Embedded Files
Selected Publications
"Von Neumann and Newman pokers with finite decks." The Mathematical Intelligencer (2025): 1-9. (With Thotsaporn Aek Thanatipanonda, and Doron Zeilberger)
"Caged Markov process–A continuous-time framework for modeling a constrained Markov process within a freely-evolving Markov process." Mathematics and Computers in Simulation 230 (2025): 350-369. (With Tanes Printechapat and Pakorn Aiewsakun)
"Embedded Vehicle Routing Problem: A modelling and optimization framework for real-world multi-purpose truck network." IEEE Access (2024). (With Chanon Boonkangwan, Chanoknun Phunnasorn, and Wasakorn Laesanklang)
"GDESA: Gradient Differential Evolution-Simulated Annealing Hybrid." IEEE Access (2024). (Witih Bhumrapee Soonjun)
"The card guessing game: A generating function approach." Journal of Symbolic Computation 115 (2023): 1-17. (With Thotsaporn Aek Thanatipanonda)
"Kernels over sets of finite sets using rkhs embeddings, with application to bayesian (combinatorial) optimization." International Conference on Artificial Intelligence and Statistics. PMLR, 2020. (With Poompol Buathong and David Ginsbourger)
Railay Beach, Thailand
Cornell Sky, USA
Research
My journey began at Chulalongkorn University in Thailand, where I earned a bachelor’s degree in mathematics. I later pursued graduate studies at Cornell University in the U.S., completing a Ph.D. in Applied Mathematics. My doctoral research focused on solving complex optimization problems—particularly those involving computationally expensive simulations—using radial basis function methods.
During my postdoctoral work in Switzerland, at the University of Bern and the Idiap Research Institute, under the supervision of David Ginsbourger↗️, I focused on Bayesian optimization, working with Gaussian process regression models to tackle high-cost black-box problems.
More recently, my research interests have expanded to include operations research, probabilistic modeling, and combinatorics. This includes developing new frameworks for constrained Markov processes, designing hybrid and Bayesian optimization algorithms, and addressing complex vehicle routing challenges through neural networks. I’ve also explored applications in GIS-based agricultural planning, combinatorics card-guessing games, and other decision-making problems.
Research Projects as Lead Investigator
2024–2028: Swiss National Science Foundation (SNSF) under SPIRIT, Joint research funding with Phil Garner↗️ from Idiap Research Institute, Martigny, Switzerland. Modelling, Optimisation and Routing using Physiological Networks.
2022–2024: Thailand Science Research and Innovation (TSRI). Spatiotemporal Gaussian Process Regression for Time-Dependent Traffic Information.
2017–2020: Commission on Higher Education (CHE), Thailand. Groundwater Contamination Remediation: Simulation and Optimization.
2017–2019: Thailand Research Fund (TRF). Large-Scale Bayesian Global Optimization with Gaussian Processes.
Matterhorn, Switzerland
Grand Canyon National Park, USA
Past Fellowships
2014–2015: Swiss Government Excellence Postdoctoral Scholarship, Switzerland.
2008–2012: King Anandamahidol Foundation Scholarship, Thailand.
2007–2009: Fulbright Fellowship, USA.
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