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Alok is a CS Ph.D. student at UC Berkeley, advised by Aydın Buluç and Kathy Yelick and affiliated with Lawrence Berkeley National Lab. He is broadly interested in designing algorithms that leverage high-performance systems, particularly heterogeneous systems. Currently, he is working on scaling graph-representation learning in distributed environments. In the past, he worked on accelerating graph analytics on GPUs with Oded Green at Georgia Tech. His work is supported by the NSF Graduate Research Fellowship.
Accelerators, FPGA, and GPUs
Linear Algebra
Machine Learning, Deep Learning and Artificial Intelligence
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