News & Events

CS Colloquium Friday, April 07 – Rik Sengupta, UMass Amherst

Friday, April 07 @ 2:35pm Wege Auditorium (TCL 123) Graphical Fair Allocations of Indivisible Goods In the EconCS community, the theory of fair allocations of indivisible goods is of rapid growing interest. For instance, the desirable condition of *envy-freeness* (EF) cannot be achieved in general, so relaxed fairness notions such… Continue reading »

Colloquium 3/10 – Graduate School Discussion

Computer Science Colloquium Graduate School Panel March 10 @ 2:35pm Wege Auditorium (TCL 123)   Thinking about graduate school? CS faculty will discuss everything you need to know about graduate school including; deadlines, personal statements, finding an advisor, research, application process, and choosing the right school. Colloquium credit… Continue reading »

Colloquium 12/09 – Amy Babay, University of Pittsburg

Computer Science Colloquium Friday, December 09 2:35pm in Wege Auditorium   Toward Intrusion-Tolerant Critical Infrastructure As critical infrastructure systems are becoming increasingly exposed to malicious attacks, it is crucial to ensure that they can withstand sophisticated attacks while continuing to operate correctly and at their expected level of performance. In this talk,… Continue reading »

Colloquium 12/02 – Sean Barker ’09, Bowdoin College

Computer Science Colloquium Friday, December 02 2:35pm in Wege Auditorium   Smart Meters for Smart Cities: Data Analytics in Energy-Aware Buildings The proliferation of smart energy meters has resulted in many opportunities for next-generation buildings.  Energy-aware “smart buildings” may optimize their energy consumption and provide convenience and economic benefits through… Continue reading »

Colloquium November 18 – Daniel Malinsky, Columbia University

Computer Science Colloquium Friday, November 18 2:35pm in Wege Auditorium   Identifying Causal Determinants of Clinical Outcomes from Electronic Health Records Using Graphical Structure Learning: Challenges and Opportunities in Causal Discovery Many goals within causal inference, including estimating average treatment effects and understanding path-specific mechanisms, depend on knowing the qualitative causal structure underlying a domain. Continue reading »