Welcome!
Our lab is headed by Professor Sujit Dey, who is also the Director of UC San Diego Center for Wireless Communications, and the Director of the Institute for the Global Entrepreneur. Our research projects aim towards enabling preventive and personalized healthcare, mobile immersive multimedia experiences, and smart and clean transportation solutions, through innovations in multi-modal sensor fusion, deep learning algorithms and architectures, edge computing, multimedia networking, and sustainable communications.
Professor Dey 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.
News and Events
NASEM Presentation: A New Wave of Applications Enabled by 5G
Professor Sujit Dey presenting at the National Academies of Sciences (NASEM), Engineering, and Medicine.Using Personal Data to Predict Blood Pressure
Engineers at UC San Diego used wearable off-the-shelf technology and machine learning to predict, for the first time, an individual’s blood pressure and provide personalized recommendations to lower it based on this data...Pagination
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Latest Publications
A. Postlmayr, B. Garg, P. Cosman and S. Dey, "PersonalPT: One-shot approach for skeletal-based repetitive action counting for physical therapy" Elsevier Smart Health, vol. 34, Dec. 2024, https://doi.org/10.1016/j.smhl.2024.100516 Smart Health
B. Kutukcu, S. Baidya and S. Dey, "Fast and Scalable Design Space Exploration for Deep Learning on Embedded Systems," in IEEE Access, doi: 10.1109/ACCESS.2024.3475416 IEEE Xplore
J. Chen, S. Dey, L. Wang, N. Bi and P. Liu, "Attention-Based Multi-Modal Multi-View Fusion Approach for Driver Facial Expression Recognition," in IEEE Access, doi: 10.1109/ACCESS.2024.3462352. PDF IEEE Xplore
O. N. Tepencelik, W. Wei, P. C. Cosman and S. Dey, "Body and Head Orientation Estimation from Low-Resolution Point Clouds in Surveillance Settings,'' IEEE Access, vol. 12, pp. 141460-141475, 2024, DOI: 10.1109/ACCESS.2024.3469197. PDF IEEE Xplore
B. Kutukcu, S. Baidya, and S. Dey, ‘SLEXNet: Adaptive Inference Using Slimmable Early Exit Neural Networks’, ACM Trans. Embed. Comput. Syst., vol. 23, no. 6, Sep. 2024. https://doi.org/10.1145/3689632 ACM Digital Library
Our research includes developing new mobile cloud computing architectures and algorithms, media analytics and personalization techniques, adaptive cloud media delivery techniques, application aware green communication techniques that reduce power consumption of both mobile networks and devices, and hardware-software design technologies to ensure reliable, low-power, and variability tolerant systems.