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Dr. Chaklam Silpasuwanchai

Position
Assistant Professor
Unit
Computer Science and Communication Technology (CSCT)
Faculty of Advanced Science and Technology
Contact Info
+66-63-310-9191
chaklam@ait.asia
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PROFILE
EDUCATIONAL BACKGROUND
RESEARCH INTERESTS
TEACHING
ACADEMIC SERVICES
SELECTED PUBLICATIONS
ONGOING AND COMPLETED PROJECTS
AWARDS AND HONORS
RESEARCH KEYWORDS

Dr. Chaklam Silpasuwanchai is an Assistant Professor in Computer Science and Communication Technology (CSCT), Faculty of Advanced Science and Technology (FAST), at the Asian Institute of Technology (AIT), Thailand.
He leads the AIT Brain Lab, which focuses on Human-Centered Natural Language Processing (NLP) and Human-AI Interaction, with research emphasizing the understanding and modeling of humans, the design of health and well-being technologies, and the development of technologies that empower human lives.

His research interests include Human-Centered AI, Natural Language Processing, Human-AI Interaction, Large Language Models, Generative AI, health and well-being technologies, accessibility and assistive technologies, Brain-Computer Interfaces, medical imaging, and intelligent systems for human empowerment.

He is an active reviewer and author for major international conferences, including CHI, ACL, and NeurIPS. He is a recipient of the CHI Best Paper Award in 2017 and the CHI Best Paper Award in 2026.

His research has been supported by organizations including the Gates Foundation, Toyota Mobility Foundation, NBTC, the Thailand Fundamental Fund, the National Research Council of Thailand, KAKENHI, the Thailand Research Fund, the National Science and Technology Development Agency, JST, and other funding organizations.

He received his Ph.D. and conducted postdoctoral research under the supervision of Xiangshi Ren at the Center for Human-Engaged Computing, Japan.

His research is grounded in the concept of Human-Engaged Computing, which explores how technologies can augment human capabilities and support human survivability and well-being. He has co-authored work with Xiangshi Ren on the philosophical foundations of Human-Engaged Computing and its implications for technology design.

He is also a co-founder of AI Brain Lab, a company established to translate selected research outcomes into practical and commercial applications.

  1. Ph.D. in Computer Science, Kochi University of Technology, Japan (2017)
  2. M.E. in Computer Science, Asian Institute of Technology, Thailand (2011)
  3. B.Sc. in Computer Science, Sirindhorn International Institute of Technology, Thailand, (2008)



