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Rig Das

Assistant Professor
Computer Science & Computer Engineering
University of Wisconsin-La Crosse

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Specialty area(s)

Brain Computer Interface (BCI), Biometrics, AI

Brief biography

Dr. Rig Das presently holds the position of Assistant Professor in the Computer Science and Computer Engineering Department at the University of Wisconsin, La Crosse (UWL) in Wisconsin, USA. Prior to joining UWL, he served as an Instructor and Research Scientist in the Department of Neurosurgery at the University of Nebraska Medical Center (UNMC) from 2021 to 2023. Preceding his tenure at UNMC, Dr. Das worked as a Postdoctoral Researcher at both the Technical University of Denmark (DTU) in Copenhagen, Denmark, and the University of Luxembourg in Luxembourg.

Dr. Das completed his Ph.D. in Applied Electronics Engineering with the European Doctorate Label from Roma Tre University in Rome, Italy, in April 2018. During his academic journey, he also worked as a visiting researcher at Bar-Ilan University in Israel in 2016.

Dr. Das's current research interests encompass a diverse range of topics, including EEG Signal Processing, Sleep Study, Deep Brain Stimulation (DBS), Brain-Computer Interfaces (BCI), and Deep Learning. As a Doctoral Fellow, he made significant contributions to the field of physiological biometric traits, including EEG signal analysis, Finger-vein recognition, and Facial recognition. In addition to these areas, Dr. Das also explores research avenues in image and video processing, pattern recognition, and AI.

Current courses at UWL

CS-202: Introduction to Web Design

CS-421: Programming Language Concepts 


2018 - Ph. D. in Applied Electronics Engineering - Roma Tre University, Rome, Italy

2012 - M.Tech. in Computer Science & Engineering - North Eastern Regional Institute of Science and Technology (NERIST), India

2007 - B.Tech. in Computer Science & Engineering - West Bengal University of Technology (WBUT), India


Professional history

1. 12/2021 - 07/2023 - Instructor & Research Scientist - University of Nebraska Medical Center (UNMC), Omaha, NE, USA.

2. 08/2019 - 10/2019 - Senior Research Scientist - GN Audio A/S, Denmark

3. 06/2019 - 05/2021 - Post Doctoral Researcher - Technical University of Denmark (DTU), Copenhagen, Denmark.

4.. 07/2018 - 04/2019 - Post Doctoral Research Associate - University of Luxembourg, Luxembourg

4. 07/2012 - 04/2013 - Assistant Professor - Assam Don Bosco University, India

5. 12/2007 - 07/2010 - Programmer Analyst - Cognizant Technology Solutions, India Pvt. Ltd.


  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (2018-23),
  • IEEE Transactions on Biometrics, Behavior, and Identity Science (TBIOM) (2019-23),
  • IEEE Transactions on Information Forensics and Security (TIFS) (2019-23),
  • IEEE Transactions on Image Processing (TIP) (2020-23),
  • IEEE ICIP (2016-19), IEEE EUSIPCO (2017-23).
  • Elsevier Signal Processing: Image Communication (2017-20),
  • Elsevier Visual Communication and Image Representation (2017-20).

Research and publishing

Research Interests: EEG Signal Processing, Biometrics, BCI, Deep Learning, Image and Video Processing, Medical Image Processing, Signal Processing, Steganography, AI.


Peer-reviewed Journals:

1. LC. West, MO. Summers, S Tang, L Hirt, CH. Halpern, D. Maroni, R. Das, SV. Gliske, A. Abosch, CA. Kushida, JA. Thompson, "Evaluation of consensus sleep stage scoring of dysregulated sleep in Parkinson's disease", Sleep Medicine, Vol. 107, 2023, PP. 236-242, ISSN 1389-9457,

2. M. A. Khan, B. M. Saibene, R. Das, I. Brunner and S. Puthusserypady, “Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review”, Journal of Neural Eng. 18 061003, Dec 2021.

3. S. Mahpod, R. Das, E. Maiorana, Y. Keller and P. Campisi, “Facial Landmarks Localization using Cascaded Neural Networks”, Elsevier Journal for Computer Vision and Image Understanding, Volume 205, 103171, Feb 2021, ISSN 1077-3142, 

4. M. A. Khan, R. Das, H. K. Iversen, S. Puthusserypadya “Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application”, Elsevier Journal for Computers in Biology and Medicine, Volume 123, PP. 103843, 2020.

5. R. Das, E. Piciucco, E. Maiorana and P. Campisi, “Convolutional Neural Network for Finger-Vein based Biometric Identification”, IEEE Transaction for Information Forensics and Security (IEEE TIFS). Vol. 14, Issue 2, PP. 360-373, 2019.

6. R. Das, E. Maiorana and P. Campisi, “EEG Biometrics Using Visual Stimuli: a Longitudinal Study”, IEEE Signal Processing Letters Vol. 23 (3), pp. 341-345, 2016.

7. R. Das, R. Dash and B. Majhi, “Hyperspectral Image Classification Based on Quadratic Fisher’s Discriminant Analysis and Multi-class Support Vector Machine”, IETE Journal of Research. Vol. 60 (6), pp. 406-413, 2014.

