ดร.วราสิณี ฉายแสงมงคล | Dr.Warasinee Chaisangmongkon
Short Bio
Dr. Warasinee Chaisangmongkon is a lecturer at the Institute of Field Robotics (FIBO), King Mongkut’s University of Technology Thonburi. She
has a Bachelor’s Degree in Physics and Cognitive Psychology from Cornell University and a Ph.D. in Computational Neuroscience from Yale
University, where she studied deep learning models that mimic human cognition.
Dr. Warasinee Chaisangmongkon is a lecturer at the Institute of Field Robotics (FIBO), King Mongkut’s University of Technology Thonburi. She
has a Bachelor’s Degree in Physics and Cognitive Psychology from Cornell University and a Ph.D. in Computational Neuroscience from Yale
University, where she studied deep learning models that mimic human cognition.
Dr. Chaisangmongkon co-founded Perceptra Co., Ltd., an AI startup with a mission to improve health outcomes for millions of people with
cutting-edge technology. Perceptra is building a robust, scalable artificial intelligence platform for enhanced medical services in Thailand.
education
● 2010 – 2015 Yale University, New Haven, CT, USA — M.Phil & Ph.D.Computational Neuroscience : Modeling brain function with deep learning
● 2005 – 2009 Cornell University, Ithaca, NY, USA — B.A.Physics and Cognitive Psychology
experience
● Since 2015 Institute of Field Robotics, KMUTT — Lecturer
●Since 2015 Big Data Experience Center, KMUTT — Data Scientist
●Since 2017 Perceptra Co., Ltd. — Co-Founder (CTO, 2021-2023)Robotic Dexterity, Factory Automation Analysis and Design of Mechanism and Control Systems
Selected Projects
Perceptra Co. Ltd — CTO, 2021 – 2023
● Built a team of engineers (deep learning researchers, MLOps engineer, cloud engineers, and software developers) that
developed and delivered medical AI platform (Inspectra) to over 100 hospitals in Thailand.
● Brought Inspectra CXR to international standard certification ISO-13485, IEC-62304, Thai FDA, Singapore HSA.
Stock Exchange of Thailand — Machine Learning Consultant, 2016 – Present
● Implement recommendation system for mobile trading platform
● Implement end-to-end Big Data Analytic and Automated Machine Learning system for marketing strategy team
Kasikorn Bank PLC — Machine Learning Consultant, 2016 – 2019
● Consultant for machine learning team at Kasikorn Bank Technology Group (KBTG)
● Built a credit risk prediction and analytics
● Built the real estate intelligence platform
NVIDIA — Certified Deep Learning Instructor, 2019
Advanced Info Service — Machine Learning Consultant, 2018 – 2019
● Consultant for the mobile phone recommender engine project
ICC International Co., Ltd. — Machine Learning Consultant, 2018 – 2019
● Built retail analytics pipelines and dashboards
● Develop machine learning model for product sales forecasting
● Develop analytic model for product lifecycle dynamics
Ayudhya Capital Services — Machine Learning Consultant, 2016 – 2017
● Built the recommender engine for credit card offersJoint Committee Member (1996 – present)
KMUTT – MIT Collaborative S&T Programs
SELECTED RESEARCH AND TRAINING PROJECTS
The Development of Theoretical and Practical Resources for Application of Artificial
Intelligence for Medical Image Analysis in Thailand
Fundamental Fund, TSRI, 2022
Artificial Intelligence for the Improvement of Breast Cancer Screening and Diagnostics
on Pilot Hospitals
National Innovation Agency (Thailand), 2022
AI for All : Training Young Engineers for AI
PMU-B NXPO, 2020
The Development of Tuberculosis Detection Algorithm for Thai Population
ASAHI Foundation Research Grant, 2020
The Development of Artificial Intelligence Algorithm for Chest X-Ray Analysis
National Innovation Agency (Thailand), 2019-2020
Machine Learning Training Program
Western Digital – Metropolitan Waterworks Authority – SCG Chemicals, 2019
AI for Business, Big Data Analytics with Apache Spark Training Program
Advanced Info Services, 2019
Deep Learning Training Program
Defence Technology Institute – Chulalongkorn University, 2018
A Cloud-based Framework for Autonomous Big Data Modeling
ASAHI Foundation Research Grant, 2017
Probabilistic Topic Mining Model for Thai Language
KMUTT Research Grant, 2016
Dynamic model of human decision making function
Yale University, 2009-2015
Study human unconscious decision through behavioral analytics and
electroencephalography (EEG)
Cornell University, 2007-2009
Modeling material properties analyzing nano-scale images from scanning tunneling
and atomic force microscopy
IBM Almaden Research Center, 2005-2006
Conferences and Publications
Chaiyungyuen, S., Chetprayoon, P., Chaisangmongkon, W. and Sakdejayont, T., 2023, May.
