Skip to main content
Rady School of Management Rady School of Management
  1. HOME
  2. Faculty & Research
  3. Other Faculty
  4. Rady Adjunct Professor: Sujit Dey

Sujit Dey

Jacobs Family Chair in Management and Engineering Leadership, Adjunct Professor

Sujit Dey is a Professor in the Department of Electrical and Computer Engineering, the Director of the Center for Wireless Communications, and the Director of the Institute for the Global Entrepreneur at University of California, San Diego.  He heads the Mobile Systems Design Laboratory , developing innovative edge computing, multimedia networking, green communications, multi-modal sensor fusion, and deep learning algorithms and architectures to enable predictive personalized health, immersive multimedia, and smart transportation applications. He has created inter-disciplinary programs involving multiple UCSD schools as well as community, city and industry partners; notably the Connected Health Program in 2016 and the Smart Transportation Innovation Program in 2018. In 2017, he was appointed as an Adjunct Professor, Rady School of Management, and the Jacobs Family Endowed Chair in Engineering Management Leadership.

Dr. Dey served as the Faculty Director of the von Liebig Entrepreneurism Center from 2013-2015, and as the Chief Scientist, Mobile Networks, at Allot Communications from 2012-2013. He founded Ortiva Wireless in 2004, where he served as its founding CEO and later as CTO and Chief Technologist till its acquisition by Allot Communications in 2012. Prior to Ortiva, he served as the Chair of the Advisory Board of Zyray Wireless till its acquisition by Broadcom in 2004, and as an advisor to multiple companies including ST Microelectronics and NEC. Prior to joining UCSD in 1997, he was a Senior Research Staff Member at NEC C&C Research Laboratories in Princeton, NJ. He received his Ph.D. in Computer Science from Duke University in 1991.

Dr. Dey has co-authored more than 250 publications, and a book on low-power design. He holds 18 U.S. and 2 international patents, resulting in multiple technology licensing and commercialization. He has been a recipient of seven IEEE/ACM Best Paper Awards, and has chaired multiple IEEE conferences and workshops. Dr. Dey is a Fellow of the IEEE.

Connected Health
Green Computing and Communications
Mobile Cloud Computing
Predictive and Prescriptive Analytics
Smart Cities and Smart Transportation
Wireless Immersive Multimedia

2022

  • B. Kutukcu, S. Baidya, A. Raghunathan, and S. Dey. "Contention Grading and Adaptive Model Selection for Machine Vision in Embedded Systems", accepted in ACM Trans. Embedd. Comput. Syst.    PDF    ACM Digital Library

2021

  • S. Das, A. Miki, C. Blanchard, E. Sazonov, C. Gilhooly, S. Dey, C. Wolk, C. Khoo, J. Hill, R. Shook, “Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints”, Advances in Nutrition,  Oxford University Press on behalf of the American Society for Nutrition    Oxford Academic
  • Y. -J. Ku, S. Baidya and S. Dey, "Adaptive Computation Partitioning and Offloading in Real-Time Sustainable Vehicular Edge Computing," in IEEE Transactions on Vehicular Technology, vol. 70, no. 12, pp. 13221-13237, Dec. 2021    PDF    IEEE Xplore
  • Pohan Chiang, Melissa Wong and Sujit Dey, "Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure," accepted in Journal of Translational Engineering in Health and Medicine
  • Rutvik V. Shah, Gillian Grennan, Mariam Zafar-Khan, Fahad Alim, Sujit Dey, Dhakshin Ramanathan, Jyoti Mishra, "Personalized machine learning of depressed mood using wearables." Translational Psychiatry 11, Article number: 338, June 09 2021.    PDF    Nature
  • J. J. Leitner, P. -H. Chiang and S. Dey, "Personalized Blood Pressure Estimation Using Photoplethysmography: A Transfer Learning Approach," in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2021.3085526.    PDF    IEEE Xplore
  • J. Chen, S. Dey, L. Wang, N. Bi, P. Liu, "Multi-modal Fusion Enhanced Model for Driver's Facial Expression Recognition", 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021.    PDF
  • O. N. Tepencelik, W. Wei, L. Chukoskie, P. C. Cosman, S. Dey, "Body and Head Orientation Estimation with Privacy Preserving LiDAR Sensors", 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021.    PDF
  • B. Kutukcu, S. Baidya, A. Raghunathan, S. Dey, "Contention-aware Adaptive Model Selection for Machine Vision in Embedded Systems", in Proc. of 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS 2021), June 2021.    PDF    IEEE Xplore

