Minlan Yu (Yale) and I  have received an NSF NeTS award for our proposal Distributed Approximate Packet Classification.

Our paper Graphlet Decomposition: Framework, Algorithms, and Applications by Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick Duffield & Theodore L. Willke has been accepted to appear in Knowledge and Information Systems

Our paper On the Tradeoff between Stability and Fit, by E. Cohen, G. Cormode, N. Duffield &  C. Lund has been accepted to appear in the ACM Transactions on Algorithms

I visited Intel Research in Santa Clara CA for 4 weeks during  June and July to continue my collaboration with Nesreen Ahmed on Graph Stream Sampling. I August I briefly visited the Oxford-Man Institute for Quantitative Finance to continue my collaboration with Weijun Xu and Ni Hao on Rough Paths analysis.

The 2nd Texas A&M Big Data Workshop was held on February 12, 2016. Dilma Da Silva and I organized this event with the aim of promoting interdisciplinary collaboration in Big Data at Texas A&M.

There are openings in my group for PhD students in two projects in Interdisciplinary Big Data Research:

• Big Data in Transportation: this project concerns the use of location data originating from mobile devices to understand the impacts of congestion and other events in the transportation system. It will involve both developing algorithms for efficient summarization and mobility data, and developing data driven models of event propagation. This is a collaborative project with the Texas A&M Transportation Institute.
• Big Data in Multi-Scale Hydrology: this project concerns the fusion of ground based sensor data an satellite data relating to soil moisture, including using data machine methods to align features across datasets, detect measurement anomalies, and develop predictive models across spatial scale incorporate domain knowledge of the underlying hydrological processes. This is a collaborative project with Prof. Binayak Mohanty in the Department of Biological and Agricultural Engineering.

If you are interested in working in either of these projects, please send me email, including your resume.

There is a postdoc opening in my group to work on a project concerning algorithms for summarizing large and complex datasets and streaming graph data in particular. Someone who has a strong background in algorithms for data science and an interest in both creating and applying them would be a great fit for this position. Some of our recent work in this area is listed here. Please contact me if you have questions. Applications take place through the position listing.

I have received a research award for the project DEDUCE: Distributed Enclave Defense Using Configurable Edges, funded by DARPA’s Edge-Directed Cyber Technologies for Reliable Mission program.  The project is led by Applied Communication Sciences with partnership from Apogee Research, the Massachusetts Institute of Technology, the University of Pennsylvania and Texas A&M University. This project will extend and apply my work in Network Tomography, in which end–to-end performance measurements between network edges can be correlated to identify common origins of performance degradation. In DEDUCE, this information will be used to inform strategies for alternate routing on an overlay network between enclaves. Further details can be found in the Texas A&M announcement.

I spent July visiting Terry Lyons, director of the Oxford-MAN Institute of Quantitative Finance, and interacting with several of his current and former postdocs, including Ni Hao, Guy Flint, and Weijun Xu (now at Warwick). We are looking to developing applications of Rough Paths to problems in (big) data analysis.

PhD Student Yunhong Xu spent July on a collaboration visit with Prof. Minlan Yu and her student Hao Wu at the University of Southern California and her student Hao Wu, to work on our project in Measurement in Software Defined Networking.

Nesreen Ahmed will present our paper Efficient Graphlet Counting for Large Networks, by N. Ahmed, J. Neville, R. Rossi, N.Duffield, at the 2015 IEEE International Conference on Data Mining.