Welcome :) I am currently a postdoc at Dartmouth College. I was a postdoc at the University of Utah. I received my PhD in Applied Mathematics in August 2022 from Case Western Reserve University, where I was also part of the Cleveland Clinic, advised by Peter J. Thomas (CWRU) and Jacob G. Scott (Cleveland Clinic). On this website, I highlight some selected experiences -- my full CV is available upon request!

Research  Broadly speaking, I do research in applied probability & stochastic processes and its intersections with optimization under uncertainty, statistical inference, and mathematical biology (stochastic population dynamics). Very broadly speaking, I enjoy thinking about analogies and synthesizing connections between seemingly disparate concepts.

Specifically, I am fascinated by the connections between the following three fields through adaptive dynamics, optimization, and complexity on high-dimensional random landscapes of interacting populations and networks:

• mathematical spin glasses (large networks with random interactions and conflicting combinatorial optimization constraints)  in high-dimensional probability & statistical physics (energy landscapes),

• eco-evolutionary dynamics in biological & social sciences (fitness landscapes). In particular, I am interested in high-dimensional fitness -- for example, birth and death rates instead of just net growth rates.

• Large Language Models in machine learning & AI (loss landscapes).

My overarching research program bridges multi-scales through

1. [macro --> micro] Inferring  microscopic interaction mechanisms from macroscopic data for a series of interacting populations that increase in complexity: 🟡homogeneous populations (Journal of Mathematical Biology by Huynh et al. 2023, and my first-author preprint on analysis of stochastic processes for limited data) to 🟡heterogeneous populations (Bulletin of Mathematical Biology by alphabetically-ordered Beckman, Cho, Huynh 2025) to 🟡network structures (my single-author preprint for an interacting particle system, and collaborative preprint with AMS MRC for an agent-based model). My simple but powerful nonparametric inference methods utilize properties of stochastic processes and work well for parameters as nondifferentiable, high-dimensional functions of the state variables (code available at https://github.com/lhuynhm/). Moreover, the methods emphasize the roles of stochasticity in identifiability. This is like Inverse Problems  in Uncertainty Quantification.

2. [micro --> macro] Modeling and analyzing how microscopic random interactions give rise to emergent macroscopic collective behaviors, especially phase transitions (my senior-author preprint arXiv:2505.02879, Parisi PDE and stochastic optimal control in spin glasses). This is like Forward Problems in Uncertainty Quantification.

Teaching  I have taught a variety of courses and worked effectively with students across a wide range of identities and backgrounds. I incorporated research on "How random is ChatGPT?" in my MATH 20 Probability in Summer 2024. One of my teaching evaluations that touches my heart and reflects my teaching philosophy is

“She was very knowledgeable on the course material. Something I found a little frustrating at first, but grew to very much appreciate, was that she would make us learn the material the “hard way.” Instead of calculators and basic quiz questions, we would do our work by hand, and answer conceptual-theory questions. This was more difficult than I had been used to in the past, but I believe I learned better because of it. She cared about our progress and was fun.”

Last year in February 2024, I gave a tutorial at the Joint Virtual Conference between the Mathematical Epidemiology and Mathematical Oncology Subgroups of the Society for Mathematical Biology.

Research Mentoring  It is very rewarding to see these two tangible products:

• My publication on statistics, information retrieval, and spin glass models for phase transitions in AI-human interaction networks with Jackson George, Zach Yusaf, and Stephanie Zoltick. They were funded by the Undergraduate Research Assistantships at Dartmouth (URAD) with me as their faculty advisor in 2025.

• Anna Tang's honors thesis on mathematical model of drug resistance with the role of ecological interactions in the tumor microenvironment in 2023. "I have to really thank Linh for putting up with my shenanigans and antics. She was a wonderful mentor and helped me find my way in this project."

Service & Outreach

• I have been a co-organizer of the Applied & Computational Mathematics Seminar at Dartmouth College.

• I was an elected co-chair of the Mathematical Oncology Subgroup of the Society for Mathematical Biology from 07/2023-10/2025.

• I recently co-organized an AWM Breakfast (23 participants from undergraduates to graduates to postdocs to active & retired professors discussing career stories) and was a math station leader at Dartmouth Science Day.

Invited Research Talks and Travels (selected recent)

• January 4-7, 2026: Joint Mathematics Meetings AMS Special Session on Advances in Mathematical Modeling of Biological Systems in the Era of Artificial Intelligence, Washington, D. C.

• November 2025: University of Florida, Biomathematics Seminar, Gainesville, FL

• November 2025: University of Massachusetts Amherst, Mathematics of Machine Learning Seminar, Amherst, MA

• October 2025: Tufts University, Computational and Applied Math Seminar, Medford, MA

• October 3-5, 2025: AMS Fall Southeastern Sectional Meeting Special Session on "Advances and challenges in the study of nonlinear PDEs," New Orleans, LA 

• September 2025: Mathematics for Poets and Other Artists Workshop, East Lansing, MI 🎨🖌️

• September 2025: The Ohio State University, Applied Math Seminar, Columbus, OH

• June 16-20, 2025: Hausdorff School on Statistical Mechanics of Spin Glasses, Neural Networks and Learning, Universität Bonn, Germany

• June 2-6, 2025: GUEST :) at (NSF-funded) Conference on Quantum Topology and Hyperbolic Geometry, Seashells Beach Resort, Phú Quốc, Việt Nam 🏖️🦞

• May 20-24, 2025: Mathematical Foundations of Data Science, Centre de recherches mathématiques, Montréal, Canada

• May 11-15, 2025: SIAM Conference on Applications of Dynamical Systems Minisymposium on “The Role of Noise from Single Cells to Populations," Denver, CO

• May 5-9, 2025: ICERM Uncertainty Quantification for Mathematical Biology, Providence, RI

Community

In addition to my professional memberships, I very much enjoy my interactions with: 

• Seminar on Stochastic Processes

• Women in Probability

• Statistical Mechanics of Spin Glasses, Neural Networks and Learning

• Fields Institute Thematic Program on Mathematical Oncology

• National Institute for Theory and Mathematics in Biology workshop on ecological dynamics 

• Cleveland Clinic, Moffitt Cancer Center Integrated Mathematical Oncology (Moffitt IMO), and Pfizer

Gratitude

• My letter writers for their time and support over many years!

• My formal and informal mentors for my academic growth.

• My collaborators for our productivity and inspirations.

• Administrators and staff for easy paperwork and pleasant working environment.

• My students for their curiosity and creativity. I am proud of you!

• My family and friends for their love & wisdom and our cherished memories. I love you!

• and many more...