Mohammadreza (Reza) Ebrahimi
Mohammadreza (Reza) Ebrahimi is an assistant professor at School of Information Systems and Management and the lead of Star-AI Lab at the University of South Florida.
Reza’s current research is focused on statistical and adversarial machine learning for AI-enabled secure and trustworthy cyberspace. He leverages a wide range of statistical learning theories, including Transductive Learning, Transfer Learning, Adversarial Learning, and Deep Reinforcement Learning. Reza’s dissertation on AI-enabled cybersecurity analytics won the ACM SIGMIS best doctoral dissertation award in 2021. Reza has published over 25 articles in peer-reviewed security journals, conferences, and workshops, including IEEE TPAMI, Applied Artificial Intelligence, Digital Forensics, MIS Quarterly, JMIS, IEEE S&PW, AAAI Workshop, IEEE ICDMW, and IEEE ISI. He has been serving as a Program Chair and Program Committee member in IEEE ICDM Workshop on Machine Learning for Cybersecurity and IEEE S&P Workshop on Deep Learning and Security. He has contributed to several projects supported by the National Science Foundation. He is a member of the IEEE, ACM, AAAI, and AIS.
Ebrahimi received his PhD in information systems from the University of Arizona, where he was a research assistant at the Artificial Intelligence Lab directed by Regents’ Professor Hsinchun Chen, and a master's degree in computer science from Concordia University in Montreal at the Center for Pattern Recognition and Machine Intelligence Lab directed by Ching Y. Suen.
- ISM 6136 Data Mining
- ISM 7561 PhD Seminar on Deep Learning for Business Analytics
Ebrahimi M., Chai Y., Zhang H., Chen H., 2022, “Heterogeneous Domain Adaptation with Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE.
Ebrahimi M., Chai Y., Samtani S., Chen H. 2022, “Cross-Lingual Security Analytics: Cyber Threat Detection in the International Dark Web with Adversarial Deep Representation Learning,” MIS Quarterly, 46(2), pp. 1209-1226.
Zhang, N., Ebrahimi, M., Li, W., Chen, H., 2022, “Counteracting Dark Web Text-Based CAPTCHA with Generative Adversarial Learning for Proactive Cyber Threat Intelligence,” ACM Transactions on Management Information Systems, ACM, 13(2), pp. 1-21.
Ebrahimi M., Nunamaker J., Chen, H., 2020, “Semi-Supervised Cyber Threat Identification in Dark Net Markets: A Transductive and Deep Learning Approach,” Journal of Management Information Systems, 37(3), pp.694-722.
Ebrahimi M., Suen C.Y., Ormandjieva O., 2016, “Detecting Predatory Conversations in Social Media by Deep Convolutional Neural Networks,” Digital Investigation, Elsevier, Volume 18, pp. 33-49.
- Workshop Chair - IEEE ICDM Workshop on Machine Learning for Cybersecurity (MLC), 2022
- Committee member - IEEE Security and Privacy (S&P) Workshop on Deep Learning and Security, 2022
- Committee member - IEEE ICDM workshop on Deep Learning for Cyber Threat Intelligence (DL-CTI), 2020
- Committee member - Informs Data Science Workshop, 2021