Abstract: Artificial intelligence and machine learning are critical to reaching full autonomy in self driving cars.  I will present two autonomy systems along with the use of machine learning in each of them.  I will summarize recent progress in commercializing these systems and make some observations about the potential impact of these systems in our daily life.  Some of the biggest remaining challenges include efficiently solving the long tail of unusual events on the road, scaling up from demos to commercially viable systems, and verifying the safety of these AI-based systems.  I will finish with thoughts on addressing those issues.

Brief Bio: Dr. Jeff Schneider is a research professor in the Carnegie Mellon University School of Computer Science where his recent research is on machine learning for autonomous systems.  He received his PhD in Computer Science from the University of Rochester.  He has over 20 years experience developing, publishing, and applying machine learning algorithms in government, science, and industry.  He has over one hundred publications and has given numerous invited talks and tutorials on the subject. Jeff is also an entrepreneur.  He was a founding member of Uber’s Advanced Technologies Group and spent three years helping to build their self driving car program.  Before that, he developed a machine learning based CNS drug discovery system and commercialized it during two years as Psychogenics’ Chief Informatics Officer.  Earlier in his career he was the co-founder and CEO of Schenley Park Research, a company dedicated to bringing machine learning to industry.  Through his research, commercial, and consulting efforts, he has worked with dozens of companies and government agencies around the world.

For more information: Stephanie Matvey (smatvey@andrew.cmu.edu)