In a research collaboration with Stanford, SLAC, MIT and Toyota Research Institute, researchers applied an approach known as "scientific machine learning" to battery cycling. The goal is the bring together foundational research and industry know-how to develop a long-lived electric vehicle battery that can be charged in 10 minutes.
The defense authorization bill passed by Congress on Jan 1, includes provisions to handle the opportunities and risks of AI along with a new White House office to coordinate AI research across government agencies. Stanford Institute for Human-Centered Artificial Intelligence had a role in shaping a national research cloud to give researchers access to world-class computing power, and data with the goal of opening up AI to a larger and more diverse array of academic researchers.
A free version of the first half of the course "Programming Methodology" called "Code in Place" will be taught again starting April 19. "Code in Place" had over 10,000 students in 120 countries learning computer programming from 900 volunteer teachers. Developed after the shelter-in-place orders, Stanford computer science faculty Chris Piech and Mehran Sahami reimagined their course for a broader online audience.
Planning for Stanford's new school for climate and sustainability has continued through the fall and winter by a 30-member faculty Blueprint Advisory Committee to design the new school's structure, education programs, themed initiatives and engagement activities.
Please join us for our May webinar with John Alsterda, Ph.D. candidate in Chris Gerde's Dynamic Design Lab. John will be presenting his work on Contingency Model Predictive Control for Autonomous Vehicles. View the agenda here and join the webinar here via Zoom.
Partnering with BEAM, Stanford Career Education, CARS will be hosting a virtual recruiting/networking event on April 19 from 5:00 - 6:30 pm PDT via Zoom. This event will provide students an opportunity to meet affiliate professionals and hear your insights and experiences about career paths. Please email Adele Tanaka if you would like to participate.
Join us for our first bi-monthly mini-class with Sandeep Chinchali, postdoctoral scholar in Marco Pavone's Autonomous Systems Lab. In the first half of the mini-class, Sandeep will cover modern deep reinforcement learning and will describe a case study of using deep reinforcement learning for compute model selection in cloud robotics in the second half.
In this thesis defense by Raunak Bhattacharyya with Mykel Kochenderfer's Stanford Intelligent Systems Lab, Raunak presents his work on: how do we model human driving, how do we evaluate how well we modeled human driving and how we do use our models.
In this Human-Centered Artificial Intelligence (HAI) Weekly Seminar, Monroe Kennedy III, assistant professor, mechanical engineering, discusses what makes an effective robotic assistant, and considerations for modeling, anticipating, and collaborating with a human teammate.
While our homes and cars are watched over by A.I.-integrated sensors, soon networks of overlapping cameras and sensors will be available to monitor us all the time, if we want.
