Research topics:
Quantum Simulation & Algorithms, Biophysics & Complex Systems
Contact: thiparat.c [AT] chula.ac.th
Office: MHMK Building Room 1905
About me: I’m a theorist working at the intersection of physics and computer science. Our work typically involves formulating and developing theoretical concepts and computational software to solve problems in complex systems and artificial intelligence. The current focus is on the analysis and the design of novel algorithms for learning and forecasting classical and quantum dynamics through the lens of computational neuroscience, statistical physics, and quantum information science. I also work closely with industry partners, identifying and solving real-world problems using tools from network science and quantum-inspired optimization.
Education & past employments:
Faculty member, Department of Physics, Faculty of Science, Chulalongkorn University (2019-present)
Visiting scientist at EPFL, Lausanne, Switzerland (2023) & KITP, Santa Barbara, USA (2019)
Postdoctoral scholar, SUTD, Singapore (2016-2019)
Ph.D. in Theoretical Physics, Harvard University, USA (2016)
M.A. in Physics, Harvard University, USA (2012) & in Mathematics, The University of Virginia, USA (2009)
B.S. in Physics and Mathematics (with Highest Distinction, Phi Beta Kappa), The University of Virginia, USA (2008)
Outreach and academic services
Program committee: Quantum Techniques in Machine Learning (QTML2023), Workshop organizer: Bangkok Workshops on Discrete Geometry, Dynamics & Statistics (link), Quantum industry conference organizer (link)
Reviewer: Physical Review Journals, New Journal of Physics, Quantum Science and Technology, Neurocomputing, AAAI, NeurIPS.
Media Partners: Suthichai Live (link), the Standard (link), Tam-Eig (link)
Quantum Ecosystem and Education by Techsauce Ep. [1][2][3][4][5]
BrainCodeCamp: AI and computational neuroscience for enthusiastic Thais (link)
Selected publications:
Rungratsameetaweemana, N., Kim, R., Chotibut, T., Sejnowski, R, Random noise promotes slow inhibitory dynamics important for robust working memory in network models, in submission (link)
Kokaew, W., Chotibut, T., Chantasri, A., Quantum state preparation control in noisy environment via most likely path, to appear in Phys. Rev. A 2023 [best poster award YQIS 2021] (link)
Tangpanitanon, J., Saiphet, J., Palittapongarnpim, P., Chaiwongkhot, P., Prugsanapan, P., Raksasri, N., Wannasiwaporn, W., Raksri, Y., Thajchayapong, P., Chotibut, T., Hybrid Quantum-Classical Algorithms for Loan-Collection Optimization with Loan-Loss Provisions. Phys. Rev. Applied 19, 064001 (2023) [industry collaboration with QTFT and KBTG] (link)
Tangpanitanon, J., Mangkang, C., Bhadola, P., Minato, Y., Angelakis, D., Chotibut, T., Explainable Natural Language Processing with Matrix Product States. New J. Phys. 24 053032 (2022) [featured on tensornetwork.org] (link)
Sornsaeng, A., Dangniam, N., Palittapongarnpim, P., Chotibut, T. Quantum diffusion map for nonlinear dimensionality reduction. Phys. Rev. A 104, 052410 (2021) (link)
Chotibut, T., Falniowski, F., Misiurewicz, M., Piliouras, G. The route to chaos in routing games: When is Price of Anarchy too optimistic? Advances in Neural Information Processing Systems 33 - NeurIPS 2020 (link)
Chotibut, T., Succi, S., and Nelson, D. R. Striated populations in disordered environments with advection. Physica A, 465, 500-514 (2017) (link)
Chotibut, T., Nelson, D. R. Population genetics with fluctuating population sizes. Journal of Statistical Physics: special edition dedicated to the memory of Leo Kadanoff, 167 (3-4) 777-791 (2017) (link)
Job Opportunities:
A few postdoc positions are available. If you’d like to join our team, please send a CV and a 2-page research statement to thiparat.c[at] chula.ac.th.