|Justin Dauwels is an Assistant Professor with School of Electrical & Electronic Engineering at Nanyang Technological University (NTU). His research interests are in Bayesian statistics, iterative signal processing, and computational neuroscience. He enjoys working on real-world problems, often in collaboration with medical practitioners. He also tries to bring real-world problems into the classroom.|
Prior to joining NTU, Justin was a research scientist during 2008-2010 in the Stochastic Systems Group (SSG) at the Massachusetts Institute of Technology, led by Prof. Alan Willsky. He received postdoctoral training during 2006-2007 under the guidance of Prof. Shun-ichi Amari and Prof. Andrzej Cichocki at the RIKEN Brain Science Institute in Wako-shi, Japan.
He obtained a PhD degree in electrical engineering at the Swiss Polytechnical Institute of Technology (ETH) in Zurich in December 2005, supervised by Prof. Hans-Andrea Loeliger, and was a teaching and research assistant at the Signal and Information Processing Laboratory (ISI) of the Department of Information Technology and Electrical Engineering at ETH Zurich from 2000 to 2005. In 2000 he received the engineering physics degree from the University of Ghent. From 1999 to 2000, he was an exchange student at ETH, and completed his master's thesis at the Institute of Neuroinformatics in Zurich.
Justin was a visiting researcher at the MIT Media Lab (Physics and Media Group) in Fall 2003 and the University of Ghent (Digital Communications Research Group) in January 2004. In Spring 2004 he was an intern at the Mitsubishi Electric Research Lab (Cambridge, MA) under supervision of Dr. Jonathan Yedidia.
He has been a JSPS postdoctoral fellow (2007), a BAEF fellow (2008), a Henri-Benedictus Fellow of the King Baudouin Foundation (2008), and a JSPS invited fellow (2010).
He is a member of the IEEE and the IMS. He is a research affiliate with Stochastic Systems Group (SSG) at the Massachusetts Institute of Technology, the Neurology Department at Massachusetts General Hospital, and the RIKEN Brain Science Institute.
- Automated Seizure Onset Zone Determination from Interictal EEG
- Behavior and Neurophysiological Study of Subliminal Priming in the Realm of Advertisement and Beyond
- Compressed Sensing for GMTI Applications
- Computationally Predicting Transcriptionally Regulated Protein Kinases
- Develop Multi-way Analysis Methods to Coping With Missing Data in Medical Questionnaires
- Hierarchical Bayesian Models for Time-Lapse Images of Cell Migration
- Monitoring of Group Discussion: A Socio-Engineering Approach
- Multi-way Analysis of Electroencephalograms of Alzheimer's Disease Patients (AD), with the Aim of Improving Early Diagnosis of AD
- NTU-MGH Programme on Clinical Neurotechnologies
- Real-Time Big Data Analytics Based New Paradigm in Internet of Things
- Real-Time On-Demand Route Guidance in Dynamic Urban Transportation Networks
- Parmod Kumar, Faisal Mahmood, Ken Wong, Abhishek Agrawal, Mohammad Elgendi, Srinivasan Kannan, Dhanya Menoth Mohan, Rohit Shukla, Dauwels Justin, and Alice H.D. Chan. (2013). Inferring subliminal primes from EEG through machine learning. 35th Annual International IEEE EMBS Conference.
- Justin Dauwels and Srinivasan Kannan. (2013). Towards compressed sensing for ground-to-air monostatic radar. 3rd SONDRA workshop on EM modeling, new concepts and signal processing for radar detection and remote sensing.
- K. Srinivasan, J. Dauwels, M. Ramasubba R. (2013). Multichannel EEG compression: Wavelet-based image and volumetric coding approach. IEEE Journal of Biomedical and Health informatics, 17(1), 113-120.
- M. Elgendi, J. Dauwels, B. Rebsamen, R. Shukla, Y. Putra, J. Gamez, Niu ZePing, Bangying Ho, N. Prasad, D. Aggarwal, A. Nair, V. Mishuhina, F. Vialatte, M. Constable, A. Cichocki, C. Latchoumane, J. Jeong, D. Thalmann, and N. Magnenat-Thalmann. (2013). From Auditory and Visual to Immersive Neurofeedback: Application to Diagnosis of Alzheimer's Disease. Neural Computation, Neurodevices, and Neural Prosthesis, .
- M.A. Vazquez, Jing Jin, J. Dauwels, F.B. Vialatte. (2013). Automated Detection of Paroxysmal Gamma Waves in Meditation EEG. ICASSP.