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16 Years
V Chandrasekar
Dr. Chandra Vaidyanathan, obtained his PhD from the University of Missouri-Columbia. He graduated with a Bachelor’s Degree from the University of Madras in Electronics and Communications Engineering. He got his Master’s Degree in Communications and Signal Processing from the University of Notre Dame. He transitioned from Engineering to Mathematics with a Master’s Degree in Applied Mathematics from the University of Notre Dame. He straddles between the theoretical world of Mathematics and the practical world of Signal Processing and Machine Learning. His areas of interest include Probability, Functional Analysis, Random Matrix Theory and its application areas such as Compressed Sensing and Machine Learning. He spent a Summer at Mathematical Sciences Research Institute (MSRI) in Berkeley and finished a year of study at the University of Michigan, Ann Arbor. He developed the algorithm that powered the washing machines of various manufacturers in Japan and Europe as a Software Engineer in Embedded DSP division of Analog Devices Inc. Recently, he was instrumental in developing a lossless video compression algorithm which performs as well as the standard ones, using Machine Learning techniques. He founded the industry driven research lab for IoT, Signal Processing and Machine Learning, iSIGMA lab at Dayananda Sagar University. In addition to his research credentials, he is also very passionate about teaching. He was consistently rated among the top Teaching Assistants at the University of Notre Dame, University of Michigan, Ann Arbor and at the University of Missouri-Columbia. He was an instructor for the Cryptology course at the Center for Talented Youth, Johns Hopkins University, Baltimore. He embraces Ken Bain’s inspirational book, What the best College teachers do? with great sincerity. He has created a workshop based on the contents of the book, which he has used for Course Design at Dayananda Sagar University. He was also the Chairman of the Maths Department there and the Assistant Dean of Academics for the School of Engineering.

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