Suzan Anwar Data-verified

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Associate Professor and CS Department Chair

Last publication 2026 Last refreshed 2026-05-16

faculty

4 h-index 16 pubs 43 cited

Biography and Research Information

OverviewAI-generated summary

Dr. Suzan Anwar investigates the application of computer vision, machine learning, and data science techniques to address challenges in healthcare and cybersecurity. Her recent work includes developing systems for breast cancer diagnosis using rough set-ensemble classifiers and generating synthetic breast cancer datasets through autoencoders and generative adversarial networks. She has also explored the use of graph convolutional networks for pain detection via telehealth.

Dr. Anwar's research background includes high-performance computing and GPU performance monitoring during her time at Argonne National Laboratory and Lawrence Berkeley National Laboratory. She has secured funding from the NSF and NSA for DART seed and GenCyber programs. Her career objective is to cultivate data scientists and cybersecurity professionals to support national business growth. Dr. Anwar holds a Ph.D. in computer and information science from the University of Arkansas at Little Rock and is an Associate Professor and Department Chair of Computer Science at Philander Smith College.

Metrics

  • h-index: 4
  • Publications: 16
  • Citations: 43

Selected Publications

  • Graph-Based Pattern Irregularity Detection Using GNNs and Spectral Deep Learning (2026)
  • Breast Cancer Diagnosing System: Using a Rough Set-Ensemble Classifier Approach (2025)
    1 citation DOI OpenAlex
  • DeepFake Technology for Breast Cancer Dataset Generation Using Autoencoders and Deep Neural Networks (2025)
  • Breast Cancer Radiogenomics Data Generation Using Combined Generative Adversarial Networks GANs (2023)
  • Graph convolutional networks for pain detection via telehealth (2023)
    2 citations DOI OpenAlex
  • List of contributors (2023)

View all publications on OpenAlex →

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