CV

Education

• Ph.D in Information Science and Technology

  Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand

  August 2017 - October 2023

• Visiting Ph.D researcher

  Biomed Group in Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven (KU Leuven), Leuven, Belgium

  January 2022 - November 2022

• B.S. in Pure Science Chemistry

  King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand

  August 2013 - May 2017

  First-Class Honors and Gold Medal in Chemistry.

Work experience

• Senior Data Scientist (Mar 2025 - present)

  Data Science & Data Engineering Unit, Gosoft (Thailand) Co., Ltd.

  • Recommendation System
  • Computer Vision
• Postdoctoral Researcher (Jan 2024 - Feb 2025)

  The School of Information Science and Technology (IST), Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand.

  • Conducting research on biomedical data such as EEG, EMG, and PPG
  • Focusing on research in the fields of motor imagery-based EEG classification, epileptic seizure-based EEG detection, and arousal detection during sleep using EEG, EOG, EMG, and PPG.
  • Mentoring three graduate students
• Mentor (Oct 2020)

  SCB Challenge '15, The Siam Commercial Bank, Thailand

  • Together with the INTERFACES team, organized workshops on basic Python, wearable devices, and machine learning for high school students.
  • Followed up and advised students to complete their projects.
• Mentor (Nov 2019)

  SCB Challenge '14, The Siam Commercial Bank, Thailand

  • Together with the INTERFACES team, organized workshops on basic Python, BCIs, UX, and UI design for high school students
• Internship (Jun 1st, 2016 – Sep 30, 2016)

  Utac Thai Company Limited, Bangkok, Thailand

  • Worked as a process engineer in process engineering section at the Engineering Department
• Research Assistant (Aug 2014 - Dec 2014)

  Chemistry Department, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

  • Investigated the synthesis of a chemical compound, named 2,2-dimethyl-2,3-dihydronaphtho[1,2-β]furan-4,5-dione.

Research experience

• Ph.D. Research (Aug 2017 - Oct 2023)

  (under the supervision of Associate Professor Theerawit Wilaiprasitporn)

  INTERFACES Group in the School of Information Science and Technology (IST), Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand.

  • Developed MIN2Net, an end-to-end neural network utilizing 2-dimensional convolutional neural networks (2D-CNNs) for classifying imagined left and right-hand movements from brain signals (EEG), incorporating a multi-task autoencoder with deep metric learning (DML) and optimizing reconstruction, cross-entropy, and triplet loss functions to preserve discriminative brain signal representations.
  • Developed machine learning approaches, including support vector machine (SVM), random forest (RF), and k-nearest neighbors (kNN) to classify music preferences using brain responses (EEG) and heart responses (ECG), effectively predicting whether a listener favored or did not favor a song (Top 200 weekly chart of Thailand from renowned music streaming as Spotify).
  • Developed a support vector machine (SVM) model to accurately classify human movements based on brain signals during imagined sit-to-stand and stand-to-sit transitions, demonstrating advanced machine learning applications in BCI technology.
  • Developed a machine learning approach for brain-computer interfaces (BCIs) that simultaneously estimates frequency and amplitude modulations of brain signals (SSVEPs) using filter bank canonical correlation analysis (FBCCA) and support vector regression (SVR), enhancing control for neuromuscular patients.
• Visiting Ph.D. Research (Jan 2022 - Nov 2022)

  (under the supervision of Professor Maarten De Vos)

  Biomed Group in Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven (KU Leuven), Leuven, Belgium

  • Developed an advanced deep learning architecture for detecting seizure events in epilepsy patients, focusing on identifying anomaly events (seizure) in brain responses.
  • Explored strategies for handling imbalanced brain signals in epileptic seizure detection.
• B.S. Research (Aug 2013 - May 2017)

  (under the supervision of Dr. Boonnak Sukhummek)

  Chemistry Department, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

  • Resolved the “delamination” issue in the integrated circuit.
  • Investigated the plating process, examining the concentration of the chemical solution and the current density.
  • Familiarized myself with the assembly process of integrated circuits, particularly QFN (Quad Flat No-Lead) technology.
• Research Assistant Project (Aug 2014 - Dec 2014)

  Chemistry Department, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

  • Together with Dr. Kriangsak Khownium explored the synthesis of a chemical compound, named 2,2-dimethyl-2,3-dihydronaphtho[1,2-β]furan-4,5-dione.

