• Professor, Electrical & Computer Engineering
  • Royce E. Wisenbaker Professor I
  • Director, Texas A&M Institute of Data Science
  • Affiliated Faculty, Computer Science & Engineering
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Nick Duffield

Educational Background

  • B.A., The University of Cambridge, UK – 1982
  • M.Math., The University of Cambridge, UK – 1983
  • Ph.D., The University of London, U.K. – 1987

Research Interests

  • 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 in communications networks and beyond. 

Awards & Honors

  • ACM Fellow
  • IET Fellow
  • IEEE Fellow
  • AT&T Fellow
  • Co-recipient of the ACM Sigmetrics Test of Time Award in both 2012 and 2013 for work in Network Tomography

Selected Publications

  • Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs, David S. Johnson, Lee Breslau, Ilias Diakonikolas, Nick Duffield, Yu Gu, MohammadTaghi Hajiaghayi, Howard Karloff, Mauricio G. C. Resende, Operations Research, 2020
  • Semi-Implicit Stochastic Recurrent Neural Networks, Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
  • Variational Graph Recurrent Neural Networks, by Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian, Neural Information Processing Conference (NeurIPS), 2019
  • Semi-Implicit Graph Variational Auto-Encoders, by Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian, Neural Information Processing Conference (NeurIPS), 2019
  • Gap Filling of High‐Resolution Soil Moisture for SMAP/Sentinel‐1: A Two‐Layer Machine Learning‐Based Framework, by Hanzi Mao, Dhruva Kathuria, Nick Duffield, Binayak P. Mohanty, Water Resources Research, 2019
  • Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games, by Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang,. Knowledge and Information Systems, 2019
  • Piecewise Stationary Modeling of Random Processes Over Graphs With an Application to Traffic Prediction , A. Hasanzadeh, X. Liu, N. Duffield and K. R. Narayanan, IEEE International Conference on Big Data (Big Data), 2019
  • A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games, Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, and Na Wang, IEEE International Conference on Data Mining (ICDM), 2018
  • Graph Reconstruction from Path Correlation Data, G. Berkolaiko, N. Duffield, M. Ettehad, K. Manouskais, Inverse Problems, 2018
  • Sampling for Approximate Bipartite Network Projection by Nesreen Ahmed, Nick Duffield, Liangzhen Xia, International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI), 2018
  • Stream Aggregation Through Order Sampling by Nick Duffield, Yunhong Xu, Liangzhen Xia, Nesreen Ahmed, Minlan Yu, Conference on Knowledge and Information Management (CIKM), 2017
  • On Sampling from Massive Graph Streams, Nesreen K. Ahmed, Nick Duffield, Theodore Willke, Ryan A. Rossi, Proceedings Very Large Databases (PVLDB), 2017
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