Anmol Agarwal, D.Eng.


Anmol Agarwal, D.Eng.

Department: Cybersecurity


Dr. Anmol Agarwal is an adjunct professor at George Washington University in the School of Engineering and Applied Sciences. Dr. Agarwal specializes in the intersection of AI, Machine Learning, and cybersecurity. She leverages her professional experience as an industry researcher in AI and Machine Learning security to secure 5G and 6G networks. She is currently teaching machine learning to doctoral students in the Artificial Intelligence & Machine Learning Doctor of Engineering program. Dr. Agarwal's research interests include adversarial machine learning, AI and Machine Learning security, Federated Learning, privacy-preserving technologies, and cybersecurity.

In addition to her industry experience in AI security research, Dr. Agarwal has worked in the federal government. Specifically, she previously served at the U.S. Cybersecurity and Infrastructure Security Agency (CISA), where she oversaw risk management efforts for High Value Assets in the U.S. federal enterprise. She has experience working in industry, government, and academia. Dr. Agarwal is also an active speaker and has spoken at a wide variety of conferences such as the Pacific Hackers Conference and SecureWorld about AI and Machine Learning security.

Dr. Agarwal holds a Doctor of Engineering degree in cybersecurity analytics from George Washington University. Her research focused on adversarial machine learning and studied attacks on machine learning models. She has a Master's degree in computer science and a Bachelor's degree in software engineering with an information assurance specialization from the University of Texas at Dallas.  In her free time, Dr. Agarwal enjoys spending time with her family and traveling.

Relevant Publications

[1] Agarwal, A. (2023). A Decision Support Tool to Evaluate the Robustness of Federated Learning to Data Poisoning Attacks (Doctoral dissertation, The George Washington University).

[2] Ayoade, G., Akbar, K. A., Sahoo, P., Gao, Y., Agarwal, A., Jee, K., ... & Singhal, A. (2020, June). Evolving advanced persistent threat detection using provenance graph and metric learning. In 2020 IEEE Conference on Communications and Network Security (CNS) (pp. 1-9). IEEE.