Skills

• Skilled in Python, MySQL, and MATLAB.
• Proficient with deep learning and machine learning tools like TensorFlow, PyTorch, Scikit-learn, MNE, and EEGLAB.
• Experienced with Conda, Docker, GitHub for version control and Object-Oriented Programming (OOP).
• Familiar with data visualization tools like Tableau and Google Data Studio.
• Experienced with transfer learning, unsupervised learning, supervised learning, and multi-task learning
• Specialized in processing and visualizing bio-signals, such as EEG, EMG, ECG, and PPG.
• Extensive experience with BCI devices, including g.HIAMP, g.USBAMP, OpenBCI, and the MUSE EEG headband.
• Experienced with various public EEG datasets and advanced EEG classification models.
• Skilled in setting up experiments for bio-signal recording and writing IRB proposals.
• Experienced in mentoring high school, undergraduate, and doctoral students in research methods.

Scholarships

• Graduate study
  • Received a Ph.D. full scholarship from PTT Public Company Limited and The Siam Commercial Bank
• Undergraduate study
  • Received merit scholarships from King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand.

Publications

AlphaGrad: Normalized Gradient Descent for Adaptive Multi-loss Functions in EEG-based Motor Imagery Classification

R. Chaisaen^*, P. Autthasan^*, A. Ditthapron and T. Wilaiprasitporn, "AlphaGrad: Normalized Gradient Descent for Adaptive Multi-loss Functions in EEG-based Motor Imagery Classification" in IEEE Journal of Biomedical and Health Informatics, Early Access

MotionXpert: EMG-Based Classification for Optimized Lower-Limb Motion Detection

P. Mitsantisuk, S. Kiatthaveephong, P. Autthasan and T. Wilaiprasitporn, "MotionXpert: EMG-Based Classification for Optimized Lower-Limb Motion Detection" in 2024 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), Penang, Malaysia, 2024, pp. 1-6.

TSeizNet: Triplet Loss Empowered Multi-Scale CNN for Superior EEG Seizure Detection

W. Polpakdee, P. Autthasan and T. Wilaiprasitporn, "TSeizNet: Triplet Loss Empowered Multi-Scale CNN for Superior EEG Seizure Detection" in 2024 IEEE SENSORS, Kobe, Japan, 2024, pp. 1-4.

ResSense: A Modern Pipeline for Respiratory Arousal Detection Using PPG Signals

N. Soontreekulpong, P. Autthasan, T. Kaewlee, W. Worawitayanon, T. Choksatchawathi, N.Jaimchariyatam, B. Chaitusaney and T. Wilaiprasitporn, "ResSense: A Modern Pipeline for Respiratory Arousal Detection Using PPG Signals" in 2024 IEEE SENSORS, Kobe, Japan, 2024, pp. 1-4.

MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG Classification

P. Autthasan^*, R. Chaisaen^*, H. Phan, M. D. Vos and T. Wilaiprasitporn, "MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG Classification" in IEEE Internet of Things Journal, vol. 11, no. 17, pp. 28539-28554, 1 September, 2024.

HeartRhythm: ECG-Based Music Preference Classification in Popular Music

P. Autthasan, P. Sukontaman, T. Wilaiprasitporn and S. Sangnark, "HeartRhythm: ECG-Based Music Preference Classification in Popular Music" in 2023 IEEE SENSORS, Vienna, Austria, 2023, pp. 1-4.

ANet: Autoencoder-Based Local Field Potential Feature Extractor for Evaluating an Antidepressant Effect in Mice After Administering Kratom Leaf Extracts

J. Nukitram, W. Saengmolee, R. Chaisaen, P. Autthasan, N. Sengnon, J. Wungsintaweekul, D. Cheaha, E. Kumarnsit, T. Sudhawiyangkul, and T. Wilaiprasitporn, "An Effect of Limb Position in Motor Imagery Training Paradigm in Immersive Virtual Environment" in IEEE Transactions on Biomedical Circuits and Systems, vol. 17, no. 1, pp. 67-76, Feb. 2023.

