufacturing machines acquire the capabilities of thinking about manufacturability, stability and materials elements, including geometry, surface, structure, property and performance. His work aims to enable innovations in additive, subtractive and hybrid manufacturing to address the supply chain challenges for a sustainable future, with broader applications in aerospace, defense, automotive and energy sectors.

Shi’s group has the capabilities to design and build open-source and low-cost CNC machines to perform fundamental research in support of this goal, while taking care to consider its integration with practical implementation, engineering education and workforce development. Through this combined agenda, students at many levels are trained to acquire physics-based modeling capabilities coupled with fundamental experimental techniques and data analytics skills, including physics-based machine learning.

Shi has published 37 technical articles and given over 20 technical presentations, including the keynote talk at the 2025 Mid-Year Industry Advisory Board Meeting of NSF IUCRC Manufacturing & Materials Jointing Innovation Center. He is a core faculty member of NSF Engineering Research Center HAMMER – Hybrid Autonomous Manufacturing, Moving from Evolution to Revolution. Dr. Shi’s research has been supported by NSF, DoE-Oak Ridge National Laboratory, DoD-Southeastern Advanced Machine Tools Network and AI Tennessee Initiative.

Education

• PhD, Management Science and Engineering, Peking University, 2017
• BS, Pure and Applied Mathematics, China University of Geosciences (Beijing), 2011

Courses Taught

• Manufacturing Systems Modeling and Analysis
• Statistical Methods in Industrial Engineering
• Design of Experiments for Engineering Managers
• Statistical Learning for Complex Systems

Awards and Honors

• Second Place, Syngenta Crop Challenge in Analytics, INFORMS, 2017.
• Outstanding Ph.D. Dissertation Award, Peking University, 2017.
• Chancellor’s Scholarship, Peking University, 2014 – 2016.
• Outstanding Graduate Award, Government of Beijing, 2017.
• National Scholarship for Graduate, Government of China, 2016.
• Outstanding Undergraduate Award, Government of Beijing, 2011.
• National Scholarship for Undergraduate, Government of China, 2009.

Professional Service

• Associate Editor, Operations Research Forum, 2023-present
• Associate Editor, Energy Systems, 2023-present
• Associate Editor, IEEE International Conference on Automation Science and Engineering, 2023-present
• DoE, Office of Science, Panelist (Advanced Scientific Computing Research), 2024
• NSF, Panelist (SBIR, Advanced Manufacturing), 2021, 2024, 2025
• Faculty Judge, UTK Perfect Pitch Competition, NSF ERC-HAMMER, Knoxville, TN, September 2025.
• Faculty Representative of NSF ERC-HAMMER (1 of 10), 2024 NSF Engineering Research Center Biennial Meeting, Arlington, VA, September 2024.
• Faculty Judge, UTK Perfect Pitch Competition, NSF ERC-HAMMER, Knoxville, TN, July 2024.
• Panelist, Model-informed AI Research Panel, AI Tennessee Initiative Seed Funds Workshop, Knoxville, TN, November 2023.
• Invited Panel Attendee, NSF Director Sethuraman Panchanathan Visit / Panel on “A Transdisciplinary Focus on Artificial Intelligence”, Knoxville, TN, June 2023.
• Invited Attendee and Panelist, Artificial Intelligence for Robust Engineering & Science (AIRES 4) Workshop, Oak Ridge National Laboratory, TN, April 2023.
• Invited Attendee and Panelist, AI Tennessee Initiative Strategic Visioning Workshop, Knoxville, TN, April 2023.
• Session Co-Chair, NSF ERC-HAMMER Session, 52nd North American Manufacturing Research Conference (NAMRC 52), Knoxville, TN, June 2024.
• Program Committee Member, World Congress on Global Optimization (WCGO 2023), Athens, Greece, July 2023.
• Session Chair, Special Session on Recent Advances in Theory and Applications of Simulation-Based Optimization, 2022.
• IEEE 18th International Conference on Automation Science and Engineering (CASE), Mexico City, Mexico, August 2022.
• Program Committee Member, World Congress on Global Optimization (WCGO 2021), Athens, Greece, July 2021.
• Organizer, Workshop on Data Analytical Approach for Large-Scale Optimization, 13th IEEE International Conference on Automation Science and Engineering, Xi’an, China, August 2017.

Research Publications

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