Contact Info

Mustafa Abdallah is a tenure-track assistant professor at the School of Applied and Creative Computing at Purdue University in Indianapolis. He also has a courtesy appointment at the School of Applied and Creative Computing at Purdue Polytechnic Institute. Before joining Purdue, he had been a tenure-track assistant professor at the CIT department at IUPUI since August 2022. He earned his PhD from the Elmore Family School of Electrical and Computer Engineering at Purdue University in July 2022. His PhD research focused on predicting the effects of human decision-making biases in securing cyber-physical systems (CPS) and designing practical learning algorithms to mitigate such effects.

Dr Abdallah's research interests include game theory, behavioral decision-making, explainable AI, meta-learning, and deep learning, with applications including proactive security of CPS, anomaly detection in the Internet of Things (IoT) and autonomous driving systems, and network intrusion detection. Aspects of his research contributions have been recognized by a Bilsland Fellowship from Purdue University. His research work appeared in premium security conferences and prestigious cybersecurity and AI journals, including IEEE S&P, IEEE TDSC, IEEE TCNS, ACM TOPS, ACM AsiaCCS, IEEE IoT-J, Computers & Security, ACM TKDD, ACM CIKM, IEEE ACCESS, IEEE SRDS, IEEE CDC, and others. He has also received several travel grants from IEEE conferences and two internal grants from IUPUI.

During his career thus far, Dr. Abdallah has had several experiences in conducting industrial research. First, he was a data science research intern at Adobe Research during summer 2021, in which he proposed a meta-learning approach for automating time-series forecasting model selection pipelines for reducing cloud costs. Second, during summer 2020, he worked as a data and operations research scientist at Principal Financial Group, where he developed a Kalman filter model to predict the future financial status of the companies for enhanced financial asset allocation. Third, he worked as a part-time R&D engineer in RDI company (in Egypt) for five years, where he had experience applying deep learning techniques for enhancing the performance of computer-aided pronunciation systems for several products. Such experiences led to a US patent, several research papers, and expanded his network of collaborators.