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Vaneet Aggarwal
Affiliation
Purdue University, West Lafayette, IN, USA
Topic
Reward Function,Base Station,Neural Network,Markov Decision Process,Network State,Deep Reinforcement Learning,Edge Server,Federated Learning,Generative Adversarial Networks,Global Model,Local Training,Machine Learning,Objective Function,State Space,Video Player,Attention Mechanism,Average Latency,Baseline Algorithms,Caching Scheme,Convolutional Neural Network,Data Rate,Deep Learning,Diffusion Model,High-level Policy,Imitation Learning,Internal Parameters,Live Streaming,Machine Learning Models,Maximum Likelihood Estimation,Mobile Network,Mobile Users,Policy Learning,Policy Network,Routing Decisions,Stochastic Gradient Descent,Streaming Platforms,Supplementary Material Online,Time Step,Train Machine Learning Models,Training Set,Variational Autoencoder,Video Playback,Video Quality,Video Segments,Actor Network,Adaptive Algorithm,Adversarial Inverse Reinforcement Learning,Arrival Rate,Artificial Neural Network,Average Transmission Rate,
Biography
Vaneet Aggarwal received the B.Tech. degree from the Indian Institute of Technology Kanpur, Kanpur, India, in 2005, and the M.A. and Ph.D. degrees from Princeton University, Princeton, NJ, USA, in 2007 and 2010, respectively, all in electrical engineering.
He is currently an Associate Professor with Purdue University, West Lafayette, IN, USA, where he has been since January 2015. He was a Senior Member of Technical Staff Research with AT&T Labs-Research, NJ (2010–2014), Adjunct Assistant Professor with Columbia University, NY (2013–2014), and VAJRA Adjunct Professor with IISc Bangalore (2018–2019). His current research interests are in communications and networking, cloud computing, and machine learning.
Dr. Aggarwal received Princeton University's Porter Ogden Jacobus Honorific Fellowship in 2009, the AT&T Vice President Excellence Award in 2012, the AT&T Senior Vice President Excellence Award in 2014, the 2017 Jack Neubauer Memorial Award recognizing the Best Systems Paper published in the IEEE Transactions on Vehicular Technology, and the 2018 Infocom Workshop HotPOST Best Paper Award. He is on the Editorial Board for the IEEE Transactions on Communications, the IEEE Transactions on Green Communications and Networking, and the IEEE/ACM Transactions on Networking.
He is currently an Associate Professor with Purdue University, West Lafayette, IN, USA, where he has been since January 2015. He was a Senior Member of Technical Staff Research with AT&T Labs-Research, NJ (2010–2014), Adjunct Assistant Professor with Columbia University, NY (2013–2014), and VAJRA Adjunct Professor with IISc Bangalore (2018–2019). His current research interests are in communications and networking, cloud computing, and machine learning.
Dr. Aggarwal received Princeton University's Porter Ogden Jacobus Honorific Fellowship in 2009, the AT&T Vice President Excellence Award in 2012, the AT&T Senior Vice President Excellence Award in 2014, the 2017 Jack Neubauer Memorial Award recognizing the Best Systems Paper published in the IEEE Transactions on Vehicular Technology, and the 2018 Infocom Workshop HotPOST Best Paper Award. He is on the Editorial Board for the IEEE Transactions on Communications, the IEEE Transactions on Green Communications and Networking, and the IEEE/ACM Transactions on Networking.