Ajay Divakaran (SRI International) ajay[dot]divakaran[at]sri[dot]com
Ajay Divakaran, PhD is a Technical Manager at SRI International Sarnoff. He has developed several innovative technologies for multimodal systems for both commercial and government programs over the past 16 years. He currently leads SRI Sarnoff’s projects on Modeling and Analysis of Human Behavior for the DARPA SSIM project, ONR Stress Resiliency project, Army "Master Trainer" Intelligent Tutoring project, Audio Analysis for Event Detection in Open Source Video in the IARPA Aladdin program, and People, Vehicle and Vessel tracking for ONR and JIEDDO-DHS among others. He worked at Mitsubishi Electric Research Labs for ten years where he was the lead inventor of the world’s first sports highlights playback enabled DVR, as well as a manager overseeing a wide variety of product applications of machine learning. He was elevated to Fellow of the IEEE in 2011 for his contributions to multimedia content analysis. He developed techniques for recognition of agitated speech for his work on sports highlights. He established a sound experimental and theoretical framework for human perception of action in video sequences, as lead-inventor of the MPEG-7 video standard motion activity descriptor. He serves on TPC’s of key multimedia conferences, served as an associate editor of the IEEE transactions on Multimedia from 2007 to 2011, and has 2 books and over 100 publications to his credit as well as over 40 issued patents. He received his Ph.D. degree in Electrical Engineering from Rensselaer Polytechnic Institute in 1993.
Maneesh Singh (SRI International) maneesh[dot]singh[at]sri[dot]com
Maneesh Singh, PhD is a Technology Leader at SRI International in the Center for Vision Technologies at Princeton, NJ. He has over 15 years of R&D experience in statistical computer vision with more than 8 years of customer-focused industrial R&D experience in designing computer vision systems in the areas of security and surveillance, industrial inspection, medical image processing and patient diagnostics. He has over 35 patents and publications in these areas. His current R&D interests lie at the confluence of social and psychological theories of human behavior, computer vision, computational neuroscience, and medical diagnostics. In his role as Staff Scientist at Siemens Corporate Technology, he led projects on multi-camera surveillance, smart vision systems for vehicle transit and lane occupancy detection, and computer aided medical diagnostics. He received his PhD in Electrical and Computer Engineering from the University of Illinois at Urbana Champaign in 2003. He is a member of the IEEE.
Mohamed Amer (SRI International ) mohamed[dot]amer[at]sri[dot]com
Mohamed R. Amer, PhD is a Computer Scientist at SRI International. His main research focus is on human activity recognition, classification in Videos. His interest is in modeling context and interactions with goal event detection and video understanding. He has done some work on 2D to 3D conversion in images, and recently, he has done some work on the problem of Multimodal Event Detection for Affect Analysis. He received his B.S., M.S., and PhD at Oregon State University.
Saad Khan (SRI International) saad[dot]khan[at]sri[dot]com
Saad Khan, PhD is a Senior Computer Scientist at SRI International with expertise in developing computer vision and human machine interaction algorithms. He has led the design and development of advanced intelligent training/tutoring systems that can adapt to both training scenarios and learners’ behavior. He serves as principal investigator (PI) and co-PI on programs in multimodal sensing systems for immersive training and human performance assessment. He led the development and transition of APELL (Automated Performance Evaluation and Lessons Learned) training system. APELL is an immersive, interactive, Mixed Reality training system that provides real-time sensing and automated performance analysis of trainee actions in MOUT sites. Prior to joining SRI Sarnoff, Khan conducted research on 3D model based object tracking and human activity analysis. His work in automated image based localization earned an Honorable Mention award at the International Conference of Computer Vision 2005. He has authored over 25 papers and has 2 issued patents. He received his PhD in Computer Science from University of Central Florida in 2008. Khan received a Ph.D. in computer science from the University of Central Florida in 2008. He is a member of IEEE and chairs the Signal Processing Chapter for Princeton / Central Jersey Section.
Behjat Siddiquie (SRI International) behjat[dot]siddiquie[at]sri[dot]com
Behjat Siddiquie, PhD is a Computer Scientist at SRI International where he is currently working on multimodal affective analysis and sensing, and modeling of interpersonal interactions. His research interests are in computer vision, machine learning and affective computing. He received the B.Tech. degree in computer science and engineering from the Indian Institute of Technology, Bombay, in 2006 and the M.S. and Ph.D. degrees in computer science from the University of Maryland, College Park, in 2009 and 2011 respectively. His Ph.D. thesis addressed the problem of efficient image retrieval based on complex and descriptive queries.