哔咔漫画

Reza Ebrahimi

Assistant Professor
ebrahimim@usf.edu 
Campus: Tampa
Room: CIS 2062
Phone: 813-974-6758

Reza Ebrahimi is an assistant professor at School of Information Systems and Management and the lead of at the 哔咔漫画.

Reza鈥檚 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鈥檚 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鈥� 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.

Teaching

• ISM 6251 - Machine Learning 鈥� Undergraduate and Master鈥檚

• ISM 7568 - Deep Learning for Business Analytics 鈥� Ph.D. Seminar

• ISM 6152 - Deep Learning 鈥� Master鈥檚

Research

• 颅颅颅Ebrahimi R., Chai Y., Li. W., Pacheco J., Chen H. RADAR: A Framework for Developing Adversarially Robust Cyber Defense AI Agents with Deep Reinforcement Learning, MIS Quarterly, Forthcoming.

• Ebrahimi M., Chai Y., Zhang H., Chen H., 2022, 鈥淗eterogeneous Domain Adaptation with Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity,鈥� in IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE.

• Ebrahimi M., Chai Y., Samtani S., Chen H. 2022, 鈥淐ross-Lingual Security Analytics: Cyber Threat Detection in the International Dark Web with Adversarial Deep Representation Learning,鈥� MIS Quarterly, 46(2), pp. 1209-1226.

• Zhang, N., Ebrahimi, M., Li, W., Chen, H., 2022, 鈥淐ounteracting Dark Web Text-Based CAPTCHA with Generative Adversarial Learning for Proactive Cyber Threat Intelligence,鈥� ACM Transactions on Management Information Systems, ACM, 13(2), pp. 1-21.

• Ebrahimi M., Nunamaker J., Chen, H., 2020, 鈥淪emi-Supervised Cyber Threat Identification in Dark Net Markets: A Transductive and Deep Learning Approach,鈥� Journal of Management Information Systems, 37(3), pp.694-722.

Service

• Workshop Chair - IEEE ICDM Workshop on Machine Learning for Cybersecurity (MLC), 2022, 2023, 2024
• Committee member - IEEE Security and Privacy (S&P) Workshop on Deep Learning and Security, 2022, 2023, 2024
• Committee member - IEEE ICDM workshop on Deep Learning for Cyber Threat Intelligence (DL-CTI), 2020
• Committee member - Informs Data Science Workshop, 2021