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How Machine Learning Powers the Connected Car
May 24 @ 5:45 pm
The Ultimate Smart Driving Machine: How Machine Learning Powers the Connected Car
Speaker: Dr. Alvin Chin, Senior Researcher, BMW Technology Corporation, BMW Group
Wednesday, May 24, 2017
5:45 pm (Social Hour, light refreshments)
6:30 pm Presentation
Loyola University Water Tower Campus (Chicago/Michigan Area)
111 E. Pearson Street, Chicago IL 60611
Beane Ballroom (13th Floor, Lewis Towers)
Admission: Free, General Admission, open to the public
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.
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.
Keywords: BMW, IoT, Machine Learning, Big Data, Computer Science, University of Toronto, Nokia, Microsoft, Smart Vehicles