EI2019 Short Course Description
NEW SC19: Developing Enabling Technologies for Automated Driving
Monday 14 January • 10:45 am – 12:45 pm
Course Length: 2 hours
Course Level: Introductory
Instructors: Forrest Iandola, Deepscale, Kurt Keutzer and Joseph Gonzalez, University of California, Berkeley
Fee*: Member: $185 /
Non-member: $210 /
Student: $65
*after December 18, 2018, members / non-members prices increase by $50, student price increases by $20
This course presents speakers covering the latest research on enabling-technologies for automated driving including sensors, perception, and motion planning and control.
Learning Outcomes
- Describe autonomous vehicle imaging challenges and constraints.
- Review the current limitations of real-time 3D imaging for automated driving.
- Understand emerging imaging technologies for autonomous vehicle imaging.
Intended Audience
Engineers, researchers, and software developers who develop automated driving imaging applications. The course assumes basic working knowledge concerning computer vision.
Dr. Forrest Iandola is an American computer scientist and entrepreneur. He is currently the CEO at Deepscale. Iandola earned his PhD in electrical engineering and computer science from the University of California, Berkeley , where his research focused on improving the efficiency of deep neural networks (DNNs). His best-known work includes deep learning infrastructure such as FireCaffe and deep models such as SqueezeNet and SqueezeDet. SqueezeNet, a lightweight deep neural network has been deployed on smartphones and other embedded devices. His advances in scalable training and efficient implementation of DNNs led to the founding of DeepScale, where he has been CEO since 2015. Iandola earned his BS in computer science from the University of Illinois at Urbana–Champaign.
Prof. Kurt Keutzer is a professor of electrical engineering and computer science at the University of California, Berkeley, and co-founder of Deepscale. Over the last decade his research group has focused on using parallel and distributed processing to accelerate machine learning, and more recently, deep learning, in its various applications in computer-vision, speech recognition, multimedia analytics, and computational finance. From November 2015, this research has been orchestrated to build superior perceptual systems for autonomous driving, commercialized in DeepScale. Kurt's research group has achieved significant speedups in machine learning (SVMs), computer vision, speech recognition, multimedia analytics, computational finance, and, most recently, training and deployment of deep neural networks. As a researcher, Kurt has published six books and over 200 refereed articles. As an entrepreneur, Kurt has been an investor and advisor to thirteen startups and an advisor to seven more.
Dr. Joseph Gonzalez is an assistant professor at the University of California, Berkeley and co-director of the UC Berkeley RISE Lab where he studies the design of algorithms, abstractions, and systems for scalable machine learning. Joseph also teaches the advanced data science class at UC Berkeley to over 600 students a semester and is helping to develop the new data science major. Before joining UC Berkeley, Joseph co-founded Turi Inc. (formerly GraphLab) to develop AI tools for data scientists and later sold Turi to Apple. Joseph holds a PhD in Machine Learning from Carnegie Mellon University.
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