When: Saturday December 2nd 2017 from 10:00am to 5:00pm
Where: CoMotion On King at 115 King Street East (3rd floor), Hamilton, ON
Cost: $20 regular, $10 student
HamOnt ML is only a couple weeks away now and more speakers are being added to the line-up each day – check out this opening keynote talk from Dr. Rong Zheng!
Professor, McMaster University
Mobile computing and machine learning: A happy marriage?
Significant progress has been made in recent years in applying machine learning in various applications. Today, predominantly, training of machine learning models and execution of inference tasks are done in the cloud due to the limited computation and storage capacity of mobile devices. However, such approaches are inadequate for latency sensitive tasks such as augmented reality and self-driven vehicles, or are too onerous when a large amount of data needs to be transferred over cellular data networks. In this talk, I will discuss ongoing projects in the Wireless System Research Group at McMaster university that develop machine learning algorithms for mobile applications and our efforts to make machine learning more amiable for mobile computing platforms.
Bio: Rong Zheng earned her Ph.D. degree from Dept. of Computer Science, University of Illinois at Urbana-Champaign. She is now an Associate Professor in the Dept. of Computing and Software, an associate member of the Dept. of Electrical and Computer Engr., and a member of the School of Computational Science and Engineering in McMaster University, Canada. Rong Zheng is a Joseph Ip Distinguished Engineering Fellow. She is a steering committe member of the MacData institute, which promotes collaboration among centers and researchers whose work involves different facets of data. Rong Zheng is also a principle investigator of the Computing Infrastructure Research Centre (CIRC).
Rong Zheng’s research interests include Cyber Physical Systems, mobile computing and networked systems. She received the National Science Foundation CAREER Award in 2006. Her research team has won many awards including the best paper award in IEEE Wireless Communications and Networking Conference, the best demo award from Cyber Physical Week 2015, and the first prize in infrastructure-less category in Microsoft Indoor Localization Competition in 2017.