Optimization Algorithms for Large-Scale Systems: From Deep Learning to Energy Markets
Brief Biography: Navid Azizan is a fifth-year PhD candidate in Computing and Mathematical Sciences (CMS) at the California Institute of Technology (Caltech), where he is co-advised by Adam Wierman and Babak Hassibi, and is a member of multiple research groups: DOLCIT, RSRG and SISL. During the summer of 2019, he was a research scientist intern at Google DeepMind. He received the B.Sc. degree in EE form Sharif University of Technology and the M.Sc. degree in ECE from the University of Southern California, in 2013 and 2015, respectively. His research interests broadly lie in mathematical optimization, machine learning, networks, and markets. He is the recipient of several awards, including the 2016 ACM GreenMetrics Best Student Paper Award, the Amazon Fellowship in Artificial Intelligence, the PIMCO Fellowship in Data Science, the Caltech CMS Fellowship, and the USC Provost's Fellowship.
© 2019 Association for Computing Machinery (ACM).