ดร.ไพสิฐ ขันอาสา | Dr.Paisit Khanarsa
Education
Ph.D. in Applied Mathematics and Computational Science (2018–2020)
ดุษฎีบัณฑิตสาขาคณิตศาสตร์ประยุกต์และวิทยาการคอมพิวเตอร์ คณะวิทยาศาสตร์ จุฬาลงกรณ์มหาวิทยาลัย (Doctor of Philosophy, Applied Mathematics and Computational Science, Chulalongkorn University), Dissertation topic: Automatic Model Identification for Time Series Analysis using Deep Learning.
M.Sc. in Applied Mathematics and Computational Science (2016–2017)
มหาบัณฑิตสาขาคณิตศาสตร์ประยุกต์และวิทยาการคอมพิวเตอร์ คณะวิทยาศาสตร์ จุฬาลงกรณ์มหาวิทยาลัย (Master of Science, Applied Mathematics and Computational Science, Chulalongkorn University (G.P.A 3.94))
B.Sc. in Mathematics (First Class Honours, Gold Medal) (2012–2015)
ปริญญาบัณฑิตสาขาคณิตศาสตร์ คณะวิทยาศาสตร์ มหาวิทยาลักเกษตรศาสตร์ (เกียรตินิยมอันดับหนึ่งเหรียญทอง) (Bachelor of Science, Mathematics, Kasetsart University (1st Class Honours, G.P.A 3.76))
Scholarship
Science Achievement Scholarship of Thailand (SAST) for Bachelor’s, Master’s, and Ph.D. studies (2012–2020)
Professional Experience
• March 2021 – Present, Lecturer at FIBO, KMUTT, Courses: Artificial intelligence, Machine learning, Deep learning, Fundamental Mathematics and Basic programming.
• March 2021 – Present, Researcher at Hospital Automation Research Center (HAC), FIBO, KMUTT, Research fields: Artificial intelligence, Machine learning, Deep learning, Data science.
• October – Present, Researcher in supported by Food and Drug Administration, Project name Surveillance and detection of illegal food advertising on internet
• August – Present, Research Assistant collaborating with Division of Computational Science, Faculty of Science,Prince of Songkla University & Pak Phanang Hospital, Thailand, Project name: Enhancing diabetes follow-up period prediction through classification algorithms with feature selection techniques
• August – December 2024, Research Assistant and Co-Advisor collaborating with VISTEC, Project name: Data Selection for Close-Domain Data in Medical Continual Pretraining.
• August – December 2024, Research Assistant and Co-Advisor collaborating with Sunday Insurance Company, Project name: Development of machine learning to identify individual critical illness risk using population data and group health insurance claim history.
• June 2023-June 2024 – Researcher in supported by Program Management Unit for Human Resources & Institutional Development Research and Innovation (PMU-B) Funds (2566), Project name: Talent Robotics, AI, and Coding Academy and Consortium Development.
• May 2024 – Invited speaker at Ocean Life Insurance Co., Ltd., Topic: Generative AI for Modern Workforce.
• April 2023 – Invited speaker at Thai Aviation Refuelling Co.,Ltd (TARCO), Topic: Artificial Intelligence for Business.
• April 2023 – Invited speaker at Applied Mathematics and Computational Science at Chulalongkon University, Topic: Artificial Intelligence in Medicine: Innovative Use Cases and Applications.
• February 2023 – Invited speaker for AI robotics for all ss 3, Topic: Introduction to Reinforcement learning and Its applications.
• March 2023 – Invited speaker for Faculty of Medicine Vajira Hospital, Topic: Artificial Intelligence in Medicine.
• January 2022 – 2023, Petch KMUTT research Funds, Project name: Research and development of time series models using deep learning to forecast the epidemic of Covid-19.
• October 2022-September 2023 – Researcher in supported by Fundamental Fund (2565), KMUTT, Project name: Robotics and Automation Learning System.
• January 2022 – December 2023, Project owner at Siriraj Applied Thai Traditional Medicine, Faculty of Medicine, Sirirah Hospital, Mahidol University, Project name: The development of artificial intelligence models for diagnosing Dhat Chao Ruean of the patient.
• February 2022, invited speaker, organized by AI/Robotics for all, FIBO, KMUTT, Topic: AI Contents in Thai Robotics Learning Hub
• January 2022, Trainer, organized by FIBO x Kidbright, KMUTT, Topic: Artificial Intelligence development Tools.
