CV

Curriculum Vitae of Tan Hoang Cao, Associate Professor of Applied Mathematics and Statistics, SUNY Korea.

Contact Information

Name Tan Hoang Cao
Professional Title Associate Professor of Applied Mathematics and Statistics
Email tan.cao@stonybrook.edu
Phone +82-32-626-1912
Location Room B524 Academic Building, 119 Songdo Moonhwa-Ro, Incheon, Yeonsu-Gu 21985
Website https://tancao.org

Professional Summary

Associate Professor and Undergraduate Program Director in the Department of Applied Mathematics and Statistics at SUNY Korea (affiliated with Stony Brook University). Research focuses on optimization, optimal control, variational analysis, sweeping processes, differential inclusions, and reinforcement learning in nonsmooth dynamical systems.

Experience

  • 2017 - present

    Incheon, Republic of Korea

    Associate Professor & Undergraduate Program Director
    SUNY Korea
    Department of Applied Mathematics and Statistics. Affiliated with Stony Brook University.
    • Teach undergraduate courses in calculus, numerical analysis, discrete mathematics, operations research, and optimization.
    • Undergraduate Program Director: academic advising and course-registration support for AMS students.
    • Chair of the Committee on Evaluation of Faculty Work (CEFW).
    • Supervised 7 undergraduate, 2 master, and 2 Ph.D. students, plus 1 postdoctoral researcher.
  • 2016 - 2017

    Ho Chi Minh City, Vietnam

    Mathematics Lecturer
    Vietnamese-German University
    Foundation Year program — Language Department.
    • Developed and taught mathematics courses in English for the Foundation Year program.
  • 2011 - 2016

    Detroit, MI, USA

    Graduate Teaching Assistant
    Wayne State University
    • Taught MAT/STA undergraduate courses while completing the Ph.D.

Education

  • 2011 - 2016

    Detroit, MI, USA

    Ph.D.
    Wayne State University
    Applied Mathematics
    • Optimal Control of a Perturbed Sweeping Process with Applications to the Crowd Motion Model
    • Advisor: Prof. Boris Mordukhovich.
    • Karl W. and Helen L. Folley Endowed Scholarship (2015, 2016).
  • 2007 - 2009

    Orléans, France

    M.S.
    University of Orléans
    Mathematics and Applications
    • Amenable groups
    • Advisor: Prof. Indira Lara Chatterji.
  • 2004 - 2008

    Ho Chi Minh City, Vietnam

    B.S.
    Ho Chi Minh City University of Pedagogy
    Mathematics
    • Numerical method in extremal problems
    • Advisor: Prof. Dieu T. Cong.
    • University Monthly Scholarship for Excellent Students (2005–2008).

Research Grants

  • NRF 기본연구 (2020–2023) — Principal Investigator, National Research Foundation of Korea. Project: Optimal Control of the Sweeping Process and Its Applications. Total budget: 165,000,000 KRW.
  • NRF 기본연구B (2026–2030) — Application submitted; currently under review, National Research Foundation of Korea.

Honors and Awards

  • 2016
    Karl W. and Helen L. Folley Endowed Scholarship
    Wayne State University
  • 2015
    Karl W. and Helen L. Folley Endowed Scholarship
    Wayne State University
  • 2015
    Nomination for the Heberlein Excellence in Teaching Award (Graduate Students)
    Wayne State University, Department of Mathematics
  • 2015
    AMS Travel Grant Support
    Wayne State University
  • 2004
    Second Prize, Mathematics Competition of Ho Chi Minh City for High School Students
    Tran Dai Nghia High School for the Gifted
  • 2003
    Silver Medal, Southern Vietnam Mathematical Olympiad for High School Students
    Tran Dai Nghia High School for the Gifted

Interests

Optimization: Convex and nonsmooth optimization, Optimization with differential inclusions
Optimal Control: Sweeping processes, Free-time and variable-time problems, Bilevel control, Discrete approximations
Variational Analysis: Generalized differentiation, Normal cones, Subdifferentials
Differential Inclusions: Maximal monotone operators, Catching-up algorithm, Sweeping processes
Applications: Crowd motion, Marine surface vehicles, Robotics, Mean-variance portfolio optimization, Reinforcement learning

Service

  • Journal Reviewer: Journal of Optimization Theory and Applications; Applied Mathematics & Optimization; Set-Valued Analysis; Journal of Global Optimization; Optimization Letters; Applied Mathematical Modelling; Evolution Equations and Control Theory; Nonlinear Differential Equations and Applications; Numerical Algorithms; Acta Mathematica Scientia.
  • Conference organization: Co-organizer and co-chair of two invited sessions on Learning-Based Control and Sweeping Processes (I & II) at the 60th IEEE Conference on Decision and Control (CDC 2021), Austin, Texas.
  • University: Chair of the Committee on Evaluation of Faculty Work (CEFW); Undergraduate Program Director, AMS.

Selected Talks and Conferences

  • OVACT 2026 — International Workshop on Optimization, Variational Analysis and Control Theory, Hanoi, Vietnam — invited talk (Oct 2026).
  • Invited seminar: The Fastest Path: From the Brachistochrone to Optimizing Crowd Dynamics, Can Tho University, Vietnam (Dec 2025).
  • Workshop on Applied Mathematics 2025, Ton Duc Thang University (Khanh Hoa Campus), Vietnam — invited talk (Jul 2025).
  • International Conference on Control of State-Constrained Dynamical Systems, Padua, Italy (Sep 2024).
  • International Conference on Optimization and Variational Analysis with Applications, Hanoi, Vietnam (Jul 2023).
  • 60th IEEE Conference on Decision and Control (CDC 2021), Austin, Texas — co-organizer and co-chair, sessions on Learning-Based Control and Sweeping Processes I/II.
  • International School and Workshop on Control of State-Constrained Dynamical Systems, Valparaíso, Chile (Sep 2019).

Languages

Vietnamese : Native speaker
English : Professional working proficiency
French : Working proficiency

Certificates

  • Agentic AI - DeepLearning.AI (2026)
  • Applied Data Science Program - MIT Professional Education (2025)
  • Optimal Control and Reinforcement Learning - Carnegie Mellon University
  • Deep Reinforcement Learning - Hugging Face
  • AI Nanodegree / Deep RL Nanodegree - Udacity
  • Mathematics for Machine Learning, Prompt Engineering - Coursera