2026 Mark Coates: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	47	6508	6319	259	246	209	8721

Overview

Mark Coates is affiliated with McGill University in Canada and has produced a substantial body of research primarily within the field of Computer Science. Their work encompasses a diverse range of subfields including Artificial Intelligence, Information Systems, Signal Processing, Computer Vision and Pattern Recognition, and Statistics and Probability.

Their contributions cover multiple main topics and areas of research interest such as:

Advanced Graph Neural Networks
Recommender Systems and Techniques
Time Series Analysis and Forecasting
Topic Modeling
Machine Learning and Algorithms
Complex Network Analysis Techniques
Traffic Prediction and Management Techniques

Mark Coates has published extensively with a notable concentration in the following venues:

arXiv (Cornell University)
Proceedings of the AAAI Conference on Artificial Intelligence
IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology
2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)
IEEE Transactions on Visualization and Computer Graphics

Frequent collaborators include:

Yingxue Zhang
Soumyasundar Pal
Florence Regol
Antonios Valkanas
Chen Ma

Representative recent papers by Mark Coates include:

Memory Augmented Graph Neural Networks for Sequential Recommendation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
Microwave Breast Screening Prototype: System Miniaturization With IC Pulse Radio, 2020, IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction, 2021, 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)

Best Publications

Network Tomography: Recent Developments

Rui Castro;Mark Coates;Gang Liang;Robert Nowak

656
Citations
Distributed particle filters for sensor networks

Mark Coates

394
Citations
Distributed Average Consensus With Dithered Quantization

T.C. Aysal;M.J. Coates;M.G. Rabbat

349
Citations
Maximum likelihood network topology identification from edge-based unicast measurements

Mark Coates;Rui Castro;Robert Nowak;Manik Gadhiok

325
Citations
Multifractal Cross-Traffic Estimation

Vinay Joseph Ribeiro;Mark J. Coates;Rudolf H. Riedi;Shriram Sarvotham

298
Citations
Network Loss Inference Using Unicast End-to-End Measurement

Mark J. Coates;Robert David Nowak

266
Citations
Network delay tomography

Yolanda Tsang;M. Coates;R.D. Nowak

235
Citations
Memory Augmented Graph Neural Networks for Sequential Recommendation

Chen Ma;Liheng Ma;Yingxue Zhang;Jianing Sun

221
Citations
An Early Clinical Study of Time-Domain Microwave Radar for Breast Health Monitoring

Emily Porter;Mark Coates;Milica Popovic

218
Citations
Multivariate Online Anomaly Detection Using Kernel Recursive Least Squares

T. Ahmed;M. Coates;A. Lakhina

216
Citations
Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification

Yingxue Zhang;Soumyasundar Pal;Mark Coates;Deniz Ustebay

212
Citations
Machine learning approaches to network anomaly detection

Tarem Ahmed;Boris Oreshkin;Mark Coates

184
Citations
Neighbor Interaction Aware Graph Convolution Networks for Recommendation

Jianing Sun;Yingxue Zhang;Wei Guo;Huifeng Guo

164
Citations
Time-Domain Multistatic Radar System for Microwave Breast Screening

E. Porter;E. Kirshin;A. Santorelli;M. Coates

161
Citations
Radio-Frequency Tomography for Passive Indoor Multitarget Tracking

Santosh Nannuru;Yunpeng Li;Yan Zeng;Mark Coates

152
Citations
Multiple source, multiple destination network tomography

M. Rabbat;R. Nowak;M. Coates

148
Citations
Likelihood based hierarchical clustering

R.M. Castro;M.J. Coates;R.D. Nowak

146
Citations
Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements

Xi Chen;Andrea Edelstein;Yunpeng Li;Mark Coates

146
Citations
Distributed Average Consensus using Probabilistic Quantization

Tuncer C. Aysal;Mark Coates;Michael Rabbat

144
Citations
Optimization and Analysis of Distributed Averaging With Short Node Memory

Boris N Oreshkin;Mark J Coates;Michael G Rabbat

142
Citations
Epidemiological Modelling of Peer-to-Peer Viruses and Pollution

R. Thommes;M. Coates

138
Citations

Frequent Co-Authors

Michael Rabbat Facebook (United States)

Robert Nowak University of Wisconsin–Madison

Xue Liu McGill University

Xiuqiang He Huawei Technologies (China)

Richard G. Baraniuk Rice University

Peter Henderson University of Oxford

Arnaud Doucet University of Oxford

Anna Scaglione Cornell University

Henry Leung University of Calgary

Michael Gastpar École Polytechnique Fédérale de Lausanne

External Links

Personal website of Mark Coates Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Pursuing Computer Science in the USA opens doors to a variety of academic and professional options. If you are still exploring your educational journey, it's helpful to learn about majors in college that align with your interests in technology and innovation.

For those seeking a more flexible learning path, online degrees have become increasingly popular. Professionals looking to balance work and study might consider the easiest online master's degree options, which can help enhance skills and credentials without overwhelming time commitments.

If advanced research or academic positions interest you, finding the most affordable online doctoral programs can make pursuing a doctorate more manageable financially. Similarly, those aiming for leadership in education may explore the cheapest edd degrees with fast-track completion options.

Exploring these online degrees and career pathways can help you achieve your professional goals in computer science while managing time and financial resources effectively.