  • Human-Centered Natural Language Processing
  • Human-AI Interaction
  • Large Language Models and Generative AI
  • Health and Well-Being Technologies
  • Accessibility and Assistive Technologies
  • Brain-Computer Interfaces
  • Medical Imaging and Visual Question Answering
  • Machine Learning and Deep Learning
  • Data Structures and Algorithms
  • Software Architecture Design
  • Programming for Data Science
  • Machine Learning
  • Natural Language Processing
  • Deep Learning
  • Human-Computer Interaction
  • Academic Program Coordinator of Data Science and AI Program, Asian Institute of Technology, 2025-present
  • Chair, AI and Simulation Lab, Asian Institute of Technology, January 2024-present
  • Reviewer, ACL, CHI, and NeurIPS, March 2024-present
  • Doctoral Progress Review Committee, Asian Institute of Technology, September 2023-present
  • Faculty Relation Committee, Asian Institute of Technology, March 2024-April 2026
  • Chair, AIT Sustainability Positioning Task Force, Asian Institute of Technology, September 2023-December 2025
  • Academic Program Coordinator of Computer Science Program, Asian Institute of Technology, 2021-2024
  • Ethics Committee, Asian Institute of Technology, July 2021-July 2023
  • Computer Science Curricula Advisor, Yangon University, 2019
  • Data Science Curricula Development, Stamford International University, 2019
  • Vice-Secretary General, ICACHI, 2016-2019
  • Technical Liaison, ACM Chinese CHI, 2013-2016
  1. Pananookooln, C., Akaranee, J., and Silpasuwanchai, C. Comparing Selective Masking Methods for Depression Detection in Social Media. Computational Linguistics. 2023.
  2. Niksirat, KS., Silpasuwanchai, C., Cheng, P. and Ren, X. Attention Regulation Framework: Designing Self-Regulated Mindfulness Technologies. ACM Transactions on Computer-Human Interaction. 26, 6, Article 39 (November 2019), 44 pages. DOI: https://doi.org/10.1145/3359593.
  3. Niksirat, KS., Silpasuwanchai, C. and Ren, X. Sex Differences in relationship between flow proneness in everyday life and gray matter of the dopaminergic system: a cross-sectional study. Personality and Individual Differences 141. 2019.
  4. Silpasuwanchai, C., Ma, X., Shigemasu, H., and Ren, X. Developing a Comprehensive Engagement Framework of Gamification for Reflective Learning. Proc. ACM DIS 2016.
  5. Silpasuwanchai, C. and Ren, X. Designing Concurrent Full-Body Gestures for Intense Gameplay. International Journal of Human Computer Studies 80 (1), Elsevier, 2015.
  1. Gates Foundation (PI): Advancing Open-Source Digital Public Infrastructure in Asia-Pacific — May 2026 – May 2029 (3,000,000 USD / approximately 105,000,000 Baht).
  2. Toyota Mobility Foundation (PI): Integrated Traffic Analytics Platform in Chatuchak Bangkok — May 2026 – Nov 2026 (500,000 Baht).
  3. Toyota Mobility Foundation (co-PI): Black Spots Improvement in Chachoengsao — June 2024 – June 2027 (3,984,814 Baht).
  4. Thailand Fundamental Fund (co-PI): AI System for Stroke Prediction and Recovery Analysis — Oct 2025 – Sep 2026 (2,000,000 Baht).
  5. Office of the National Broadcasting and Telecommunications Commission (co-PI): โครงการพัฒนาภูมิปัญญาภาษามือและการนำไปประยุกต์ใช้ — Oct 2025 – Sep 2027 (13,303,064.49 Baht).
  6. Royal Golden Jubilee PhD.: RGJPHD by National Research Council of Thailand (NRCT) (PI): Developing Question-Answering System Using Large Language Models for Thai Applications — Sep 2023 – Feb 2026 (1,690,000 Baht).
  7. Office of the National Broadcasting and Telecommunications Commission (co-PI): Telehealth Monitoring and Assistive Systems for Elderly and Disabled People — June 2022 – June 2025 (14,000,000 Baht).
  8. Ministry of Higher Education, Science, Research and Innovation (MHESI), Young Scientist (PI): Hybrid P300-SSVEP BCI Speller for Thai Language — March 2021 – March 2023 (595,000 Baht).
  9. Thailand Science Research and Innovation (TSRI) (PI): Hybrid P300-SSVEP BCI Speller for Thai Language — October 2020 – October 2021 (124,750 Baht).
  10. Thailand Toray Science (PI), National Science and Technology Development Agency: Hybrid P300-SSVEP BCI Speller for Thai Language — March 2019 – March 2020 (190,000 Baht).
  11. Stamford Competitive Internal Grants (PI): Developing Brain-Computer Interfaces Using P300 — September 2018 – September 2019 (234,000 Baht).
  12. Grant-in-Aid for Scientific Research by MEXT (PI), Ministry of Education, Culture, Sports, Science and Technology, Japan (No. 16K21300): Investigating Cognitive Enhancement of Elderly People by Using Motion Video Games — April 2016 – March 2018 (4,992,000 JPY).
  13. Japan-Finland Collaborative Research Projects by JST, AF and Tekes (co-PI): User Interface Design for the Ageing Population — April 2015 – March 2017 (18,000,000 JPY).
  1. Best CHI Paper Award – 2026
  2. Best Teacher Award, Asian Institute of Technology (AIT), Large Class Category – 2024
  3. Best CHI Paper Award – 2017
  4. Honorable Mention by the ICACHI Community – 2015
  5. Special Scholarship Program Full Scholarship, Kochi Prefecture, Japan – 2012-2015
  6. Royal Thai Government Full Scholarship, Asian Institute of Technology, Thailand – 2009-2011
  7. 2nd Place Award, Thailand National Open-Sourced Software Contest, for a sketch recognition algorithm for diagram construction – 2008
  8. KAKENHI Young Scientist Grant
  9. Young Scientist Grant by Thailand Research Fund (TRF)
  10. National Science and Technology Development Agency (NSTDA) Toray Science Grant
  11. JST Grant Project – Member
  • Human-Centered NLP
  • Human-AI Interaction
  • Large Language Models
  • Generative AI
  • Natural Language Processing
  • Machine Learning
  • Deep Learning
  • Brain-Computer Interfaces
  • Medical Imaging
  • Health and Well-Being Technologies
  • Accessibility and Assistive Technologies