Making Autonomous Driving more Reliable using Live 3D Digital Twins

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A live digital twin is a high-fidelity 3D representation of a physical object. This digital representation continuously replicates the physical object in real-time. My research vision is to build a live digital twin of the entire world. A live digital twin creates unprecedented capabilities for both computer and human consumption. It has the potential to improve safety and efficiency for autonomous driving, monitor on-going construction, and enable timely disaster relief operations etc. For humans, it means the possibility of digitally transporting to any place on the globe to live, interact and experience it in 3D like never before.

These capabilities have strict performance and accuracy requirements. Achieving these requirements is not possible today for two reasons: limited wireless bandwidths, and limited on-board compute resources. I will talk about how I have tackled these challenges in my research to build end-to-end systems that build live digital twins and consume them for safer and more reliable autonomous driving. I will also discuss how I plan to implement my vision for building a live digital twin of the world in future.

Brief Biography

Fawad Ahmad is a Ph.D. candidate in the Computer Science Department at the University of Southern California where he works with Prof. Ramesh Govindan. He received his undergraduate degree in Electrical Engineering from the University of Engineering and Technology, Peshawar (UETP) where he was the recipient of the Presidential Gold Medal. His research interests are in networks/systems, more specifically in mobile systems. During his Ph.D. he has interned at Microsoft Research and NEC Laboratories. He received the best paper runner-up award at MobiSys 2018. His work on autonomous vehicles was adopted by General Motors with two global patents. He was also the finalist for the Qualcomm Innovation Fellowship in 2019. 

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