About me
I am a lecturer at Mahidol University. My research interest is to train deep learning model end-to-end on large datasets, including time-series and images. I got my PhD in Computing Research from Imperial College London. During my PhD, I have developed deep learning models that can automate feature extraction process in biosignal analysis, especially EEG signals (i.e., brain activity). My PhD supervisor is Prof. Yike Guo, a director of Data Science Institute of Imperial College London.
Current Research Projects
2019 – Current: MU Young Researcher Grant: Transfer Learning in Sleep Stage Scoring (Role: Principal Investigator).
2019 – Current: U.Reka: Information Embedding-Retrieval of Re-recorded Video (Role: Deep Learning Expert).
Selected Publications
Journal Papers
Remote Monitoring in the Home Validates Clinical Gait Measures for Multiple Sclerosis
Akara Supratak, Gourab Datta, Arie R. Gafson, Richard Nicholas, Yike Guo and Paul M. Matthews
Frontiers in Neurology, 2018
Mixed Neural Network Approach for Temporal Sleep Stage Classification
Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M Matthews and Yike Guo
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
Akara Supratak, Hao Dong, Chao Wu and Yike Guo
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017
Conference and Workshop Papers
Towards Desynchronization Detection in Biosignals
Akara Supratak, Steffen Schneider, Hao Dong, Ling Li and Yike Guo
NIPS Time Series Workshop, 2017
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu and Yike Guo
ACM Multimedia, 2017 (Best Open source software)
Feature extraction with stacked autoencoders for epileptic seizure detection
Akara Supratak, Ling Li and Yike Guo
IEEE Engineering in Medicine and Biology Society (EMBC), 2014 (Oral Presentation)
Past Research Projects
2015 – 2017: Progressive MS Alliance: Novel Enabling Infrastructure for Outcomes Monitoring: Dynamic Remote Performance Capture to Assess Disability in Progressive Multiple Sclerosis [link] (Role: Lead Data Scientist).
2014 – 2015: Samsung GRO Award 2014: Deep Learning on Fused Brain and Heart Signals for Mental Disorder Detection Grant: Samsung GRO Award 2014 (Role: Lead Data Scientist).
Timeline
2013-2018: Imperial College London: Ph.D. in Computing Research. Adviser: Prof. Yike Guo.
2012-2013: Imperial College London: M.Sc. in Computing (Software Engineering).
2011-2012: Mahidol University: Assistant Instructor.
2007-2011: Mahidol University: B.Sc. in Information and Communication Technology (Computer Science).
Awards
2018: Think Disruptive from U ME IDEA U.Reka (Team: TinyEpicBrains) [link].
2018: Finalist of U.Reka program (Team: TinyEpicBrains) [link].
2017: Winner of Anglo-Thai Society Educational Award for Excellence 2017 in Engineering and Technology [link] [news].
2017: Best Open Source Software Award at ACM MM 2017 [link] [pdf].
2011: Full Scholarship for Young ICT Instructor Development from the Faculty of Information and Communication Technology, Mahidol University.
2011: Academic Excellence from the Faculty of Information and Communication Technology, Mahidol University.
2011: 2nd Place in Game Design, Imagine Cup 2011, New York, US.
2010: One of the six finalists in Game Design, Imagine Cup 2010, Warsaw, Poland.
2009: Honorable Mention, ACM-ICPC Asia Phuket Regional Programming Contest 2009, Phuket, Thailand.
2009: Two Honorable Mentions of PC and Console game category of SIPA Game Contest 2009.
Academic Experience
2013 – 2017: Teaching Assistant for several undergraduate and graduated courses, Imperial College London.
2016: Invited Speaker for the Revolutions in Biomedicine Summer Programme, Imperial College London.
2015: Invited Speaker for the short course in eHealth, Imperial College London.
2011: Instructor and Teaching Assistant for several undergraduate course, Mahidol University.