I would like to thank you for visiting my homepage. My nationality is Vietnamese-American. My primary research interests lie in Applied Mathematics and Computer Science, including harmonic analysis, optimization, and stochastic calculus, with applications in signal and image processing, machine learning, and stochastic dynamical systems. I am currently a Research Fellow in the Division of Mathematical Sciences at NTU, Singapore, working with Dr. Ariel Neufeld on a project of Stochastic Dynamical Systems for Imaging. Previously, I was an Associate at SSC, where I worked on research projects involving partially observable Markov decision processes in reinforcement learning and hierarchical Dirichlet processes for Bayesian object tracking, contributing to work for the U.S. Navy. I also served as a Research Collaborator V at Meta, USA, where I worked on an AI project titled Inverse Reinforcement Learning from Human Feedback for Large Language Modeling.

Education and Work Experience:

• Dec 2025: Research Fellow in Division of Mathematical Sciences, Nanyang Technological University, Singapore, with A. Prof. Dr. Ariel Neufeld 

• Nov 2024 - Dec 2025: Research Collaborator V at Meta, USA  

• May 2024 - Nov 2024: Associate in Signal Systems Corporation (SSC), USA

• 2022-2024: Research Associate in department of Biomedical Engineering at university of Virginia, USA 

• 2021-2022: Post Doc Research Fellow in Geography and GeoInformation Science at George Mason University, USA

• 2016-2021: Post Doc Research Fellow in Department of Statistical Science at Duke university, USA, with Prof. D. Banks, S. Mukherjee, D. Dunson

• 2015-2016: Post Doc Research Fellow in The Statistical and Applied Mathematical Science Institute (SAMSI), USA, with Prof. R. Smith (UNC)

• 2011-2015: PhD in Institute for Mathematical Stochastics, University of Goettingen, Germany, with Prof. A. Munk and P. Mihailescu

• 2009-2011: Master in Bio-Mechatronics Engineering, Sungkyunkwan University, South Korea

• 2008-2009: Master in Control Theory, Faculty of Electrical - Electronics, Ho Chi Minh City University of Technology, Vietnam (not finished)

• 2008: Undergraduate in Control Theory (honor program), Faculty of Electrical - Electronics, Ho Chi Minh City University of Technology, Vietnam

Publications:

1. D.H. Thai. Bayesian Approach to Large POMDPs in System Identification. [in preparation].

2. D.H. Thai, A.L. Young and D.B. Dunson. Proximal Algorithms for Accelerated Langevin Dynamics. [in preparation].

3. A.H.M. Rubaiyat, D.H. Thai, G.K. Rohde, J.M. Nichols, M.N. Hutchinson. System Identification Using the Signed Cumulative Distribution Transform In Structural Health Monitoring Applications, 2023. [article] [arxiv] [code]

4. X. Fei, M.T. Le, D.H. Thai, K. Wessels and A. Zufle. Semi-Supervised Satellite Image Segmentation Using Spatial and Temporally Informed Poisson Segmentation. IGARSS 2023: 5642-5645.

5. D.H. Thai, X. Fei, M.T. Le, A. Zufle and K. Wessels. Riesz-Quincunx-Unet Variational Auto-Encoder for Satellite Image Denoising. IEEE Transactions on Geoscience and Remote Sensing, 2023. [article] [arxiv] 

6. A. Susarla, A. Liu, D.H. Thai, M.T. Le and A. Zufle. Spatiotemporal Disease Case Prediction Using Contrastive Predictive Coding. SpatialEpi '22: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, 2022. [article] [code]

7. D.H. Thai and D. Banks. Directional Mean Curvature for Textured Image Demixing. Applied Mathematical Modelling, Vol. 102, 2021. [article] [arxiv] 

8. R. Richter, D.H. Thai and S. Huckemann. Generalized Intersection Algorithms with Fixpoints for Image Decomposition Learning, SIAM Journal on Imaging Sciences, Vol. 14, Iss. 3, 2021. [article] [arxiv] 

9. R. Richter, D.H. Thai, C. Gottschlich and S. Huckemann. Filter Design for Image Decomposition and Applications to Forensics. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2020. [article]

10. D.H. Thai, Hau-Tieng Wu and D. Dunson. Locally Convex Kernel Mixtures: Bayesian Subspace Learning. 18th ICMLA, 2019. [article] 

11. R. Richter, C. Gottschlich, L. Mentch, D.H. Thai and S. Huckemann. Smudge Noise for Quality Estimation of Fingerprints and its Validation. IEEE Transactions on Information Forensics and Security, 2019. [article] 

12. D.H. Thai and L. Mentch. Multiphase Segmentation For Simultaneously Homogeneous and Textural Images. Applied Mathematics and Computation, 335(15):146-181, October 2018. [article] 

13. D.H. Thai and C. Gottschlich. Simultaneous Inpainting and Denoising by Directional Global Three-part Decomposition: Connecting Variational and Fourier Domain Based Image Processing. R.Soc.opensci.5: 171176, June 2018. [article] 

14. D.H. Thai and C. Gottschlich. Directional Global Three-part Image decomposition. EURASIP Journal on Image and Video Processing, 2016(12):1-20, March 2016. [article] 

15. D.H. Thai and C. Gottschlich. Global Variational Method for Fingerprint Segmentation by Three-Part Decomposition. IET Biometrics, 5(2):120-130, June 2016. [article] 

16. D.H. Thai, S. Huckemann and C. Gottschlich. Filter Design and Performance Evaluation for Fingerprint Image Segmentation. PLoS ONE, 11(5):e0154160, May 2016. [article] 

17. S.H. Cho, D.H. Thai, J.W. Han and H. Hwang. Multi-level Thresholding based on Non-Parametric Approaches for Fast Segmentation. Journal of Biosystems Engineering, 38(2):149-162, June 2013. [article]

18.  D.H. Thai. Fourier and Variational Based Approaches for Fingerprint Segmentation. PhD thesis, University of Goettingen, 2015. [dissertation]