Consumer-Grade Brain Measuring Sensor in People With Long-Term Kratom Consumption

W. Saengmolee, R. Chaisaen, P. Autthasan, C. Rungsilp, N. Sa-Ih, D. Cheaha, E. Kumarnsit, and T. Wilaiprasitporn, "Consumer-Grade Brain Measuring Sensor in People With Long-Term Kratom Consumption" in IEEE Sensors Journal, vol. 22, no. 6, pp. 6088-6097, 15 March, 2022.

MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification

P. Autthasan^*, R. Chaisaen^*, T. Sudhawiyangkul, P. Rangpong, S. Kiatthaveephong, N. Dilokthanakul, G. Bhakdisongkhram, H. Phan, C. Guan, and T. Wilaiprasitporn, "MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification," in IEEE Transactions on Biomedical Engineering, vol. 69, no. 6, pp. 2105-2118, June 2022.

EEGWaveNet: Multiscale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection

P. Thuwajit, P. Rangpong, P. Sawangjai, P. Autthasan, R. Chaisaen,</b> N. Banluesombatkul, P. Boonchit, N. Tatsaringkansakul, T. Sudhawiyangkul, and T. Wilaiprasitporn, "EEGWaveNet: Multiscale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection," in IEEE Transactions on Industrial Informatics, vol. 18, no. 8, pp. 5547-5557, Aug. 2022.

A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition

S. Kongwudhikunakorn, S. Kiatthaveephong, K. Thanontip, P. Leelaarporn, M. Piriyajitakonkij, T. Charoenpattarawut, P. Autthasan, R. Chaisaen, P. Dujada, T. Sudhawiyangkul, V. Senanarong, and T. Wilaiprasitporn, "A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition," in IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-10, 2021.

Revealing preference in popular music through familiarity and brain response

S. Sangnark, P. Autthasan, P. Ponglertnapakorn, P. Chalekarn, T. Sudhawiyangkul, M. Trakulruangroj, S. Songsermsawad, R. Assabumrungrat, S. Amplod, K. Ounjai and T. Wilaiprasitporn, "Revealing Preference in Popular Music Through Familiarity and Brain Response" in IEEE Sensors Journal, vol. 21, no. 13, pp. 14931-14940, 1 July, 2021.

Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and Sitting

R. Chaisaen^*, P. Autthasan^*, N. Mingchinda, P. Leelaarporn, N. Kunaseth, S. Tammajarung, P. Manoonpong, S. C. Mukhopadhyay, and T. Wilaiprasitporn., "Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and Sitting," in IEEE Sensors Journal, vol. 20, no. 22, pp. 13776-13786, 15 Nov.15, 2020.

A single-channel consumer-grade EEG device for brain–computer interface: Enhancing detection of SSVEP and its amplitude modulation

P. Autthasan, X. Du, J. Arnin, S. Lamyai, M. Perera, S. Itthipuripat, T. Yagi, P. Manoonpong and T. Wilaiprasitporn, "A single-channel consumer-grade EEG device for brain–computer interface: Enhancing detection of SSVEP and its amplitude modulation" in IEEE Sensors Journal, vol. 20, no. 6, pp. 3366-3378, 15 March, 2020.

Drowsiness detection for office-based workload with mouse and keyboard data

S. Natnithikarat, S. Lamyai, P. Leelaarporn, N. Kunaseth, P. Autthasan, T. Wisutthisen and T. Wilaiprasitporn, "Drowsiness Detection for Office-based Workload with Mouse and Keyboard Data" in 2019 12th Biomedical Engineering International Conference (BMEiCON), Ubon Ratchathani, Thailand, 2019, pp. 1-4.

Towards asynchronous motor imagery-based brain-computer interfaces: a joint training scheme using deep learning

P. Cheng, P. Autthasan, B. Pijarana, E. Chuangsuwanich and T. Wilaiprasitporn, "Towards Asynchronous Motor Imagery-Based Brain-Computer Interfaces: a joint training scheme using deep learning" in TENCON 2018 - 2018 IEEE Region 10 Conference, Jeju, Korea (South), 2018, pp. 1994-1998.

^* Equal contributions