Magic Leap Augmented Reality + Computer Vision Technical Leads Panel
Come join fellow Augmented Reality and Computer Vision/Machine Learning folks for our fun-packed event!
This event is sponsored by Epic. Epic is a mobile wallet and self-checkout app incorporating Computer Vision and Augmented Reality. Sign Me Up as a Beta User!
Join Our Meetup Groups:
6:30pm - 7:00pm: Registration and Networking
7:00pm - 7:10pm: Opening Remarks
7:10pm - 8:00pm: Augmented Reality Fireside Chat and Panel
Ali Shaw-Rockney - Lead Embedded Software Engineer, Magic Leap
Ali Shaw-Rockney is a Lead Software Engineer in the Embedded Algorithms Team at Magic Leap. He received his PhD in Computer Vision from EPFL, Switzerland and postdoc from the Robotics Lab, University of Oxford, UK. He has over a decade of industrial and academic research experience in Computer Vision for 3D reconstruction and Mixed Reality. He has worked at Amazon Lab126, Broadcom, 2d3/Vicon as part of their embedded Computer Vision team prior to joining Magic Leap. Outside work, he enjoys long distance road cycling, amateur carpentry, photography and spending time with his wife and two boys.
Ashwin Swaminathan - Distinguished Fellow of Computer Vision, Magic Leap
Ashwin Swaminathan is part of computer vision team at Magic Leap where he leads a team researching on world sensing, simultaneous localization and mapping, object recognition, visual inertial odometry, and scene semantics.
Prior to joining Magic Leap, he was with Qualcomm Research in San Diego from 2008 to 2015. At Qualcomm Research, he was involved in various computer vision and machine learning projects for applications in augmented reality and context aware computing on mobile phones. In addition, he was involved in Qualcomm’s efforts in robotics and drones.
Ashwin Swaminathan holds a Ph.D. from the University of Maryland, College Park where he conducted research in several topics in image processing, multimedia forensics, security and watermarking.
Ashwin holds 30+ patents in the field of computer vision, machine learning and Augmented Reality. He has authored 7 journal papers, 30+ conference papers with a combined 3200+ citations.
Prateek Singhal - Lead Computer Vision Engineer, Magic Leap
Prateek currently is a lead computer vision research engineer at Magic Leap. He leads the team on Scene Understanding and Object Recognition using different modalities like depth camera, cameras and IMU. He previously led the team for large scale persistence on the device. He is also one of the core members of headpose team and have worked on core tracking and mapping algorithms for Magic Leap One.
Prior to Magic Leap, he got his Masters from Georgia Tech, working with Dr Henrik Christensen. He worked and published on integrating object tracking and multiple objects into SLAM to create semantically rich maps. He also worked on Dynamic Motion Segmentation for autonomous car scenarios, at IIIT Hyderabad. He has been working on SLAM and related areas for over 6 years.
Sheng Huang, Moderator - Head of Business Operations & Partnerships, Sturfee
Sheng Huang is the Head of Business Operations at Sturfee, a computer vision company that creates the world’s first city-scale visual positioning service (VPS).
Prior to Sturfee, he was an early member of Niantic Labs, helping them scale user operations to support millions on Ingress. Before Niantic, Sheng was part of the strategy team in Google’s internal incubator for local products such as Wallet, Offers, and indoor maps. Sheng did his MBA at the London Business School and undergraduate business and legal degrees from UC Berkeley.
8:00pm - 9:00pm: Networking
Venue: UC Berkeley Extension - SAN FRANCISCO CAMPUS
160 Spear St., Floor 6 (Room 609), San Francisco, CA 94105
Notice of Photo/Video Consent: Video footage (including 360 Video) and/or photos may be taken during this event, which may or may not include your recognizable image. Please be advised, by participating in this event, you agree to allow AR + CV and its partners to use the images in print, digital or web-based formats for promotional and archival purposes.