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Machine Learning for Safety-Critical Applications

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Hosted By
Gideon W.
Machine Learning for Safety-Critical Applications

Details

Welcome to the October BostonML Meetup hosted by Optimus Ride!

Schedule:
5:30 - 6:00pm Registration and Mingling
6:00 - 7:00pm Presentation from Optimus Ride
7:00 - 7:30pm Q&A
7:30 - 8:00pm Networking

Abstract:

In this talk, we will discuss key considerations when developing and deploying ML algorithms for safety-critical applications such as self-driving vehicles. This includes how we collect, sample and annotate the data required for training, testing and validation of ML and NN models for different autonomy components, as well as how these models are then tested and validated in both simulation and on-vehicle testing, across multiple deployment sites.

Speakers:

RJ He is the VP Engineering at Optimus Ride, where he works with an amazing team of engineers to build and deploy self-driving vehicles across numerous geo-fenced environments. He was previously at Google, where he developed ML algorithms for the Google Assistant, as well as the military, where he was a Mechanized Infantry Company Commander. RJ holds a PhD in Aerospace Engineering and a MS in Political Science, both from MIT.

Dr. Ryan C.C. Chin is the CEO and Co-founder of Optimus Ride. He was previously the Managing Director of the City Science Initiative at the MIT Media Lab (2012-2015) where innovative research was conducted on urban housing, transport, and energy. He researched Autonomous Mobility-on-Demand Systems – a network of self‑driving, shared-use, electric vehicles (EVs). He developed EVs including the GreenWheel, RoboScooter, Persuasive Electric Vehicle, and the CityCar – a foldable, electric, two-person vehicle. Time Magazine named the CityCar the “Automotive Invention of the Year”.

Dr. Chin advises industry and government agencies on Smart Cities innovations. He was a member of the White House President’s Council of Advisors on Science and Technology working group in 2015 on “Technology and the Future of Cities.” His MIT Professional Education course “Beyond Smart Cities” attracted global participants from corporate, public, and educational sectors. He frequently travels as a speaker at conferences like TEDx, MIT EmTech, and Smart City Expo. He received at MIT his PhD (2012) and MS (2004) in Media Arts and Sciences and a MArch (2000) in Architecture.

Jenny Larios Berlin is the COO and Co-Founder of Optimus Ride and is a veteran of car sharing technology and operations, having worked previously for Zipcar. As a General Manager, Jenny introduced Zipcar operations into several university campuses nationwide. She created the strategic vision and managed the sales, marketing, and operations teams to deliver groundbreaking mobility solutions. Jenny was also the National Members Services Manager for Zipcar and was responsible for their service operations in all of their cities worldwide. In 2015, Jenny earned her Master’s in City Planning and MBA from the MIT. While at MIT, Jenny worked in the Transportation Lab investigating mobility and urban transportation systems in low- income communities, which culminated in the publication of the book Simple Rules: How to Thrive in a Complex World (2015).

Sertac Karaman is the President of Optimus Ride and is also an Associate Professor at MIT in the Lab for Information and Decision Systems. His research interests lie in the broad area of embedded systems and mobile robotics. His recent research has focused on developing planning and control algorithms for self‑driving vehicles and autonomy-enabled transportation systems. More broadly, he has worked on driverless cars, unmanned aerial vehicles, distributed aerial surveillance systems, air traffic control algorithms, certification and verification of control systems software. In particular, he was on MIT’s team that built a self‑driving car and competed in the DARPA Urban Challenge. His experience with robotic platforms also includes developing an autonomous forklift, working with Willow Garage’s personal robot PR2, and developing fully autonomous drones.

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