Artificial Intelligence for Autonomous Driving

Abstract

Autonomous driving is one of the fastest-growing industries leveraging artificial intelligence solutions. Autonomous driving has been using a suite of modalities like cameras, LiDARs, RADARs, microphones, ultrasonics, city-traffic data, and everything around in order to bring autonomous cars to a boring reality. This panel will bring together experts in the field of AI for autonomous driving to discuss the frontiers of Perception; the field of distilling sensor data into representations understandable by the autonomy stack. The panel is comprised of a diverse group with several years of experience in building robots and complex perception systems for the purpose of autonomous passenger vehicles and delivery robots. This panel will discuss challenges to developing a scalable, safe, and ethical perception system for the future. Topics will include, but are not limited to long tail problems in autonomous driving, data mining, perception architectures, ML Infrastructure, and future technologies, among others. The panelists will provide their viewpoint not only from a performance perspective but from the lens of an experienced practitioner balancing reliability with practical computing considerations. This is an excellent opportunity for attendees to gain a deeper understanding of the latest advancements in AI for autonomous driving and the pivotal role it will play in reshaping our transportation landscape.

Date
Jun 6, 2023 11:00 AM
Location
2023 IEEE CAI AI for AD Panel
Santa Clara, California, USA

I was invited as a panelist for the ‘Artificial Intelligence for Autonomous Driving’ panel discussion on IEEE Conference on Artificial Intelligence 2023.

Aleksandr Petiushko Александр Петюшко
Aleksandr Petiushko Александр Петюшко
Director, Head of ML Research / Adjunct Professor / PhD

Principal R&D Researcher (15+ years of experience), R&D Technical Leader (10+ years of experience), and R&D Manager (7+ years of experience). Running and managing industrial research and academic collaboration (35+ publications, 30+ patents). Inspired by theoretical computer science and how it changes the world.