8. E. Ahmed, A. Saint, Abd El R. Shabayek, K. Cherenkova, R. Das, G. Gusev, D. Aouada, B. Ottersten, “Deep Learning Advances on Different 3D Data Representations: A Survey”, arXiv Preprint Computer Vision. 1808.01462, 2019.

Peer-reviewed Conferences:

1. C1: A. E. Voinas, R. Das, M. A. Khan, I. Brunner and S. Puthusserypady, "Motor Imagery EEG Signal Classification for Stroke Survivors Rehabilitation," IEEE 10th International Winter Conference on Brain-Computer Interface (BCI), 2022, pp. 1-5, doi: 10.1109/BCI53720.2022.9734837, 2022.

2. C. Uyanik, M. Khan, R. Das, J. Hansen, and S. Puthusserypady,  “Brainy Home: A Virtual Smart Home and Wheelchair Control Application Powered by Brain Computer Interface,” In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIODEVICES, ISBN 978-989-758-552-4; ISSN 2184-4305, pages 134-141. DOI: 10.5220/0010785800003123, 2022.

3. M. A. Khan, B. M. Bayram, R. Das, and S. Puthusserypady, "Electromyography and Inertial Motion Sensors Based Wearable Data Acquisition System for Stroke Patients: A Pilot Study," IEEE 43rd Annual International Conference of the Engineering in Medicine & Biology Society (EMBC), 2021, Conference due on Oct 31 - Nov 4, 2021.

4. S. D. T. Olesen, R. Das, M. D. Olsson, M. A. Khan and S. Puthusserypady, "Hybrid EEG-EOG-based BCI system for Vehicle Control," 2021 9th International Winter Conference on Brain-Computer Interface (BCI), Gangwon, Korea (South), 2021, pp. 1-6, doi: 10.1109/BCI51272.2021.9385300.

5. R. Das, P. S. Lopez, M. Ahmed Khan, H. K. Iversen and S. Puthusserypady, "FBCSP and Adaptive Boosting for Multiclass Motor Imagery BCI Data Classification: A Machine Learning Approach," 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Toronto, ON, 2020, pp. 1275-1279, doi: 10.1109/SMC42975.2020.9283098.

6. R. Das, E. Maiorana and P. Campisi, "Motor Imagery for EEG Biometrics Using Convolutional Neural Network," 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, 2018, pp. 2062-2066.

7. R. Das, E. Maiorana, and P. Campisi, “Visually Evoked Potentials for EEG Biometrics Using Convolutional Neural Network”, 25th European Signal Processing Conference (EUSIPCO) IEEE, Kos Island, Greece, Aug 28 – Sept 2, 2017.

8. R. Das, E. Piciucco, E. Maiorana, and P. Campisi, “Visually Evoked Potentials for EEG Biometric Recognition”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), Aalborg, Denmark, July 6 - 8, 2016.

9. R. Das, E. Maiorana, D. La Rocca and P. Campisi, “EEG Biometrics for User Recognition Using Visually Evoked Potentials”, In 14th IEEE International Conference of the Biometrics Special Interest Group (BIOSIG), Sept, 2015, pp. 1-8.

10. R. Das, T. Tuithung, "A Review on "A Novel Technique for Image Steganography Based on Block-DCT and Huffman Encoding"", 4th International Conference on Computer Graphics and Image Processing, ICGIP–2012, 06-07 OCT, Singapore, Proceedings on SPIE Conference Proceeding. DOI: 10.1117/12.2009430.

11. R. Das, T. Tuithung, "A Novel Steganography Method for Image Based on Huffman Encoding", 3rd IEEE National Conference on Emerging Trends and Applications in Computer Science (NCETACS - 2012, India).  DOI:  10.1109/NCETACS.2012.6203290.

Book Chapters:

1. M. A. Khan, R. Das, J. P. Hansen, S. Puthusserypady, " Brain and Behavior Computing: EEG-Based BCI Systems for Neurorehabilitation Applications", ISBN 9780367552978, CRC Press, June 24, 2021.

2. B. Choudhury, R. Das, A. Baruah, “A Novel Steganalysis Method based on Histogram Analysis", in Advanced Computer and Communication Engineering Technology. Vol. 315, pp. 779-789, 2015, Springer LNEE Series.

3. B. Choudhury, R. Das, T. Tuithung, “A Novel Method for Distributed Image Steganography”, In Advanced Computer and Communication Engineering Technology. Vol. 315, pp. 615-625, 2015, Springer LNEE Series.

4. R. Koikara, D. Deka, M. Gogoi, R. Das, "A Novel Distributed Image Steganography Method based on Block-DCT", In Advanced Computer and Communication Engineering Technology. Vol. 315, pp. 423-435, 2015, Springer LNEE Series.


1. First prize winner for European Biometrics Research Award 2018 for the PhD thesis entitled “Biometric Recognition using Deep Learning”, Darmstadt, Germany 26-Sept, 2018.

2. Finalist of 3MT PhD Thesis presentation at EUSIPCO 2017, Kos Island, Greece, 28-Aug to 02-Sept, 2017. 

Memberships & affiliations