Roborace @ CMU

Carnegie Mellon University is the first U.S.-based team to join Roborace, a novel autonomous racing series. Created to accelerate the development of autonomous software, Roborace pushes the current technology to its limits and provides education about autonomous driving.

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About Us

We’re CMU Roborace Team.

The first U.S.-based team to join the Roborace series, Carnegie Mellon’s School of Computer Science is widely recognized as one of the best computer science programs in the world.

Accelerating innovation in autonomous driving systems and exciting a new generation of students to pursue STEM and AI careers.

Students and faculty across Carnegie Mellon collaborate to compete in this novel intersection of technology and sport.

Roborace supplies a platform for the competition, including venues, vehicles, compute platforms, and sensor stacks.

Teams bring their AI algorithms to compete head-to-head on a level playing field.

A Leader in Autonomous Driving

Join our Team

CMU's History in Autonomous Driving

1985

NAVLAB 1

The first self-driving vehicle was created at CMU, with top speed of 20 mph.

1995

NAVLAB 5

Traveled from Pittsburgh to San Diego in the No Hands Across America Tour, driving autonomously for 98% of the trip, with top speed of 60 mph.

2005

H1ghlander

Finished a 60-mile desert road course 100% autonomously.

2007

Tartan Racing’s “Boss”

Won DARPA Urban Challenge, taking home a $2 million first prize.

2020

Roborace

CMU joined the Roborace series and finished on podium in its first race.

Our Team

Our team is comprised of Carnegie Mellon students and alumni. For many of our teammates, the platform serves as a research capstone project with the goal of developing state-of-the-art technology in a domain where autonomous driving systems are pushed to their limits. Together with Roborace, we will provide an alternative perspective on the progression of autonomous driving technology.

[Jimmy Herman](https://www.linkedin.com/in/jimmy-herman)

Jimmy Herman

Team Principal, Master’s Student in Computational Data Science

Jimmy, a graduate student in the Master’s in Computational Data Science program at CMU, is a software engineer and the team principal. A credentialed actuary and former NFL athlete, Jimmy brings significant statistical modeling experience and a competitive spirit to the team. He is interested in building the next generation of autonomous driving agents, which have learned competitive racing strategies, and bringing them to reality.

[Shravya Bhat](https://www.linkedin.com/in/shravyabhat/)

Shravya Bhat

Master’s Student in Computational Data Science

Shravya Bhat is a Computer Science Engineer currently pursuing a Master’s degree in Computational Data Science at Carnegie Mellon University. She has extensive research experience with Natural Language Processing and Machine Learning technologies. She also worked as a senior software engineer at Nasdaq and was instrumental in rewriting nasdaq.com. Her current interests lie in employing deep learning technologies to solve real-world problems.

[Christian Deverall](https://www.linkedin.com/in/christian-deverall-cmu/)

Christian Deverall

Master’s Student in Computational Data Science

Christian Deverall comes from a background in Computer Engineering and is now a student in the Master’s of Computational Data Science program at Carnegie Mellon University. He has industrial and academic experience in the areas of Natural Language Processing, Computer Vision and Robotics with a focus on health applications. His current research interest is to use multimodal machine learning for fully-autonomous navigation.

Jingyuan Li

Jingyuan Li

Master’s Student in Computational Data Science

Jingyuan is a graduate student pursuing a Master’s Degree in Computational Data Science program at Carnegie Mellon University. He has rich experience in computer vision technologies and has published papers in related fields at ICCV and CVPR. His current interest is in computer vision technologies for robotic control (e.g. video motion prediction, video understanding), especially under weak/no supervision. His eventual goal is to allow the machine to understand the structure of the visual world with little human guidance.

[Ruoxin Huang](https://github.com/rxhuang)

Ruoxin Huang

Master’s Student in Computational Data Science

Ruoxin Huang comes from a statistics background, and has done extensive research on databases and deep learning. He has 2 years of experience as a Financial Analyst for the private equity firm Partners Group, where he developed applications to support billion dollar level trading.

[Jiayi Weng](https://www.linkedin.com/in/trinkle23897/)

Jiayi Weng

Master’s Student in Computational Data Science

Jiayi Weng has rich research experience in Reinforcement Learning and machine learning. He has previously published one paper, got the first place in VizDoom 2018 competition (single player track), and built one of the most popular PyTorch Reinforcement Learning platform Tianshou. His goal is to do impactful work in this challenging field.

