Events

Topic : Internet of Things and Data Analytics for Good

Speaker: Prof. Xiaofan (Fred) Jiang (Columbia University)

Date: Monday, August 6th, 2018

Time: 10:30 - 12:00

Venue: R210, CSIE - DerTian Hall, NTU 臺灣大學 德田館 210會議室

Abstract

In this talk, I will present several recent projects at the Columbia Intelligent and Connected Systems Lab (ICSL) that combine Internet of Things (IoT) with data analytics to improve various aspects of our daily lives. The ePrints project combines large-scale building energy monitoring, indoor localization, and deep reinforcement learning to provide each occupant a real-time view of her own energy impact (energy footprint), as well as provide actionable recommendations for reduction. In the PAWS project, we combine custom IC design, wearable systems, and machine learning to localize vehicles on the road and warn pedestrians of potential dangers. Finally, the Intelligent Fabrics project uses conductive thread-based sensor together with data analytics for perspiration level monitoring.

Biography

Dr. Xiaofan (Fred) Jiang is an assistant professor in electrical engineering and computer engineering at Columbia University and co-Chair of Smart Cities Center at the Data Science Institute. Prof. Jiang received his Ph.D. in 2010 in Computer Science from UC Berkeley. He has been working on wireless embedded systems and smart buildings for the past 14 years. In 2008, he led one of the earliest projects in IP-based smart-buildings, paving the way for an information revolution in the building industry. At Microsoft Research, he developed a magnetic-based indoor localization system with an accuracy and consistency that is significantly better than the state of art. His recent work on low-power wearable systems demonstrated the potential of wearables for urban safety. He is actively serving on several technical and organizing committees including ACM SenSys, ACM/IEEE IPSN, and ACM BuildSys. He has published over 30 peer-reviewed papers, including Best Paper at IPSN ’05, Best Demo at SenSys ’11, Best Poster at BuildSys ’16, and Best Paper Runner-Up at BuildSys ’17.