The submission is open until August 18, 2017. Please consider submitting your papers to AIPR2017. ****All registered papers will be published in publisher's Digital Library.**** BEST registered papers will be published in one of the special issues listed in the website provided that the author do major improvements and extension within the time frame set by the conference and his/her paper is approved by the chief editor. =================================================================================================

12th IEEE International Symposium on Industrial Embedded Systems (SIES 2017) June 7-9, 2017 | Toulouse, France | Web site: http://sies2017.onera.fr

Sanjit A. Seshia is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He received an M.S. and Ph.D. in Computer Science from Carnegie Mellon University, and a B. Tech. in Computer Science and Engineering from the Indian Institute of Technology, Bombay. His research interests are in dependable computing and computational logic, with a current focus on applying automated formal methods to problems in cyber-physical systems, computer security, electronic design automation, and synthetic biology. His Ph.D.

Multi-timescale electricity markets augment the traditional electricity market by enabling consumers to procure electricity in a futures market. Heavy power consumers, such as cloud providers and data center operators, can significantly benefit from multi-timescale electricity markets by purchasing some of the needed electricity ahead of time at cheaper rates.

Large scale deployment of connected and automated vehicles is impeded by significant technical and scientific gaps, especially when it comes to achieving real-time and high accuracy situational awareness for cooperating vehicles. This CAREER project aims at closing these gaps through developing fundamental information networking methodologies for coordinated control of automated systems. These methodologies are based on the innovative concept of modeled knowledge propagation. The approach is to utilize the novel concepts of model communication and its derived multi-resolution networking.

The objective of this proposal is to exploit an early concept of a flexible, low-cost, and drone-carried broadband long-distance communication infrastructure and investigates its capability for immediate smart-city application in emergency response.