University of Central Florida - Computer Science
Director, AI and Machine Learning, ACTNext at ACT
Education Management
Saad
Khan
Princeton, New Jersey
Experienced technical leader with expertise in Computer Vision, AI and Machine Learning. 11+ years of technical leadership in developing and deploying data-driven machine learning solutions and actionable insights that drive business value including video analytics, business process automation, cognitive computing architectures and advanced learning systems. Demonstrated ability to successfully lead and manage large teams of data scientists and software engineers, and articulate strategic business value propositions to technical leaders, C-level executives and clients. Extensive experience in business capture and development with a track record of winning and leading programs awarded by external clients.
Graduate Research Assistant
I worked on a variety of research projects including:
* Multi-view Tracking in Crowds of People
* Activity Recognition in Groups of People
* 3D Reconstruction
* View Invariant Object Recognition
* Route Panoramas for Localization
* Vision based Navigation
Managing Sr Research Scientist - Computer Vision and Machine Learning
Lead a team of multi-disciplinary scientists conducting research and development in advanced cognitive computing architectures for a new generation of video based learning and assessment systems. My work encompasses advances in AI, Machine Learning, Multimodal Analytics and their intersection with education research. In addition I lead proposal development and business capture activities and am currently PI on various research programs leading cross functional matrix teams.
Adjunct Faculty Department of Electrical and Computer Engineering
Saad worked at Rutgers University as a Adjunct Faculty Department of Electrical and Computer Engineering
Director, AI and Machine Learning, ACTNext
Saad worked at ACT as a Director, AI and Machine Learning, ACTNext
Senior Computer Scientist
Leadership in design and development of advanced computer vision algorithms for human-machine interaction and automated content analysis from audio, video and other sensors. I also served as principal investigator and project lead on a number of R&D programs funded by DARPA, ONR and AFRL.
Ph.D.
Computer Science
Graduate Research Assistant
I worked on a variety of research projects including:
* Multi-view Tracking in Crowds of People
* Activity Recognition in Groups of People
* 3D Reconstruction
* View Invariant Object Recognition
* Route Panoramas for Localization
* Vision based Navigation
Bachelor of Science - BS
Computer Science
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