Addressing Data Scarcity in Thai Car Recognition Using Few-Shot Learning. In 2023 8th
International Conference on Business and Industrial Research (ICBIR) (pp. 471-476). IEEE.
Saiviroonporn, P., Wonglaksanapimon, S., Chaisangmongkon, W., Chamveha, I., Yodprom, P., Butnian, K., Siriapisith, T. and Tongdee, T., 2022.
A clinical evaluation study of cardiothoracic ratio measurement using artificial intelligence. BMC Medical Imaging, 22(1), pp.1-10.
Rajak, A., Chaisangmongkon, W., Chamveha, I., Promwiset, T., Rungsinaporn, K., Saiviroonporn, P. and Tongdee, T., 2022, November.
External Validation of Deep Learning Algorithm for Tuberculosis Detection in Thai Population. In 2022 6th International Conference on Information Technology (InCIT) (pp. 314-319). IEEE.
Harnpadungkij, T., Chaisangmongkon, W. and Phunchongharn, P., 2022. Risk-Sensitive Portfolio
Management by Using C51 Algorithm. CHIANG MAI JOURNAL OF SCIENCE, 49(5), pp.1458-1482.
Chanlongrat, W., Apichanapong, T., Sinngam, P. and Chaisangmongkon, W., 2022. A semi-automated system for person re-identification
adaptation to cross-outfit and cross-posture scenarios. Applied Intelligence, 52(8), pp.9501-9520.
Saiviroonporn, P., Rodbangyang, K., Tongdee, T., Chaisangmongkon, W., Yodprom, P., Siriapisith, T., Wonglaksanapimon, S. and Thiravit, P., 2021.
Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies. BMC Medical Imaging, 21(1), p.95.
Chaisangmongkon, W., Chamveha, I., Promwiset, T., Saiviroonporn, P. and Tongdee, T., 2021.
External validation of deep learning algorithms for cardiothoracic ratio measurement. IEEE Access, 9, pp.110287-110298.
Chamveha, I., Promwiset, T., Tongdee, T., Saiviroonporn, P., Chaisangmongkon, W. (2021).
Local Adaptation Improves Accuracy of Deep Learning Model for Automated X-Ray Thoracic Disease Detection : A Thai Study. (Accepted at 19th Asian Oceanian Congress of Radiology)
Chamveha, I., Tongdee, T., Saiviroonporn, P., Chaisangmongkon, W. (2020).
Local Adaptation Improves Accuracy of Deep Learning Model for Automated X-Ray Thoracic Disease Detection : A Thai Study. arXiv preprint arXiv:2004.10975.
Chamveha, I., Promwiset, T., Tongdee, T., Saiviroonporn, P., Chaisangmongkon, W. (2020).
Automated Cardiothoracic Ratio Calculation and Cardiomegaly Detection using Deep Learning Approach. arXiv preprint arXiv:2002.07468.
Limsurat, T., and Chaisangmongkon, W. (2019).
Event-based Feature Synthesis: Autonomous Data Science Engine. Journal of Computers, 30(2),
pp. 55-67
Asawaroengchai, C., Chaisangmongkon, W., & Laowattana, D. (2018, May).
Probabilistic learning models for topic extraction i Thai language. In
2018 5th International Conference on Business and Industrial Research (ICBIR) (pp. 35-40). IEEE.
Chaisangmongkon, W., Swaminathan, S.K., Freedman, D.J. and Wang, X.J., 2017.
Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions. Neuron, 93(6), pp.1504-1517.
Soltani, A., Chaisangmongkon, W., and Wang, X.J., 2017.
“Neural Circuit Mechanisms Of Value-Based Decision-Making And Reinforcement
Learning”. Decision Neuroscience, 163-176. doi:10.1016/b978-0-12-805308-9.00013-0.
Engel, T.A., Chaisangmongkon, W., Freedman, D.J. and Wang, X.J., 2015.
Choice-correlated activity fluctuations underlie learning of neuronal category representation. Nature communications, 6. (* equal contribution)
Chaisangmongkon W, Swaminathan SK, Freedman DJ, Wang XJ.
Dynamic neural population coding of visual categories in the fronto-parietal
network. Society for Neuroscience annual meeting, San Diego, CA. November 9-13, 2013.
Chaisangmongkon W, Engel TA, Freedman DJ, Wang XJ.
Reward-dependent plasticity model for categorization and category match decision.
Society for Neuroscience annual meeting, New Orleans, LA. Oct 13-17, 2012.
Chaisangmongkon W, Swaminathan SK, Freedman DJ, Wang XJ.
Direction tuning vs. category tuning in delayed match-to-category task.
Computational and Systems Neuroscience (Cosyne) annual meeting, Salt Lake City, UT. February 23-26, 2012.
