World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
8152
World Ranking
12409
National Ranking
5032

Overview

Nesreen K. Ahmed is affiliated with Intel in the United States and has a significant body of research primarily in the field of Computer Science. Their work spans various subfields, with a strong focus on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Information Systems, and Electrical and Electronic Engineering.

Their research contributions are notably concentrated on topics including Advanced Graph Neural Networks, Complex Network Analysis Techniques, Topic Modeling, Natural Language Processing Techniques, Data Visualization and Analytics, Parallel Computing and Optimization Techniques, and Software Engineering Research.

Recent published papers by Nesreen K. Ahmed include:

  • Bias and Fairness in Large Language Models: A Survey (2024, Computational Linguistics)
  • Graph Neural Networks with Heterophily (2021, Proceedings of the AAAI Conference on Artificial Intelligence)
  • Role-Based Graph Embeddings (2020, IEEE Transactions on Knowledge and Data Engineering)
  • Deep graph similarity learning: a survey (2021, Data Mining and Knowledge Discovery)
  • On Proximity and Structural Role-based Embeddings in Networks (2020, ACM Transactions on Knowledge Discovery from Data)

Nesreen K. Ahmed has published extensively in venues such as arXiv (Cornell University), IEEE Transactions on Neural Networks and Learning Systems, ACM Transactions on Knowledge Discovery from Data, Companion Proceedings of the Web Conference 2020, and Zenodo (CERN European Organization for Nuclear Research).

Frequent collaborators include Ryan A. Rossi, Franck Dernoncourt, Sungchul Kim, Theodore L. Willke, and Namyong Park, reflecting a network of partnerships within their research community.

Best Publications

  • The network data repository with interactive graph analytics and visualization

    Ryan A. Rossi;Nesreen K. Ahmed

  • An empirical comparison of machine learning models for time series forecasting

    Nesreen K. Ahmed;Amir F. Atiya;Neamat El Gayar;Hisham El-Shishiny

  • Continuous-Time Dynamic Network Embeddings

    Giang Hoang Nguyen;John Boaz Lee;Ryan A. Rossi;Nesreen K. Ahmed

  • Bias and Fairness in Large Language Models: A Survey

    Unknown

  • Attention Models in Graphs: A Survey

    John Boaz Lee;Ryan A. Rossi;Sungchul Kim;Nesreen K. Ahmed

  • Efficient Graphlet Counting for Large Networks

    Nesreen K. Ahmed;Jennifer Neville;Ryan A. Rossi;Nick Duffield

  • Network Sampling: From Static to Streaming Graphs

    Nesreen K. Ahmed;Jennifer Neville;Ramana Kompella

  • Role Discovery in Networks

    Ryan A. Rossi;Nesreen K. Ahmed

  • Graph Neural Networks with Heterophily.

    Jiong Zhu;Ryan A. Rossi;Anup B. Rao;Tung Mai

  • Graph sample and hold: a framework for big-graph analytics

    Nesreen K. Ahmed;Nick Duffield;Jennifer Neville;Ramana Kompella

  • DistGNN: scalable distributed training for large-scale graph neural networks

    Vasimuddin;Sanchit Misra;Guixiang Ma;Ramanarayan Mohanty

  • Higher-order Network Representation Learning

    Ryan A. Rossi;Nesreen K. Ahmed;Eunyee Koh

  • Learning Role-based Graph Embeddings.

    Nesreen K. Ahmed;Ryan A. Rossi;John Boaz Lee;Xiangnan Kong

  • Graphlet decomposition: framework, algorithms, and applications

    Nesreen K. Ahmed;Jennifer Neville;Ryan A. Rossi;Nick G. Duffield

  • On sampling from massive graph streams

    Nesreen K. Ahmed;Nick Duffield;Theodore L. Willke;Ryan A. Rossi

  • Deep graph similarity learning: a survey

    Guixiang Ma;Nesreen K. Ahmed;Theodore L. Willke;Philip S. Yu

  • An Interactive Data Repository with Visual Analytics

    Ryan A. Rossi;Nesreen K. Ahmed

  • Deep Inductive Graph Representation Learning

    Ryan A. Rossi;Rong Zhou;Nesreen K. Ahmed

  • On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications

    Ryan A. Rossi;Di Jin;Sungchul Kim;Nesreen K. Ahmed

  • Role-based Graph Embeddings

    Nesreen Ahmed;Ryan Anthony Rossi;John Lee;Theodore Willke

  • Time-based sampling of social network activity graphs

    Nesreen K. Ahmed;Fredrick Berchmans;Jennifer Neville;Ramana Kompella

  • Network Sampling: Methods and Applications

    Mohammad Al Hasan;Nesreen K. Ahmed;Jennifer Neville

  • NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning

    Ameer Haj-Ali;Nesreen K. Ahmed;Ted Willke;Sophia Shao

Frequent Co-Authors

Nick Duffield
Nick Duffield Texas A&M University
Jennifer Neville
Jennifer Neville Purdue University West Lafayette
Xiangnan Kong
Xiangnan Kong Worcester Polytechnic Institute
Danai Koutra
Danai Koutra University of Michigan–Ann Arbor
Ion Stoica
Ion Stoica University of California, Berkeley
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Krste Asanovic
Krste Asanovic University of California, Berkeley
Michael W. Cole
Michael W. Cole Rutgers, The State University of New Jersey

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