Tamoghna Roy

ML@DeepSig | Applied Research | Deep Learning

Education

Virginia Polytechnic Institute and State University

Ph.D., Electrical Engineering / December, 2017

Blacksburg, Virginia, United States of America

Virginia Polytechnic Institute and State University

M.S., Electrical Engineering / December, 2014

Blacksburg, Virginia, United States of America

Jadavpur University

B.E., Electrical Engineering / June, 2009

Kolkata

Experience

DeepSig Inc.

Principal Engineer, Machine Learning / February, 2018Present

Building Machine Learning Solutions for Wireless Communication problems

Publications

Over-the-Air Deep Learning Based Radio Signal Classification

IEEE Journal of Selected Topics in Signal Processing / Feb 01, 2018

O’Shea, T. J., Roy, T., & Clancy, T. C. (2018). Over-the-Air Deep Learning Based Radio Signal Classification. IEEE Journal of Selected Topics in Signal Processing, 12(1), 168–179. https://doi.org/10.1109/jstsp.2018.2797022

Physical Layer Communications System Design Over-the-Air Using Adversarial Networks

2018 26th European Signal Processing Conference (EUSIPCO) / Sep 01, 2018

Oshea, T. J., Roy, T., West, N., & Hilburn, B. C. (2018). Physical Layer Communications System Design Over-the-Air Using Adversarial Networks. 2018 26th European Signal Processing Conference (EUSIPCO). https://doi.org/10.23919/eusipco.2018.8553233

Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks

2019 International Conference on Computing, Networking and Communications (ICNC) / Feb 01, 2019

O’Shea, T. J., Roy, T., & West, N. (2019). Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks. 2019 International Conference on Computing, Networking and Communications (ICNC). https://doi.org/10.1109/iccnc.2019.8685573

Learning robust general radio signal detection using computer vision methods

2017 51st Asilomar Conference on Signals, Systems, and Computers / Oct 01, 2017

O’Shea, T., Roy, T., & Clancy, T. C. (2017). Learning robust general radio signal detection using computer vision methods. 2017 51st Asilomar Conference on Signals, Systems, and Computers. https://doi.org/10.1109/acssc.2017.8335463

Spectral detection and localization of radio events with learned convolutional neural features

2017 25th European Signal Processing Conference (EUSIPCO) / Aug 01, 2017

O’Shea, T. J., Roy, T., & Erpek, T. (2017). Spectral detection and localization of radio events with learned convolutional neural features. 2017 25th European Signal Processing Conference (EUSIPCO). https://doi.org/10.23919/eusipco.2017.8081223

Demonstrating Deep Learning Based Communications Systems Over the Air In Practice

2018 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) / Oct 01, 2018

O’Shea, T. J., Roy, T., West, N., & Hilburn, B. C. (2018). Demonstrating Deep Learning Based Communications Systems Over the Air In Practice. 2018 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN). https://doi.org/10.1109/dyspan.2018.8610491

Generative Adversarial Radio Spectrum Networks

Proceedings of the ACM Workshop on Wireless Security and Machine Learning / May 15, 2019

Roy, T., O’Shea, T., & West, N. (2019). Generative Adversarial Radio Spectrum Networks. Proceedings of the ACM Workshop on Wireless Security and Machine Learning. https://doi.org/10.1145/3324921.3328782

A word-space visualization approach to study college of engineering mission statements

2017 IEEE Frontiers in Education Conference (FIE) / Oct 01, 2017

Bhaduri, S., & Roy, T. (2017). A word-space visualization approach to study college of engineering mission statements. 2017 IEEE Frontiers in Education Conference (FIE). https://doi.org/10.1109/fie.2017.8190704

A Wideband Signal Recognition Dataset

2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) / Sep 27, 2021

West, N., O’Shea, T., & Roy, T. (2021). A Wideband Signal Recognition Dataset. 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). https://doi.org/10.1109/spawc51858.2021.9593265

Demonstrating Use of Natural Language Processing to Compare College of Engineering Mission Statements

