Dear Friends and Affiliates,
The Product Realization Lab (PRL), and its satellite space, Room 36 in Huang Engineering is a major making space on campus where each year more than 1000 undergraduate, graduate and professional students do hands on work to bring their ideas to life. In existence since the University opened its doors 125 years ago, the PRL is also where the X1 research vehicle was built. Lab fees were eliminated during COVID-19 and coupled with the many courses that use the PRL, the VAIL CNC was moved to main campus to help alleviate the backlog of students waiting to use the CNC. Courses that incorporate CNC use include ME128: Computer Aided Product Realization, ME318: Computer-Aided Product Creation and
ME325: Making Multiples: Injection Molding. With three weeks remaining in the spring quarter, students are rushing to complete their projects before commencement on June 12.
In case you missed the last webinar, CARS Fellow, Karthik Gopalakrishnan, presented his recent work on Efficient Traffic Routing While Preserving Privacy earlier this month. The video recording is available here. Karthik's work leverages ideas from cryptography, differential privacy and online learning to achieve efficient routing without compromising user privacy. Karthik is a postdoctoral scholar in the Autonomous Systems Lab.
Please be sure to checkout our archives of past webinars and mini-classes in the members only section at cars.stanford.edu. You'll also find past annual meeting recordings and newsletter items. Email me at [email protected] with any access issues.
Sincerely,
Adele Tanaka
Associate Director
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Moving day for the CNC that was in the VAIL machine shop to its new home at the Product Realization Lab as part of the reconfiguration of the machine shop. |
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Tire shipment from Bridgestone ahead of the May Thunderhill Raceway research trip. |
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Designing Decision-Making Algorithms in an Uncertain World
The new book by Mykel Kochenderfer, associate professor of aeronautics and astronautics and colleagues, Tim A. Wheeler and Kyle H. Wray, recommends various approaches for designers solving different kinds of problems. In this article, Kochenderfer discusses the value of computer-based algorithmic decision making and the key themes of the book.
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Stanford expert on climate report: Energy technology is ready, but time is short
Inês Azevedo, a lead author of the energy chapter in the United Nations' new report on climate mitigation, discusses changes necessary to keep global warming below 2 degrees Celsius. “We have the technologies needed to have net-zero energy systems. What we are lacking is time,” said Inês Azevedo. Link
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Are Big Companies' Net-Zero Pledges a Well-Intentioned Shell Game?
In a chapter in the new book, Frontiers of Social Innovation, Stefan Reichelstein, professor emeritus at Stanford Graduate School of Business, proposes a framework called the Intertemporal Corporate Carbon Reporting standard, to make the distinction between corporate spin and real impact. Link
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Reversible fuel cells can support grid economically, Stanford researcher finds
Researchers at Stanford and the University of Mannheim report that reversible fuel cells can be an economically viable source of backup electricity during periods of surging prices. Being able to switch directions, the entire system can run closer to full capacity which reduces the cost of producing both carbon-free hydrogen and carbon-free electricity. Link
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How to build a better magnet
Researchers from Stanford and John Hopkins University are developing a new type of ultra-efficient material called "soft magnetic composite," or SMC, that can lead to miniaturized motors, power supplies and generators. Magnets are used in almost every step of electrical production but improving them has been a challenge. Link
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New hardware created by Stanford team shows a way to develop delicate quantum technologies based on tiny mechanical devices
By bringing the benefits of mechanical systems into the extremely small scales of the quantum realm, Stanford researchers have demonstrated new capabilities by coupling tiny nanomechanical oscillators with a type of circuit that can store and process energy in the form of a qubit. The aim is to create advanced computing and sensing devices. Link
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Stanford AI's Legacy Through the Decades
Stanford University has a rich history as one of the pioneers in AI. In this video, Stanford Human-Centered Artificial Intelligence (HAI) professors Fei-Fei Li, Chris Manning, and others describe the history of Stanford AI and the future of AI. Link
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Efficient Traffic Routing while Preserving Privacy with Karthik Gopalakrishnan, ASL
Knowledge of the preferences and actions of other users is essential for making optimal traffic routing decisions. However, in practice, this information may not be available due to privacy considerations, which makes it challenging to compute efficient solutions. In this talk, Karthik will describe two settings where we achieve efficient routing without compromising user privacy by leveraging ideas from cryptography, differential privacy, and online learning. View the webinar recording here.
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CARS Mini-class with Sriramya Bhamidipati, NAV Lab
Title: Safe Vision-based Navigation of Autonomous Vehicles
In this tutorial, Ramya Bhamidipati, postdoctoral scholar in the Stanford Navigation and Autonomous Vehicles Lab (NAV Lab) will explore the use of computer vision algorithms to perform safe and trustworthy localization of autonomous vehicles. View the mini-class agenda here and view the recording here.
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CARS Mini-class with Akshay Shetty, NAV Lab
Title: Trajectory Planning for Autonomous Vehicles Under Motion and Sensing Uncertainties
Akshay Shetty, postdoctoral scholar in the Stanford Navigation and Autonomous Vehicles Lab (NAV Lab) will lead our next mini-class. He will begin by looking at traditional tree-based planning algorithms, then cover recent extensions that account for motion and sensing uncertainties and finally, explore how these tools can be applied to ensure collision-safety for neural network-based planners. View the mini-class agenda here and join the mini-class on Zoom.
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Joint Optimization of Autonomous EV Fleet Vehicle Sizing, Charging Station Siting, and Fleet Operations
This webinar presents an optimization model that jointly determines the vehicle sizing, the siting of charging stations of varying charging speeds, and the macroscopic-level operations for an autonomous electric mobility-on-demand fleet. Justin Luke, PhD candidate in Civil and Environmental Engineering, is co-advised by Marco Pavone and Ram Rajagopal. View the webinar agenda here and the recording here.
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