Asaad Hakeem has over 15 years of experience in video analytics and computer vision. His expertise includes target tracking, event representation, event specification, and complex event detection in videos from ground, maritime and airborne sensors. He has several papers published in peer reviewed conferences and journals in the field of computer vision and artificial intelligence. He received the best paper award nomination at the ACM Multimedia conference for his work in object-based video compression. He is the winner of both UCF's EECS and Industry day outstanding dissertation awards. He has served on several peer review committees in top tier computer vision conferences and journals; and has conducted a series of (continuing) workshops as chair on “Visual Analysis and Geo-Localization of Large-Scale Imagery” at premiere computer vision conferences related to IARPA Finder and DARPA Visual Media Reasoning programs.
He is currently the CEO of SARC MedIQ, a disruptive cloud based Artificial Intelligence driven medical imaging infrastructure, annotation, archiving and billing platform that is FDA/HIPAA compliant. We have partnered with one of the largest medical consortium in the mid-west United States consisting of over 100 clinics and hospitals to transform their past archiac infrastructure to a seamless cloud-based global platform. He is also currently the Director of Research at Aquabyte, a leader in environmentally safe protein production through Artificial Intelligence and Computer Vision based hardware and software platforms. He is on the board for several stealth startups in the Artificial Intelligence application domain. Previously, he was the head of the Perception at JDX, a chinese giant equivalent to Amazon where he lead a team of 20+ researchers and developers. His team collaborated with Stanford, Berkeley, and Rutgers for products related to Autonomous Driving - Indoor and outdoor delivery vehicles, trucks and drones; Robotic arm navigation and fast object picking; and ARGUS - Next Generation Tracking and Activity Recognition.
He holds a MS. and Ph.D Degrees in Computer Science from University of Central Florida, a Bachelors degree in Computer Systems Engineering from GIKI, and is currently enrolled in LEAD - Executive Education in Leadership from Stanford GSB.