Meet the 2017 Amazon Fellows
Four graduate students from the Computing and Mathematical Sciences (CMS) Department and one from the Electrical Engineering (EE) Department have been selected as 2017 Amazon Fellows. This fellows program is the result of a partnership between Caltech and Amazon AWS around Machine Learning and Artificial Intelligence. The EE fellow is Srikanth Tenneti who is exploring the potential of deep learning for Direction of Arrival applications, and extending Ramanujan Sums based techniques for multi-dimensional periodicity extraction. CMS graduate student Navid Azizan Ruhi is researching faster optimization algorithms for machine learning. He is looking forward to visiting Amazon AI as a fellow and exchanging ideas with their researchers. Computer science graduate student Hoang Le is developing methods for efficient and intelligent sequential decision making in realistic systems. Florian Schaefer, whose focus is applied and computational mathematics, is researching the interface of statistical estimation and the design of fast algorithms. Control and dynamical systems graduate student Ellen Feldman, working with Professor Joel Burdick, has used part of the funding to present her research at the Society for Neuroscience annual meeting and looking forward to other future opportunities to share her research.
P. P. Vaidyanathan
Navid Azizan Ruhi
Caltech and Disney Engineers Collaborate on Robotics
Caltech and Disney Research have entered into a joint research agreement to pioneer robotic control systems and further explore artificial intelligence technologies. Pietro Perona will work with Disney roboticist Martin Buehler to create navigation and perception software that could allow robotic characters to safely move through dense crowds and interact with people. Aaron Ames will work with Disney Research's Lanny Smoot to further explore robot autonomy and machine learning by creating objects that can self-navigate and perform stunts. Yisong Yue has been working with engineers from Disney Research on the use of machine learning to analyze the behavior of soccer players and to measure audience engagement. [Caltech story]