• August – September 2021, Trainer, organized by Premium Training (AI/Robotics for all 2020) FIBO, KMUTT, Topic: Introduction to Artificial Intelligence & Machine learning & Deep learning.
• August 2021, invited speaker, organized by Chulalongkorn University, Topic: Automatic model Identification for time series analysis using deep learning.
• November 2021, invited speaker for FIBO Talk Series, organized by FIBO, KMUTT, Topic: Artificial intelligence and robotics ethics in hospitals.
• May 2021, invited speaker for FIBO Virtual Open House 2021, organized by FIBO, KMUTT, Topic: Machine learning training.
• February 2021 – July 2021, Program Developer and Data Analyst, Developed a program for optimizing the efficiency of cement allocation of SCG company.
• February 2020, Speaker Assistant, AI-ML-DL (Artificial Intelligence-Machine Learning-Deep Learning), organized by Rajavithi Hospital and Faculty of Science, Chulalongkorn University, 7 February 2020.
• 2019, Teacher Assistant, Mathematics for Applied Digital Intelligence, International Program School of Integrated Innovation, Chulalongkorn University.
• 2016 – 2019, Teacher Assistant, Calculus I and II, International School of Engineering, Faculty of Engineering, Chulalongkorn University.
• June 2018, Speaker Assistant, Big Data and Data Science, organized by Thailand Post and Faculty of Science, Chulalongkorn University,1 June 2018.
• November – December 2018, Speaker Assistant, Data Science Essential Workshop, organized by Chevron and Faculty of Science, Chulalongkorn University, 27,30 November and 3, 6, 7 December 2018.
• 2011 – 2019, Full scholarship (Bachelors, Masters, and PhD), Science Achievement Scholarship of Thailand (SAST) supporting by grant funds from Office of the Higher Education Commission and Council of Science Dean of Thailand
• 2010, Student of POSN Science Camp, The Promotion of Academic Olympiad and Development of Science Education Foundation under the patronage of Her Royal Highness Princess Galyani Vadhana Krom Luang Naradhiwas Rajanagarindra.
Publications and Conferences
Ardchon, C & Khanarsa, P. Data Selection for Close-Domain Data in Medical Continual Pretraining: A Case Study on Data Selection via Importance Resampling (DSIR). In 2025 9th International Conference on Machine Learning and Soft Computing (ICMLSC 2025). ACM (Accepted)
Uraisomsurat, N & Khanarsa, P. Utilizing Demographic Data and Insurance Claims History to Develop Machine Learning for Assessing Cardiovascular Disease Risk. In 2025 9th International Conference on Machine Learning and Soft Computing (ICMLSC 2025). ACM (Accepted)
Lin, T., Natsupakpong, S., & Khanarsa, P. (2024, November). Deep Learning-Based Course Recommendations Using Sentence Embeddings and User Information for Learning Platforms. In 2024 28th International Computer Science and Engineering Conference (ICSEC) (pp. 1-6). IEEE.
Patcharapimpisut, P., & Khanarsa, P. (2024, February). Generating Synthetic Images Using Stable Diffusion Model for Skin Lesion Classification. In 2024 16th International Conference on Knowledge and Smart Technology (KST) (pp. 184-189). IEEE.
Kitsiranuwat, S., Kawichai, T., & Khanarsa, P. (2023). Identification and Classification of Diseases Based on Object Detection and Majority Voting of Bounding Boxes. Journal of Advances in Information Technology, 14(6).
Khanarsa, P., & Kitsiranuwat, S. (2024). Deep Learning-based Ensemble Approach for Conventional Pap Smear Image Classification. ECTI Transactions on Computer and Information Technology (ECTI-CIT), 18(1), 101-111.
Khanarsa, P., Luangsodsai, A., & Sinapiromsaran, K. (2020, June). Self-identification deep learning ARIMA. In Journal of Physics: Conference Series (Vol. 1564, No. 1, p. 012004). IOP Publishing.
Khanarsa, P., & Sinapiromsaran, K. (2020). Automatic SARIMA order identification convolutional neural network. Int. J. Mach. Learn. Comput, 10(5), 662-668.
Khanarsa, P., Luangsodsai, A., & Sinapiromsaran, K. R. U. N. G. (2020). Self-Identification ResNet-ARIMA Forecasting Model. WSEAS transactions on systems and control, 15(21), 196-211.
Khanarsa, P., & Sinapiromsaran, K. (2017, February). Multiple ARIMA subsequences aggregate time series model to forecast cash in ATM. In 2017 9th International Conference on Knowledge and Smart Technology (KST) (pp. 83-88). IEEE.
