Welcome to my homepage.
I am an Experiential AI Postdoc of Roux Institute at Northeastern University. I work at Next Generation Networks and Systems (GENESYS) lab, directed by Prof. Kaushik Roy Chowdhury. I received my PhD degree in Computer Science under the supervision of Dr. Mainak Chatterjee in Spring 2020 from Department of Computer Science, University of Central Florida. I also received Master of Sceience (Spring 2018) in Computer Science from the same University.
Present: Multimodal Data Fusion, Beam Selection and Channel Estimation in mmWave band, NextG Communication.
Past: Radio Frequency Machine Learning Systems (RFMLs), Generative Adversarial Nets, Real-time Video Transmission, Vehicular Netwroks, Heterogeneous Networks, Modeling and Simulation, Dynamic Spectrum Access.
Tathagata Mukherjee, Eduardo Pasiliao,Debashri Roy, Alec Riden, Jared Paquet , GANSAT: A GAN and SATellite Constellation Signal-based Framework for Detecting GPS Spoofers , (U.S. Patent 2020, November), Status: Provisional Patent Application (63/086, 126).
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, Transmitter Identification Using Adversarial Networks and IQ Data , (U.S. Patent 2020, March), Status: Provisional Patent Application (62/993, 748).
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Erik Blasch, Eduardo Pasiliao, Adversarial Learning for RF Transmitter Identification and Classification , (U.S. Patent 2020, March), Status: Provisional Patent Application (62/993, 751).
Debashri Roy, Tathagata Mukherjee, Eduardo Pasiliao, Exploiting Spatio-temporal Correlation in RF Data using Deep Learning , In Deep Learning Applications, Volume 2, Springer, 2021.
Chandan Bandyopadhyay, Shalini Parekh, Debashri Roy, Hafizur Rahaman, Improving the Designs of ESOP-Based Reversible Circuits , In Design and Testing of Reversible Logic, pp. 49–64, 2020.
Debashri Roy, Yuanyuan Li, Tong Jian, Peng Tian, Kaushik R. Chowdhury, Stratis Ioannidis, Multi-modality Sensing and Data Fusion for Multi-vehicle Detection , In IEEE Transactions on Multimedia, Jan 2022.
Mauro Belgiovine, Kunal Sankhe, Carlos Bocanegra, Debashri Roy, Kaushik R. Chowdhury, Deep Learning at the Edge for Channel Estimation in Beyond-5G Massive MIMO , In IEEE Wireless Communications Magazine, Feb 2021.
Muthukumaran Ramasubramanian, Chaity Banerjee, Debashri Roy, Tathagata Mukherjee, Eduardo Pasiliao, Exploiting Spatio-Temporal Properties of I/Q Signal Data using 3D Convolution for RF Transmitter Identification , In IEEE Journal of Radio Frequency Identification, Dec 2020.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, Adaptive Streaming of HD and 360 Degree Videos over Software Defined Radios , In Elsevier Pervasive and Mobile Computing, July 2020.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Erik Blasch, Eduardo Pasiliao, RFAL: Adversarial Learning for RF Transmitter Identification and Classification , In IEEE Transactions on Cognitive Communications and Networking, 2020.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Machine Learning in Adversarial RF Environments , In IEEE Communications Magazine, May 2019.
Debashri Roy, Mainak Chatterjee, Eduardo Pasiliao, Video Quality Assessment for Inter-Vehicular Streaming with IEEE 802.11p, LTE, and LTE Direct Networks over Fading Channels , In Elsevier Computer Communications, 2017.
Debashri Roy, Prasun Ghosal, Saraju P. Mohanty, FuzzRoute: A Thermally Efficient Congestion Free Global Routing Method for Three Dimensional Integrated Circuits , ACM Transactions on Design Automation of Electronic Systems (TODAES), November 2015.
Batool Salehi, Jerry Gu, Debashri Roy , Kaushik Chowdhury, FLASH: Federated Learning for Automated Selection of High-band mmWave Sectors . In International Conference on Computer Communications (INFOCOM), 2022. [Accepted]
Guillem Reus-Muns, Batool Salehi, Debashri Roy , Tong Jian, Zifeng Wang, Jennifer Dy, Stratis Ioannidis, Kaushik Chowdhury, Deep Learning on Visual and Location Data for V2I mmWave Beamforming . In IEEE International Conference on Mobility, Sensing and Networking (MSN), 2021.
Alec Riden, Debashri Roy, Tathagata Mukherjee, Eduardo Pasiliao, DeePOE: Deep Learning for Position and Orientation Estimation . In IEEE Asia Pacific Conference on Communications (APCC), 2021.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, Defense against PUE Attacks in DSA Networks using GAN based Learning , IEEE Global Communications Conference (GLOBECOM), 2019.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, RF Transmitter Fingerprinting Exploiting Spatio-temporal Properties in Raw Signal Data. , IEEE International Conference on Machine Learning and Applications (ICMLA), 2019.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, Primary User Activity Prediction in DSA Networks Using Recurrent Structures , IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2019.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, Detection of Rogue RF Transmitters using Generative Adversarial Nets , IEEE Wireless Communications and Networking Conference (WCNC), 2019.
Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao, Adaptive Video Encoding and Dynamic Channel Access for Real-time Streaming over SDRs , IEEE International Performance Computing and Communications Conference (IPCCC), 2018. [Best Paper Runner-up Award]
Debashri Roy, Prasun Ghosal, Saraju P. Mohanty, Fuzzroute: A Method for Thermally Efficient Congestion Free Global Routing in 3D ICs , IEEE Computer Society Annual Symposium on VLSI(ISVLSI), 2014.
Debashri Roy, Prasun Ghosal, Nabanita Das, A Thermal and Congestion Driven Global Router for 3D Integrated Circuits , IEEE Students’ Technology Symposium(TechSym), 2014.
Debashri Roy, Prasun Ghosal Fuzzified Approach towards Global Routing in VLSI Layout Design , IEEE International Conference on Fuzzy Systems (FUZZ), 2013.
Supervisor: Dr. Kaushik Chowdhury.
Project: RF Antenna Pose and Range Estimation using Deep Learning.
Project: Radio Frequency Machine Learning.
Project: Detection of Rogue Transmitter in RFML System for Vehicular Networks.
Project: Channel Adaptive Real-time Video Steaming over DSA.
Areas: LVC (Live Virtual Constructive) Networks - Modeling and Simulation.
Courses Taught: Operating Systems(COP 4600), System Software (COP 3402), Computer Science II (COP 3503), Object Oriented Programming (COP 3330).
Project: Performance-centric Design Optimization in 3D Nanoscale Integrated Circuits and Systems.
Role: 2 years and 2 months of experience in Core Java, J2EE, Swing and Java EE based application development,and worked in four different projects.
Mentoring Disha Agarwal as part of women mentorship program (WeSupport) in Northeastern University, USA.
Mentored "NU Huskies" team (ranked 3rd) in ITU AI/ML in 5G Challenge ["Beam-selection" track], Northeastern University, USA.
Alec Riden from University of Alabama, Huntsville, USA, from Spring 2020 - Summer 2020. [Thanks to Dr. Tathagata Mukherjee]
Francisco Morales in Spring 2019 via L.E.A.R.N Undergraduate Research Program, BS in Information Technology, University of Central Florida.
Ngoc Nguyen in Spring 2019 via L.E.A.R.N Undergraduate Research Program, BS in Computer Science, University of Central Florida.