Please ensure Javascript is enabled for purposes of website accessibility Faculty | Information Technology | University of West Florida
Skip to main content
Logo of University of West Florida
Maryam Taeb - 211

Dr. Maryam Taeb

Biography

Dr. Ramezanzadehmoghadam (Taeb) received her PhD in Electrical Engineering from the FAMU-FSU College of Engineering in 2024, her MS in Computer Science from Florida A&M University in 2021, and her BS in Computer Science from the University of Central Florida in 2019. She is currently an Assistant Professor at the University of West Florida. Maryam has extensive experience in large language models, generative AI, digital forensics and designing protocols to mitigate the spread of misinformation and authenticate evidence in court by leveraging Web3 and blockchain technology. Her research interests include generative AI, Vision Language Models, and their intersection with cybersecurity and human-computer interaction.

Degrees & Institutions

  • Ph.D. Electrical Engineering, FAMU-FSU College of Engineering
  • M.S. Computer Information Sciences, Florida A&M University
  • B.S. Computer Science, University of Central Florida

Research

Dr. Ramezanzadehmoghadam (Taeb)’s research interests lie at the intersection of large language models (LLMs), Vision Language Models, and their application within cybersecurity, Web3, and blockchain technologies. Her work explores the development and assessment of generative AI systems, focusing on the ethical implications and fairness in machine learning, especially concerning racial and gender biases. Dr. Ramezanzadehmoghadam (Taeb) investigates innovative approaches to deepfake detection and secure digital evidence acquisition, leveraging blockchain's decentralized architecture in digital forensic scenarios. Additionally, her research on AI-driven tools explores the security risks AI-generated code poses, further contributing to cybersecurity. Dr. Ramezanzadehmoghadam's (Taeb) work also addresses the societal impacts of AI, as demonstrated in her studies on anti-vaccination sentiment analysis and the inherent biases in models like BERT and ELECTRA. By integrating her expertise in human-computer interaction, Dr. Taeb is committed to advancing the responsible development of AI technologies that are not only innovative but also equitable and secure.

Current Courses

  • CIS5775 Cybersecurity Principles
  • CIS6394 Digital Forensics

Special Interests

  • Large Language Model (LLM)
  • Vision Language Models (VLM)
  • Cybersecurity for AI
  • Generative AI Data Security

Publications

  1. Taeb, Maryam, et al. "AXNav: Replaying Accessibility Tests from Natural Language." CHI conference on
    Human Factors in Computing Systems 11-16 May 2024
  2. Taeb, Maryam, Chi, Hongmei, Bernadin, Shonda. “Assessing the Effectiveness and Security Implications of
    AI Code Generators.” The Colloquium for Information Systems Security Education (CISSE 2023), Nov 1-3,
    2023
  3. Taeb, Maryam, Chi, Hongmei, Bernadin, Shonda. “Targeted Data Extraction and Deepfake Detection with
    Blockchain Technology.” International Conference on Universal Village (IEEE UV2022), Oct 22-25, 2022
  4. Taeb, Maryam, Torres, Yonathan, Chi, Hongmei, Bernadin, Shonda. “Investigating Gender and Racial Bias
    in ELECTRA.” International conference on Computational Science & Computational Intelligence (CSCI'22),
    Dec 14-16, 2022
  5. Elliston, J., Chi, H., Bernadin, S., & Taeb, M, “Integrating Blockchain Technology into Cybersecurity
  6. Taeb, M., & Bernadin, S, “Broadening Participation in URE Using PS-MMM-based Mentoring for URM
    Engineering Students.” The Chronicle of Mentoring & Coaching conference 2022, Oct 23-27, 2022
  7. Taeb, Maryam, Chi, Hongmei, Bernadin, Shonda (2022). “Digital Evidence Acquisition and Deepfake
    Detection with Decentralized Applications.” Practice and Experience in Advanced Research Computing
    (PEARC). July 10-14, 2022
  8. Taeb, Maryam, & Chi, Hongmei (2022). “Comparison of Deepfake Detection Techniques through Deep
    Learning.” Journal of Cybersecurity and Privacy, 2(1), 89-106.
  9. Taeb, Maryam, Chi, Hongmei, Yan, Jie, “Applying Machine Learning to Analyze Anti-vaccination on
    Tweets.” IEEE International Conference on Big Data (BDA COVID-2021), Dec 15-18, 2021
  10. Taeb, Maryam and Hongmei Chi, “A Personalized Learning Framework for Software Vulnerability Detection
    and Education.” 2021 International Workshop on Cyber Security (CSW) Aug 13-15, 2021
  11. Taeb, Maryam, Chi, Hongmei, Jones, Edward. L. et al. “Inherent Discriminability of BERT towards racial
    Minority Associated Data”, The 21st International Conference on Computational Science and Applications
    (ICCSA 2021), Sept 13-16, 2021
  12. A Ali, K Adjei, S Fatimah, K Ezendu, M Taeb, H Chi, C King, V Diaby, “Using Twitter to Examine Public
    Perceptions about COVID-19 in the United States: A Sentiment Analysis”, ISPOR, May 17-20
  13. Maryam Moghadam, “Vegetation Classification Using Lidar Data”, ACM Richard Tapia and Grace Hopper
    Celebration 2020 poster presenter.
  14. Maryam Moghadam, “Introduction to deep learning, from theory to practice” attended by the FAMU Vice
    President for federal Research 2020