Dr. Thu Thi Le Nguyen

Tenure-Track

Department of Mathematics and Statistics

College of Natural and Mathematical Sciences

She/Her/Hers/Herself

About

I received the B.Sc. degree in Mathematics and Computer Sciences from the University of Sciences HCM VNU, Ho Chi Minh City, Vietnam, in 2008, the M.Sc. degree in Applied Mathematics from the University of Orleans, France, in 2010, the Ph.D. degree in Statistical Signal Processing from Lille1 University-Science and Technology, France, in 2014, and the PhD. degree in Applied Mathematics from Wayne State University, USA, in 2020. I have been working as a tenure-track assistant professor in the department of Mathematics and Statistics at UMBC since August 2020.

Research interests

Stochastic Approximation, Monte Carlo Methods, Bayesian Estimation/ Inference, Statistical Learning, Machine Learning, Stochastic Systems, Stochastic Processes, Stochastic Simulation, Numerical Methods, Stochastic Differential Equations, Dynamical Systems.

Teaching interests

Statistics, Statistical Learning, Machine Learning, Applied Probability and their applications in Engineering, Life Sciences, Finance and Actuarial Sciences.

Education

  • MA, Statistics — Wayne State University (2020)
  • Ph D, Applied Mathematics — Wayne State University (2020)
    Stochastic Approximation and Applications to Network Systems
  • Ph D, Statistical Signal Processing — Lille 1 University-Science and Technology (2014)
    Sequential Monte Carlo Sampler for Bayesian Inference in Complex Systems.
  • MS, Applied Math — University of Orleans (2010)
    Exchangeable Distributions and Applications
  • BS — University of Science Ho Chi Minh City, Vietnam National University (2008)
    Dispersion Functions in L² Space.

Publications

  • Enhanced Time Series Forecasting with Convolutional Neighborhood Similarity and Dual Attention Mechanisms. In Preparation; Not Yet Submitted
  • Segment-based join temporal and variables attention for multivariate time series forecasting. Submitted

Presentations

  • A Chemostat Model with Common Noise 2020 2020 Guam TICEAS · MOCT Education Institution · Oral Presentation Thu Nguyen, George Yin (Author & Presenter), Le Yi Wang (Author)
  • Switching Stochastic Approximation and Applications to Networked Systems 2020 Joint Mathematics Meetings · AMS, MAA · Oral Presentation

Grants and Contracts

  • Advanced Machine Learning Approaches for Enhanced GCS Prediction in Traumatic Brain Injury 2025 UMB · Grant · In-Progress

Research in Progress

  • Bridging Multi-Agent Consensus and Online Learning with Asynchronous Stochastic Approximation 2025 Scholarly · Writing Results
  • DEEP LEARNING BASED TECHNIQUES FOR TRAUMA DATA 2025 Scholarly · Writing Results
  • Spatial-Temporal Modeling and Forecasting of Public Health Outcomes Using Advanced Regression Methods 2025 Scholarly · Writing Results

Courses Taught

  • Statistical Learning STAT 436 · Fall 2025
  • Statistics Practicum STAT 496 · Fall 2024
  • Financial Math for Actuaries MATH 365 · Fall 2024
  • Top:Stat Mthd/Data Analy STAT 700 · Spring 2024
  • Special Topics In Stat STAT 490 · Spring 2024
  • Indep Study In Math MATH 499 · Spring 2024
  • Statistical Learning STAT 606 · Fall 2023
  • Statistical Learning STAT 436 · Fall 2023
  • Financial Math for Actuaries MATH 365 · Fall 2023
  • Pre Candidacy Doc Rsch STAT 898 · Spring 2023
  • Special Topics In Stat STAT 490 · Spring 2023
  • Financial Math for Actuaries MATH 365 · Spring 2023
  • Top:Stat Mthd/Data Analy STAT 700 · Fall 2021
  • Special Topics In Stat STAT 490 · Fall 2021
  • Financial Math for Actuaries MATH 365 · Fall 2020