Tentative Program:

13:30 – 13:45: Opening
Chairs: Nicole Immorlica and Stefan Schmid

13:45 – 15:00: Keynote Session
Chairs: Nicole Immorlica and Stefan Schmid

Keynote: Dana Randall
Co-Executive Director, Institute for Data Engineering and Science, and ADVANCE Professor of Computing, Georgia Tech

Phase Transitions and Emergent Phenomena in Random Structures and Algorithms
Markov chain Monte Carlo methods have become ubiquitous across science and engineering as a means of exploring large configuration spaces and modeling dynamics. The idea is to walk among the configurations so that even though you explore a very small part of the space, samples will be drawn from a desirable distribution. Over the last 20 years there have been tremendous advances in the design and analysis of efficient sampling algorithms for this purpose, largely building on insights from statistical physics. One of the striking discoveries has been the realization that many natural Markov chains undergo phase transitions, whereby they change from being efficient to inefficient as some parameter of the system is modified, also revealing interesting properties of the underlying random structures. In this talk, we will explore this phenomenon and show how insights from computing help us understand models from other fields, including segregation, colloids, and asynchronous models of programmable matter.

Dr. Dana Randall is a Co-Executive Director of the Institute for Data Engineering and Science at Georgia Tech, where she is also the ADVANCE Professor of Computing and an Adjunct Professor of Mathematics. Randall received her A.B. in mathematics from Harvard and her Ph.D. in computer science from the University of California at Berkeley. Her research in randomized algorithms and stochastic processes bridges computer science, discrete mathematics and statistical physics. Dr. Randall is a fellow of the American Mathematical Society and a National Associate of the National Academies. She has been an Alfred P. Sloan Fellow, a Kavli Fellow, received an NSF Faculty Early Career Development Award, and has received numerous awards for research, teaching and service. She chaired the Program Committees for the 2011 ACM/SIAM Symposium on Discrete Algorithms and the 2016 SIAM Conference on Discrete Mathematics, and recently was Director of the Algorithms and Randomness Center at Georgia Tech.  

15:00 – 15:30: Coffee Break

15:30-16:25: Session 1: Graphs and Topologies

Topology Inference of Multilayer Networks
Panagiotis A. Traganitis, Yanning Shen and Georgios B. Giannakis (University of Minnesota, USA)

Multiple Graph Abstractions for Parallel Routing over Virtual Topologies
Ahmet Soran (University of Nevada, Reno, USA); Murat Yuksel (University of Central Florida, USA); Mehmet Hadi Gunes (University of Nevada, Reno, USA)

Re-mapping the Internet: Bring the IXPs into Play
Pavlos Sermpezis and George Nomikos (FORTH, Greece); Xenofontas Dimitropoulos (FORTH-ICS, Greece)

16:30-17:25: Session 2: Dealing with Complexity

On the "Familiar Stranger'' Phenomenon in a Large-scale VoD System
Chen Zhang and Yuedong Xu (Fudan University, P.R. China); YiPeng Zhou (Shenzhen University, P.R. China); Xiaoming Fu (University of Goettingen, Germany)

Controlled Growth of Simplicial Complex Networks
Alexey Nikolaev (The Graduate Center, CUNY, USA); Saad Mneimneh (Hunter College, the City University of New York, USA); Amotz Bar-Noy (Brooklyn College & Graduate Center, CUNY, New York, USA); Ram Ramanathan (BBN Technologies, USA)

Predicted Max Degree Sampling: Sampling in Directed Networks to Maximize Node Coverage through Crawling
Ricky Laishram, Katchaguy Areekijseree and Sucheta Soundarajan (Syracuse University, USA)

17:25-17:30: Wrapup