Amazon is establishing world-class research partnerships at strategic, preeminent institutions across the world. Bringing leading scholars, faculty, students, and entrepreneurs together with Amazon’s top science leaders and engineering teams from multiple business units, this initiative furnishes a framework for supporting fluid, university-industry collaboration. Tackling large-scale, foundational technical challenges in key areas such as machine learning, computer vision, speech recognition/natural language processing, optimization, economics, sustainability, hardware, data science and robotics, hubs create communities that welcome diverse perspectives and disciplines to accelerate innovation.As the Principal Technical Program Manager, I have responsibility for defining and deploying the global strategy for Amazon's company-wide university partnerships. My work involves forging alignment and technical requirements across multiple Amazon businesses and academic partners in North America, Europe, and Asia. To do so, I work with an array of internal stakeholders including finance, legal, HR, and science/engineering teams as well as university administrators and scholars.

Directs all research and development activities for the Perceptional and Analytics Lab (PAL) and manages a talented team of expert engineers and scientists. PAL is at the intersection of silicon architecture and high-performance applications using vision, sensor fusion, and environmental modeling. PAL develops algorithms, advanced prototypes, novel IP as well as high-performance embedded systems for autonomous vehicles, drones, and robots.

Stereo Vision team lead for Processor's Perception Processing and Analytics Lab. Responsible for multiple stereo vision-related projects, all with significant engagement with Processor businesses (ADAS BU and Catalog/Industrial). Scope of projects include algorithm design and development, software architecture and optimization, system and application prototyping as well as software modeling and simulation.

As a Senior Software Design Engineer and member of TI's peer-elected Technical Ladder (MGTS), I develop computer-vision, image, and video-based technologies for video surveillance, automotive, and mobile applications. I lead development of DMVA, the world's first low-cost embedded IP camera processors with hardware-accelerated video analytics. My primary focus is on developing novel smart-camera prototypes to solve customer problems, drive internal product roadmaps, and demonstrate system capabilities. I really enjoy collaborating with business development, product engineering teams, and customers to deliver highly-optimized embedded solutions as well as reference designs.

Designed performance-optimized motion estimation algorithms for H.264, WMV9 (VC-1) and MPEG-4 encoders.Invented low-complexity rate-distortion optimization technique to improve the image quality of video encoders for mobile applications (Patent #8,160,150). Developed JPEG2000 image compression software for digital still cameras, camcorders, and mobile phones. Optimized software for TI DSP-based digital media processors. ▫ Created TI’s 1st real-time, digital camera System-on-chip prototype with JPEG2000 encoding.▫ Developed new algorithms for video performance acceleration eliminating the need for specialized wavelet hardware accelerators. Also developed custom framework to support parallel processing (Pat#7,327,894).

Developed computer-vision based PHyCONS (physical icons) for intelligent, interactive environments.

Developed computer vision software for NCR's Customer Activity Analysis software.