2017 ASEE Annual Conference & Exposition Proceedings

Bhaduri, S., & Roy, T. (n.d.). Demonstrating Use of Natural Language Processing to Compare College of Engineering Mission Statements. 2017 ASEE Annual Conference & Exposition Proceedings. https://doi.org/10.18260/1-2--28102

Power Measurement Based Code Classification for Programmable Logic Circuits

2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) / Dec 01, 2018

Roy, T., & Beex, A. A. L. (2018). Power Measurement Based Code Classification for Programmable Logic Circuits. 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). https://doi.org/10.1109/isspit.2018.8642680

BER modeling for interference canceling FIR Wiener equalizer

2013 International Conference on Computing, Networking and Communications (ICNC) / Jan 01, 2013

Roy, T., & Beex, A. A. (2013). BER modeling for interference canceling FIR Wiener equalizer. 2013 International Conference on Computing, Networking and Communications (ICNC). https://doi.org/10.1109/iccnc.2013.6504095

A Semester Like No Other: Use of Natural Language Processing for Novice-Led Analysis on End-of-Semester Responses on Students’ Experience of Changing Learning Environments Due to COVID-19

2021 ASEE Virtual Annual Conference Content Access Proceedings

Bhaduri, S., Soledad, M., Roy, T., Murzi, H., & Knott, T. (n.d.). A Semester Like No Other: Use of Natural Language Processing for Novice-Led Analysis on End-of-Semester Responses on Students’ Experience of Changing Learning Environments Due to COVID-19. 2021 ASEE Virtual Annual Conference Content Access Proceedings. https://doi.org/10.18260/1-2--36609

Polarization consideration in characterizing radio wave propagation in urban microcellular channels

11th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. PIMRC 2000. Proceedings (Cat. No.00TH8525)

El-Sallabi, H. M. (n.d.). Polarization consideration in characterizing radio wave propagation in urban microcellular channels. 11th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. PIMRC 2000. Proceedings (Cat. No.00TH8525). https://doi.org/10.1109/pimrc.2000.881458

MSE Analysis of Bi-scale LMS Used for Narrowband Interference Cancellation

2020 IEEE Latin-American Conference on Communications (LATINCOM) / Nov 18, 2020

Roy, T., Ikuma, T., & Louis Beex, A. A. (2020). MSE Analysis of Bi-scale LMS Used for Narrowband Interference Cancellation. 2020 IEEE Latin-American Conference on Communications (LATINCOM). https://doi.org/10.1109/latincom50620.2020.9282346

Links & Social Media

Research Interests

Machine Learning
Statistical Signal Processing
Deep Learning
Electrical and Electronic Engineering
Signal Processing
Join Tamoghna on NotedSource!

At NotedSource, we believe that professors, post-docs, scientists and other researchers have deep, untapped knowledge and expertise that can be leveraged to drive innovation within companies. NotedSource is committed to bridging the gap between academia and industry by providing a platform for collaboration with industry and networking with other researchers.

For industry, NotedSource identifies the right academic experts in 24 hours to help organizations build and grow. With a platform of thousands of knowledgeable PhDs, scientists, and industry experts, NotedSource makes connecting and collaborating easy.

For academic researchers such as professors, post-docs, and Ph.D.s, NotedSource provides tools to discover and connect to your colleagues with messaging and news feeds, in addition to the opportunity to be paid for your collaboration with vetted partners.

Expert Institutions
NotedSource has experts from Stanford University
Expert institutions using NotedSource include Oxfort University
Experts from McGill have used NotedSource to share their expertise
University of Chicago experts have used NotedSource
MIT researchers have used NotedSource
Proudly trusted by
Microsoft uses NotedSource for academic partnerships
Johnson & Johnson academic research projects on NotedSource
ProQuest (Clarivate) uses NotedSource as their industry academia platform
Slamom consulting engages academics for research collaboration on NotedSource
Omnicom and OMG find academics on notedsource
Phoenix Tailings finds academic collaborations on NotedSource
Unilever research project have used NotedSource to engage academic experts

Connect with researchers and scientists like Tamoghna Roy on NotedSource to help your company with innovation, research, R&D, L&D, and more.