In this meetup being sponsored by Wave Computing and RSIP Vision, we'll have three talks.
Majid Bemanian from Wave Computing will talk about the current state of computer vision technology.
Following, Max Allen from Intuitive Surgical will discuss his company's revolutionary approach to combine computer vision with robotics in medical surgeries.
Finally Pulkit Agrawal, a PhD student at UC Berkley & Chief Architect of SafelyYou, will present a new approach of robots learning via biological sensorimotor techniques.
Tentative agenda is:
- 6:00 - 6:45 Pizza and networking
- 6:45 - 7:00 Welcome and sponsor message
- 7:00 - 8:30 Presentations and Q&A
- 8:30 - 8:45 Additional Q&A and wrap up
- See further description below -
Advances in Computer Vision
In this talk, Majid will discuss the latest advancements in computer vision – from processing needs to hardware and software requirements – for applications spanning the datacenter to the edge. He’ll address key topics including parameters for both training and inferencing, as well as highlight the best practices to evaluate and fine-tune these parameters for computer vision applications.
Bio: Majid is the Director of Marketing for Wave Computing, where he is responsible for leading the market strategy for Wave’s MIPS IP Business Unit. He also co-chaired the prpl Foundation’s security working group, focused on developing open standards and APIs around next-generation security solutions. Majid has more than 30 years of high-tech industry experience for companies including Amdahl Communications, Ascom-Timeplex, Encore Video, Raytheon Semi, LSI Logic, AppliedMicro, and many early-stage startups. He is also an inventor on more than 10 U.S. patents.
Using computer vision for robotics surgery
The talk will focus on the history and current state-of-the-art in robotic minimally invasive surgery and how computer vision and machine learning can potentially revolutionize this field.
Bio: Max Allan works as computer vision engineer at Intuitive Surgical in Sunnyvale. His work is focussed on applying computer vision and machine learning algorithms to build products for the da Vinci surgical robot. He is originally from the U.K. where in 2017 he received a PhD from UCL on the detection and tracking of surgical instruments for laparoscopic and robotic surgery.
Computational Sensorimotor Learning
An open question in artificial intelligence is how to endow agents with common sense knowledge that humans naturally seem to possess.
A prominent theory in child development posits that human infants gradually acquire such knowledge through the process of experimentation.
According to this theory, even the seemingly frivolous play of infants is a mechanism for them to conduct experiments to learn about their environment.
Inspired by this view of biological sensorimotor learning, I will present my work on building artificial agents that use the paradigm of experimentation to explore and condense their experience into models that enable them to solve new problems.
I will discuss the effectiveness of my approach and open issues using case studies of a robot learning to push objects, manipulate ropes, finding its way in office environments and an agent learning to play video games merely based on the incentive of conducting experiments.
Bio: Pulkit is a Ph.D. Student in the department of computer science at UC Berkeley.
He is advised by Dr. Jitendra Malik and his research spans robotics, deep learning, computer vision and computational neuroscience.
Pulkit completed his bachelors in Electrical Engineering from IIT Kanpur and was awarded the Director’s Gold Medal. His work has appeared multiple times in MIT Tech Review, Quanta, New Scientist, NYPost etc.
He is a recipient of Signatures Fellow Award, Fulbright Science and Technology Award, Goldman Sachs Global Leadership Award, OPJEMS, Sridhar Memorial Prize and IIT Kanpur’s Academic Excellence Awards.