How Machine Learning Powers the Connected Car

  • May 24, 2017
  • 6:30 PM - 8:00 CST
  • Lewis Towers, Floor 13, Beane Hall
  • Dr. Ronald Greenberg, rig@cs.luc.edu
  • free
  • all
     Open to the public.
  • http://chicagoacm.org
  • Add to calendar
  • Details

    The Ultimate Smart Driving Machine: How Machine Learning Powers the Connected Car
    Speaker 6:30
    Social time with light refreshments 5:45
    About the Talk:
    What is the state-of-the-art in the connected car industry, and what are the challenges and opportunities that big data and machine learning can address? Cars are now connected to the internet and car manufacturers are becoming more like software companies, shifting focus from traditional hardware platforms towards the software and services platform, leveraging scalable cloud computing with machine learning and IoT. Learn what BMW is doing with machine learning to address the challenges of journey management and integrating daily activities into the car.

    The car is not just about going from point A to point B anymore, but rather delivering a holistic experience that revolves around the activities in our daily lives. Car manufacturers are using big data, machine learning and AI to understand consumer behaviors, and preferences for specific cars that they like to drive. Your car may predict when you should leave for work and home, and learn which places you go often, to make the car become The Ultimate Smart Driving Machine.
    About the Speaker:
    Alvin Chin is a Senior Researcher in Machine Learning at BMW Technology Corporation, Chicago of the BMW Group. His research interests include connected car, machine learning, big data, mobile social networking, and ubiquitous computing. Dr. Chin has authored more than 30 publications and 10 patents, including pending. He received a PhD in Computer Science from the University of Toronto and previously worked for Nokia Research Center, Nokia and Microsoft in Beijing, China. He can be contacted at alvin.chin@bmwna.com and more about Dr. Chin can be found at his website http://www.alvinychin.com