Advisors

[Anirudh Koul](https://www.linkedin.com/in/AnirudhKoul/)

Anirudh Koul

Coach, Master’s in Computational Data Science Alumni

Anirudh Koul is a noted AI expert, NASA ML Lead, UN/TEDx speaker, author of the Practical Deep Learning book, and a former scientist at Microsoft AI & Research, where he founded Seeing AI, considered the most used technology among the blind community after the iPhone. With features shipped to a billion users, he brings over a decade of production-oriented applied research experience on petabyte-scale datasets. His work in the AI for Good field, which IEEE has called ‘life-changing’, has received awards from CES, FCC, MIT, Cannes Lions, American Council of the Blind, showcased at events by UN, World Economic Forum, White House, House of Lords, Netflix, National Geographic, and lauded by world leaders including Justin Trudeau and Theresa May.

[Siddha Ganju](https://www.linkedin.com/in/sidgan/)

Siddha Ganju

Coach, Master’s in Computational Data Science Alumni

Siddha Ganju, an AI researcher who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. As an AI Advisor to NASA FDL, she helped build an automated meteor detection pipeline for the CAMS project at NASA, which ended up discovering a comet. Previously at Deep Vision, she developed deep learning models for resource constraint edge devices. Her work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN’s petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS. She has served as a featured jury member in several international tech competitions including CES. As an advocate for diversity and inclusion in technology, she speaks at schools and colleges to motivate and grow a new generation of technologies from all backgrounds. She is also the author of O’Reilly’s Practical Deep Learning for Cloud, Mobile and Edge.

[Jonathan Francis](http://www.linkedin.com/in/jonmfrancis/)

Jonathan Francis

Coach, PhD Candidate of Carnegie Mellon’s School of Computer Science

Jonathan Francis is a staff AI research scientist at Bosch Research & Technology Center North America and a PhD student in the School of Computer Science at Carnegie Mellon University. His research area is in the field of Multimodal Machine Learning – with patents, publications, and fellowship awards covering such areas as: robot skill distillation in vision+language navigation, multi-agent trajectory forecasting, virtual sensing and machine health monitoring for complex systems, hybrid modeling for neural commonsense reasoning, and domain adaptation for autonomous vehicle perception systems. As a former research engineer in a major U.S. defense contractor and a research committee member for various U.S. Department of Energy programs in distributed sensing and control, Jonathan brings over a decade’s worth of experience in institutional research and advanced development from public, private, and academic sectors.

[Eric Nyberg](https://scholar.google.com/citations?hl=en&user=G6XN5cRm0FIJ&view_op=list_works)

Eric Nyberg

Coach, Master’s in Computational Data Science Program Director

Noted for his contributions to the fields of automatic text translation, information retrieval, and automatic question answering, Nyberg holds a Ph.D. from Carnegie Mellon University (1992) and a B.A. from Boston University (1983). He is a recipient of the Allen Newell Award for Research Excellence (for his contributions to the field of question answering and his work as an original developer on the Watson project) and the BU Computer Science Distinguished Alumna/Alumnus Award. Eric currently directs the Master of Computational Data Science (MCDS) program. He is also co-Founder and Chief Data Scientist at Cognistx, and serves on the Scientific Advisory Board for Fairhair.ai.

Past Contributors

Our Sponsors

Honda Research & Development

Honda Research & Development

The Power of Dreams

Honda Research & Development is supporting the 2021 Masters in Computational Data Science capstone research team and their efforts to bring the next generation of autonomous racing agents to the race track. For more information about Honda R&D, visit their website here.

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Maxim Integrated Products

Maxim Integrated Products

Empowering Design Innovation

Every day, electronic devices are becoming smarter with greater integration. Body sensors can monitor our health. Cars can drive themselves. Networked homes can power up when needed. At Maxim Integrated, we’re solving engineering problems and empowering design innovation, enabling our customers to create products that shape our world. Our innovative and high-performance analog and mixed-signal products and technologies make systems smaller and smarter, with enhanced security and increased energy efficiency.

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Contact Us

For information, media requests and sponsorship inquiries, please contact:
roborace-list [@] cs.cmu.edu

Carnegie Mellon University, School of Computer Science
5000 Forbes Ave
Pittsburgh, PA 15213