Dr. Chantri Polprasert
Dr. Chantri Polprasert is an Assistant Professor at the Asian Institute of Technology whose work focuses on artificial intelligence, machine learning, and data science, with particular emphasis on sign language intelligence and inclusive communication technologies. His research spans sign language recognition, sign language production, multimodal AI, and multilingual sign language translation. He also conducts research on graph neural networks, AI for health analytics, recommendation systems, and virtual credential design for vulnerable groups. His broader interests include cloud-based AI systems, data engineering, and applied AI for education, accessibility, and socially impactful digital services. He actively collaborates with regional and international partners to develop inclusive, human-centered technologies with real-world impact.
- Ph.D. in Electrical Engineering, University of Washington, Seattle, USA, 2009
- M.Eng. in Telecommunications, Asian Institute of Technology, Thailand, 2000
- B.Eng. in Electrical Engineering, Chulalongkorn University, Thailand, 1999
Dr. Chantri’s research interests include sign language intelligence, sign language recognition and production, multimodal AI, inclusive communication technologies, graph neural networks for stroke prediction, recommendation systems, virtual credential design for vulnerable groups, machine learning, data science, cloud-based AI systems, and AI for education and accessibility.
Dr. Chantri Polprasert teaches courses in computer science, data science, artificial intelligence, algorithm design, data structures, data engineering, MLOps, full-stack application development, and cloud computing. His teaching integrates conceptual foundations with hands-on practice, with emphasis on problem solving, algorithmic thinking, machine learning workflows, data-driven system development, and modern computing platforms. He is committed to preparing students to design and build practical digital solutions for real-world challenges, especially in accessibility, education, and socially impactful technologies.
Representative courses include:
- Algorithm Design and Data Structures
- Computer Programming for Data Science and Artificial Intelligence
- Data Engineering and MLOps
- Full Stack Application Development
- Cloud Computing
He has also previously taught Computer Networks and Numerical Methods at Srinakharinwirot University.
- Phuangchoke, N., & Polprasert, C. (2026). Bridging Text-to-Sign Translation via Codebook-Oriented Pretraining. Accepted at LREC-COLING 2026.
- Arayarungsarit, N., Phuangchoke, N., & Polprasert, C. (2026). Enhancing Sign Language Recognition with Video Swin Transformer and Keypoint-Based Frame Selection. In Data Science and Artificial Intelligence (DSAI 2025), Springer CCIS.
- Pongnumkul, S., Khonnasee, C., Lertpattanasak, S., & Polprasert, C. (2020). Proof-of-Concept (PoC) of Land Mortgaging Process in Blockchain-based Land Registration System of Thailand. In Proceedings of the 2nd International Conference on Blockchain Technology (ICBCT 2020).
- Polprasert, C., Ritcey, J. A., & Stojanovic, M. (2011). Capacity of OFDM Systems Over Fading Underwater Acoustic Channels. IEEE Journal of Oceanic Engineering.
- Polprasert, C., Kukieattikool, P., Demeechai, T., Ritcey, J. A., & Siwamogsatham, S. (2013). New stimulation pattern design to improve P300-based matrix speller performance at high flash rate. Journal of Neural Engineering.
- Polprasert, C., & Ritcey, J. A. (2008). A Nakagami Fading Phase Difference Distribution and Its Impact on BER Performance. IEEE Transactions on Wireless Communications.
- Polprasert, C., & Ritcey, J. A. (2012). Performance analysis of the bit-interleaved coded modulation using turbo equalization with single-carrier frequency-domain equalization over fast fading channels. Signal Processing.
Dr. Chantri Polprasert is currently involved in research projects in sign language intelligence, AI for health, and digital public infrastructure.
- Sign Language Intelligence and Applications
Funded by the Office of the National Broadcasting and Telecommunications Commission (NBTC), Thailand; Principal Investigator; December 2025 – November 2028; 13.3 million THB.
This project focuses on developing sign language intelligence technologies, language resources, and AI systems to support accessible communication and inclusive digital services. - AI System for Stroke Prediction and Recovery Analysis
Funded by Thailand Science Research and Innovation (TSRI); Principal Investigator; September 2025 – August 2026; 2 million THB.
This project develops AI-based methods for stroke prediction and recovery analysis using data-driven models for healthcare support. - Advancing Open-Source Digital Public Infrastructure in Asia-Pacific
Funded by the Gates Foundation; Co-Investigator; May 2026 – April 2029; USD 3 million.
This project supports the advancement of open-source digital public infrastructure in Asia-Pacific, with emphasis on inclusive, interoperable, and scalable digital systems.
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- Honorable Mention Award for Toktak: An Autonomous Convenience Robot for Internal Deliveries for People with Movement Disability in the Youth Innovation for Society Contest, 2020
- Bronze Award from the National Research Council of Thailand (NRCT) for Trashy: A Smart Bin for Recycling, 2020
- Ph.D. Thesis Award, National Research Council of Thailand (NRCT), 2011
- Mobile App Award for the Tangmochecker Android App, NECTEC, 2011
- Fellow, UK Professional Standards Framework (UKPSF)
- Reviewer for international journals and conferences in AI, computing, and engineering
- AWS Certified Solutions Architect
- AWS Certified Cloud Practitioner
- CCNA Certified Instructor
- Sign language intelligence
- Sign language recognition
- Sign language production
- Multimodal AI
- Inclusive communication technologies
- Graph neural networks
- Stroke prediction
- Recommendation systems
- Virtual credentials
- Digital public infrastructure
- Machine learning
- Data science
- Cloud-based AI systems
- AI for education and accessibility
