*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Overview:
At its best, intelligence creates aesthetic and beauty, yet from a utilitarian perspective intelligence primarily serves the purpose of making better decisions. Today's prescriptive decision support systems are most effective when applied to specific recurring operational problems. Recent advances in AI technology have revived the vision of commercially viable cooperative strategic decision support systems. These cognitive systems integrate information retrieval, knowledge representation, interactive modelling, as well as social and self-learning capabilities with logic reasoning and probabilistic decision making under uncertainty. I provide a snapshot of the current technology status by showcasing several projects that ultimately aim at intelligent human-in-the-loop decision making.
Bio:
Meinolf Sellmann is the senior manager for cognitive data curation at IBM Watson Research. He received his doctorate degree from Paderborn University. From there, he went to Cornell University as a postdoctoral associate and afterwards became an assistant professor at Brown University. Dr. Sellmann has published more than 70 articles at international conferences and in journals with central contributions in symmetry breaking, global constraints, the integration of mathematical and constraint programming, search, autonomous algorithm configuration, and algorithm portfolios.
He serves as PC chair of LION 2016 and CPAIOR 2013, conference chair of CP 2007, and associate editor of the "Informs Journal on Computing." He received an NSF Early Career Award in 2007, IBM Outstanding Technical Innovation Awards in 2013 and 2014, and an IBM Business Accomplishment in 2015. Based on their meta-algorithmic research, for five consecutive years, Dr. Sellmann and his team won at international SAT and MaxSAT solver competitions, among others for the overall most efficient parallel SAT Solver in 2013, and thirteen first places at the 2013-2015 MaxSAT Evaluations.