2020

  • X. Hou and S. Dey, “Motion Prediction and Pre-Rendering at the Edge to Enable Ultra-Low Latency Mobile 6DoF Experiences,” IEEE Open Journal of the Communications Society, vol. 1, pp. 1674-1690, Oct. 2020.    PDF    IEEE Xplore
  • Y. -J. Ku, S. Sapra, S. Baidya and S. Dey, "State of Energy Prediction in Renewable Energy-driven Mobile Edge Computing using CNN-LSTM Networks," 2020 IEEE Green Energy and Smart Systems Conference (IGESSC), Long Beach, CA, 2020, pp. 1-7    pdf    IEEE Xplore
  • S. Thornton, S. Dey, “Machine Learning Techniques for Vehicle Matching with Non-Overlapping Visual Features,” IEEE 3rd Connected and Automated Vehicles Symposium (CAVS), November 2020.    pdf    IEEE Xplore
  • S. Baidya, Y. Ku, H. Zhao, J. Zhao, S. Dey, "Vehicular and Edge Computing for Emerging Connected and Autonomous Vehicle Applications", in Proc. of 2020 57th ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, 2020, pp. 1-6    pdf    IEEE Xplore
  • W. Wei, C. McElroy, S. Dey, "Using Sensors and Deep Learning to Enable On-Demand Balance Evaluation for Effective Physical Therapy," IEEE Access, vol. 8, pp. 99889-99899, May 2020.    IEEE Xplore
  • X. Hou, S. Dey, J. Zhang and M. Budagavi, “Predictive Adaptive Streaming to Enable Mobile 360-degree and VR Experiences,” IEEE Transactions on Multimedia, April 2020.    PDF    IEEE Xplore
  • Y. Ku, P. Chiang and S. Dey, "Real-Time QoS Optimization for Vehicular Edge Computing With Off-Grid Roadside Units," in IEEE Transactions on Vehicular Technology, vol. 69, no. 10, pp. 11975-11991, Oct. 2020    PDF    IEEE Xplore

2019

  • X. Hou, J. Zhang, M. Budagavi and S. Dey, "Head and Body Motion Prediction to Enable Mobile VR Experiences with Low Latency," in Proc. of the 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, Dec. 2019, pp. 1-7.    PDF    IEEE Xplore
  • P. Chiang and S. Dey, "Offline and Online Learning Techniques for Personalized Blood Pressure Prediction and Health Behavior Recommendations," in IEEE Access, vol. 7, pp. 130854-130864, 2019    IEEE Xplore
  • W. Wei, C. McElroy, S. Dey, "Towards On-Demand Virtual Physical Therapist: Machine Learning-Based Patient Action Understanding, Assessment and Task Recommendation," IEEE Transactions on Neural Systems & Rehabilitation Engineering, vol. 27, no. 9, pp. 1824-1835, September 2019.     PDF    IEEE Xplore
  • Y. Ku and S. Dey, “Sustainable Vehicular Edge Computing Using Local and Solar-Powered Roadside Unit Resources,” 2019 IEEE 90th Vehicular Technology Conference (VTC-Fall), Honolulu, HI, USA, Sep. 2019, pp. 1-7    pdf    IEEE Xplore
  • J. Leitner, P. Chiang and S. Dey, "Personalized Blood Pressure Estimation using Photoplethysmography and Wavelet Decomposition," 2019 IEEE International Conference on E-health Networking, Application & Services (HealthCom), 2019, pp. 1-6.    pdf
  • W. Wei, and S. Dey, "Center of Mass Estimation for Balance Evaluation Using Convolutional Neural Networks," Proceedings of the Seventh IEEE International Conference on Healthcare Informatics, Xi'an, China, June 2019, pp. 1-7.    PDF    IEEE Xplore

For Dr. Dey’s list of publications, please see http://esdat.ucsd.edu/publications.