I am a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, TEES Research Professor, and Director of the Texas A&M Institute of Data Science. My research combines the foundations and applications of data science and computer networking, currently graph stream sampling, network measurement and resilience, and applications of data science to transportation and hydrology.
Further information about my work
- Personal webpage including publications, patents, standards, funding, awards
- Google Scholar (H-index 63 from over 16,000 citations)
- DBLP; MathSciNet; US Patent and Trademark Office
Positions available
- NSF Funded PhD assistantship in graph data stream sampling and learning
- Postdoc position in applications of data science to transportation or agriculture
If you are interested in either of these positions, please send me email including resume, transcripts, and a statement of your interest in the position.
Recent news
- Sep 2019: Paper: Variational Graph Recurrent Neural Networks accepted to NeurIPS
- Sep 2019: Paper: Semi-Implicit Graph Variational Auto-Encoders accepted to NeurIPS
- Aug 2019: NSF Award: Planning Grant: Engineering Research Center for AI in Construction (AI-Con)
- Aug 2019: Preprint: Optimizing Consistent Merging and Pruning of Subgraphs in Network Tomography
- Aug 2019: Preprint: Network Shrinkage Estimation
- Jul 2019: NSF Award CC* Team SWEETER for regional expertise in computational and data sciences
- Jul 2019: Texas A&M Data Science Bootcamp announced for August 2019
- Jul 2019: HDR-Nets2019, Workshop on Harnessing the Data Revolution in Networking at ICNP’19
- Jul 2019: Paper: Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs, accepted to Operations Research
- Jul 2019: Paper: Gap Filling of High-Resolution Soil Moisture accepted to Water Resources Research
- Jun 2019: Completion of ACM Sigmetrics / IFIP Performance 2019 as TPC Co-Chair. Thanks to all authors, TPC members and organizers!
- Jun 2019: Paper: Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games accepted to KAIS
- Jun 2019: Preprint: Piecewise Stationary Modeling of Random Processes Over Graphs With an Application to Traffic Prediction
- Apr 2019: TAMIDS Workshop on Data Science/AI/ML in Education
- Mar 2019: Paper: Real-Time Streaming Graph Embedding Through Local Actions accepted to DL4G-SDE
- Feb 2019: TAMIDS Workshop on Operational Data Science
- Feb 2019: Patent: 10,192,547: System and method for customized voice response
- Jan 2019: Venturebeat news item on our ICDM paper on churn prediction for mobile games
- Oct 2018: Announced as Director of Texas A&M Institute of Data Science
- Sep 2018: NSF Grant 1808551 Awarded: Real-Time Learning-Mediated Control for Traffic Shaping
- Aug 2018: Paper: A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games accepted for ICDM 2018
- Aug 2018: New Grant Awarded: Advanced Traffic Analysis For Network Virtualization
- Aug 2018: NSF Grant 1848596 Awarded: Adaptive Sampling of Massive Graph Streams
- Aug 2018: PhD student Yixiao Feng completes his internship at Regeneron Pharmaceuticals
- Jul 2018: Research Visit to Mathematical Institute, Oxford, UK
- Apr 2018: Paper: Sampling for Approximate Bipartite Network Projection accepted to IJCAI-ECAI-2018
- Apr 2018: TPC Co-Chair for ACM Sigmetrics / Performance 2019
- Apr 2018: TPC for IEEE BigData 2018
- Apr 2018: Preprint: Graph Reconstruction from Path Correlation Data
- Apr 2018: PhD student Hanzi Mao will intern this summer at Pinterest
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