Yogesh Rawat

Yogesh Rawat is an Assistant Professor in the Department of Computer Science at the University of Central Florida and a faculty member at the Center for Research in Computer Vision (CRCV). He earned his Ph.D. in Computer Science from the National University of Singapore in 2017.

• Ph.D. in Computer Science – National University of Singapore

His research focuses on deep learning and computer vision, with applications in video understanding, human activity detection, multimedia computing, and media aesthetics. He explores how advanced algorithms can analyze and interpret visual data, particularly in dynamic environments and human-centric contexts.

Dr. Rawat has received recognition for his work, including a DARPA award (2019), multiple TRECVID challenge accolades (2014–2018), and a Research Achievement Award from NUS (2016).

• DARPA award, KAIROS, 2019
• Runners-up, ActEV Challenge for Activity Detection, TRECVID, Nov 2018
• Second runners-up, ActEV Challenge for Activity Object Detection, TRECVID, Nov 2018
• Research Achievement Award for outstanding research performance, NUS, Jan 2016
• Finalist at ACM Multimedia Grand Challenge, Amsterdam, Oct 2016
• Finalist at ACM Multimedia Grand Challenge, Orlando, Nov 2014

He has contributed to academic communities by serving on program committees for ACM Multimedia and the IEEE Winter Conference on Applications of Computer Vision, and as a reviewer for journals like IEEE Transactions on Multimedia and ACM Transactions on Multimedia Computing, Communications and Applications. Prior to joining UCF, Rawat worked at Mentor Graphics in India (2009–2012) and completed a postdoctoral fellowship at UCF (2017–2019).