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Monday, June 25, 2018 4:00 pm - 4:00 pm EDT (GMT -04:00)

Seminar • Artificial Intelligence — Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks

Abdullah Rashwan, PhD candidate
David R. Cheriton School of Computer Science

Sum-product networks have recently emerged as an attractive representation due to their dual view as a special type of deep neural network with clear semantics and a special type of probabilistic graphical model for which inference is always tractable. Those properties follow from some conditions (i.e., completeness and decomposability) that must be respected by the structure of the network. 

Monday, July 9, 2018 2:30 pm - 2:30 pm EDT (GMT -04:00)

Seminar • CrySP Speaker Series on Privacy — Where Theory Meets Practice for Privacy Enhancing Technologies

Chelsea Komlo, HashiCorp

​Privacy Enhancing Technology communities rely on the research community for help designing and validating protocols, finding potential attack vectors, and applying new technological innovations to existing protocols. However, while the research community has made significant progress studying projects such as Tor, the number of research outcomes that have actually been incorporated into privacy enhancing technologies such as The Tor Project is lower than the number of feasible and useful research outcomes. 

Tuesday, July 10, 2018 2:30 pm - 2:30 pm EDT (GMT -04:00)

Seminar • CrySP Speaker Series on Privacy — "Where's Waldo?" — Privacy in the Age of Internet-connected Mobile Technology

Matthew Finkel, The Tor Project

There are hundreds of millions of new "smart" mobile device users every year, but the mobile ecosystem and infrastructure are designed and built for optimizing convenience, not protecting the privacy of the user. From a design flaw in the Internet Protocol to an abundence of physical sensors, a mobile device may tell a third-party more information than the user intended or wanted. 

Thursday, July 12, 2018 10:30 am - 10:30 am EDT (GMT -04:00)

Seminar • Data Systems — Managing Big Multidimensional Data — A Journey from Data Acquisition to Prescriptive Analytics

Torben Bach Pedersen, Professor of Computer Science
Aalborg University

Data collected from new sources such as sensors and smart devices is large, fast, and often complex. There is a universal wish to perform multidimensional OLAP-style analytics on such data, i.e., to turn it into “Big Multidimensional Data.” Supporting this is a multi-stage journey, requiring new tools and systems, and forming a new, extended data cycle with models as a key concept. We will look at three specifics steps in this data cycle.

Friday, July 13, 2018 3:00 pm - 3:00 pm EDT (GMT -04:00)

Seminar • Software Engineering — The Prehistory and History of RE (+SE) as Seen by Me

Daniel M. Berry
David R. Cheriton School of Computer Science

Dan Berry weaves the twin peaks of (1) his life in computing, programming, programming languages, software engineering, electronic publishing, and requirements engineering with (2) the almost concurrent development of programming languages, software engineering, and requirements engineering.