Nick Duffield

Professor | Royce E. Wisenbaker Professorship I | Director, Texas A&M Institute of Data Science
Contact

Biography

I am a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, holder of the Royce E. Wisenbaker Professorship I, 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. I am an ACM Fellow, IEEE Fellow, AT&T Fellow and IET Fellow, and was a co-recipient of the ACM Sigmetrics Test of Time Award in both 2012 and 2013 for work in Network Tomography.

Further information about my work

Positions available

Positions available

Jobs at the Texas A&M Institute of Data Science

Recent news

See TAMIDS webpage for more recent news. Sep 2002: Paper: Rapid Damage Estimation of Texas Winter Storm Uri from Social Media Using Deep Neural Networks, appeared in Urban Science Jul 2022: Paper: Hashing Design in Modern Networks: Challenges and Mitigation Techniques, appeared in Usenix ATC Jun 2022: Talk: Keynote at ACM Sigmetrics / IFIP Performance 2022 Jun 2022: Paper: Multiscale Energy Network Tomography, to appear in IFIP Networking May 2022 Paper: Revealing the linguistic and geographical disparities of public awareness to Covid-19 outbreak through social media, appeared in International Journal of Digital Earth Feb 2022: THECB Award: Texas A&M University System Consortium for Graduate Data Science Credentialing Jan 2022: Paper: MoReL: Multi-omics Relational Learning, accepted to ICLR 2022. Jan 2022: Paper: Visual Recognition for Urban Traffic Data Retrieval and Analysis in Major Events Using Convolutional Neural Networks, appeared in Computational Urban Science Dec 2021: Paper: SmartWatch: Accurate Traffic Analysis and Flow-state Tracking for Intrusion Prevention using SmartNICs, appeared in CoNext 2021 Nov 2021: Paper: A time-series clustering algorithm for analyzing the changes of mobility pattern caused by COVID-19, appeared at HANIMOB ’21: Proc. 1st ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility Nov 2021: Paper: Mentoring in Artificial Intelligence and Materials Science: Applying a New Doctoral Model, appeared in The Chronicle of Mentoring and Coaching, Oct 2021: Preprint: Revealing the Global Linguistic and Geographical Disparities of Public Awareness to Covid-19 Outbreak through Social Media Sep 2021: NIH Award: Maximizing Student Development in Data and Information Science-Related Disciplines for Biomedical PhD Trainees Sep 2021: NIST Award: Creating a Shared Public Safety Radio Data Set for Sharing and Analysis, National Institute of Standards and Technology Sep 2021: TWRI Award: Development of an Unmanned Aerial System (UAS)-based System to Improve Water Use Efficiency of Cotton by Monitoring Crop Water Use and Biomass Accumulation Aug 2021:Congratulations to Yixiao Feng on his PhD graduation, and best wished for success at Facebook! Aug 2021: Microsoft Award under AI for Humanitarian Action Program Jun 2021: Paper: Online Sampling of Temporal Networks appeared in ACM Trans. Knowl. Discov. Data Sep 2020: Paper: Adaptive Shrinkage Estimation for Streaming Graphs, accepted to NeurIPS 2020 Sep 2020: Paper: BayReL: Bayesian Relational Learning for Multi-omics Data Integration, accepted to NeurIPS 2020 Aug 2020: Paper: Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis, accepted to ICDM 2020 Jul 2020: Paper: A SmartNIC-Accelerated Monitoring Platform for In-band Network Telemetry, appeared at IEEE LANMAN 2020 Jul 2020: Online Workshop: AI Applications to Agriculture Jun 2020: PhD student Yixiao Feng interned at Facebook Jun 2020: Congratulations to Mahmood Ettehad on passing his PhD thesis exam! Jun 2020: Congratulations to Ruihong Wang on passing his MS thesis exam! May 2020: Paper: Bayesian Graph Neural Networks with Adaptive Connection Sampling, accepted to ICML 2020 May 2020: Congratulations to Hanzi Mao on passing her PhD thesis exam! May 2020: Congratulations to Yunhong Xu on her PhD graduation! Mar 2020: Paper: Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs, appeared in Operations Research Jan. 2020: Paper, Semi-Implicit Stochastic Recurrent Neural Networks, accepted to ICASSP 2020 Oct. 2019: Preprint: Temporal Network Sampling Sept..2019: NSF Award: HDR Tripods: Texas A&M Research Institute for Foundations of Interdisciplinary Data Science (FIDS) Sept..2019: Paper: Variational Graph Recurrent Neural Networks accepted to NeurIPS Sept..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 July 2019: NSF Award CC* Team SWEETER for regional expertise in computational and data sciences July 2019: Texas A&M Data Science Bootcamp announced for August 2019 July 2019: HDR-Nets2019, Workshop on Harnessing the Data Revolution in Networking at ICNP’19 July 2019: Paper: Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs, accepted to Operations Research July 2019: Paper: Gap Filling of High-Resolution Soil Moisture accepted to Water Resources Research June 2019: Completion of ACM Sigmetrics / IFIP Performance 2019 as TPC Co-Chair. Thanks to all authors, TPC members and organizers! June 2019: Paper: Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games accepted to KAIS June 2019: Preprint: Piecewise Stationary Modeling of Random Processes Over Graphs With an Application to Traffic Prediction April 2019: TAMIDS Workshop on Data Science/AI/ML in Education March 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 Sept. 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 July 2018: Research Visit to Mathematical Institute, Oxford, UK April 2018: Paper: Sampling for Approximate Bipartite Network Projection accepted to IJCAI-ECAI-2018 April 2018: TPC Co-Chair for ACM Sigmetrics / Performance 2019 April 2018: TPC for IEEE BigData 2018 April 2018: Preprint: Graph Reconstruction from Path Correlation Data April 2018: PhD student Hanzi Mao will intern this summer at Pinterest

Teaching

 

Most recent course versions

Research Opportunities

 

View research opportunities (13 entries)

Positions Available

If you are interested in either of these positions, please send me an e-mail including your resume, transcripts, and a statement of your interest in the position.

Graduate Student Research

I am currently advising students at the PhD and MS level in graph summarization, network resilience, and applications of data science to transportation and hydrology. I expect to have further openings in these areas. My primary appointment is in Electrical and Computer Engineering, but I also advise students in Computer Science and Engineering (where I have a courtesy appointment) and in the Interdisciplinary PhD program in Mathematics. Applications for graduate study are handled at the departmental level. If you are an interested in joining my group, you should apply to the department and let me know by e-mail so that I can look for your application.

Research Areas

Suggested Preparatory Graduate Courses

  • ECEN 758 Data Mining and Analysis
  • ECEN 748 Data Stream Algorithms and Applications
  • ECEN 602 Computer Communications and Networking
  • CSCE 629 Analysis of Algorithms

Advising

  • I act as primary adviser for graduate students in ECEN and CSCE.
  • I currently also advise in the MATH Interdisciplinary PhD program.

Financial Support

  • PhD students: RA support may be available for students working on specific research projects. Some TA support is available to students in the ECEN and CSCE departments.

Research Focus

My research focuses on data and network science, particularly applications of probability, statistics, algorithms and machine learning to the acquisition, management and analysis of large datasets. I am an ACM Fellow, IEEE Fellow, and IET Fellow, and I was a co-recipient of the ACM Sigmetrics Test of Time Award in both 2012 and 2013 for work in Network Tomography.

Current Roles

Contact

Personal Web Page: nickduffield.net/work
Admin Contact (TAMIDS): Jennifer South, jsouth@tamu.edu