Ebrima N. Ceesay is a principal cyber security and machine learning scientist at Noblis, where he directs and leads the Cyber Center of Excellence and is the technical program manager of the company’s largest cybersecurity program. Ceesay is also an instructor at Johns Hopkins University’s Whiting School of Engineering, an adjunct faculty member at the University of California, Berkeley’s Information School, and an associate professor in the Department of Information Sciences and Technology at the George Mason University
Cessay’s primary research interests are at the intersection of computer security and machine learning, with interests in using machine learning to improve software security and in improving the security and reliability of the machine learning models themselves. His other professional areas of interest include insider, intrusion, misuse detection, adaptive and resilience systems, data science, and advance analytics.
Ceesay earned a PhD in computer science, with an emphasis on security and applied machine learning, from the University of California, Davis. He has years of experience leading, designing, and implementing national cybersecurity initiatives in collaboration with several U.S. federal government agencies and departments, as well as private industry stakeholders, to protect cyber infrastructures. Ceesay was formerly a senior software and security engineer for companies including as Apple, Inc., IBM, Booz Allen Hamilton, TASC and Leidos. He currently works as principal scientist and program manager at Noblis.
- Ph.D Computer Science, University of California at Davis
Sr Distinguished Engineer, Capital One Financial
Kassa, Hailu, Kornegy, Kevin and Ceesay, Ebrima. Energy Efficient Cellular Network User Clustering Using Linear Radius Algorithm. 53rd Annual Conference on Information Systems & Sciences, CISS 2019.
Ceesay, Ebrima N. and Perez, Anthony,. Improving End-to-End Verifiable Voting Systems with Blockchain Technologies. IEEE Confs on iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT/Cybermatics, 2018
Ceesay, Ebrima N., Myers, Kent, and Watters, Paul. Human-centered strategies for cyber-physical systems security. EAI Endorsed Transactions on Security and Safety, 2018.
Ceesay, Ebrima N., Shuford, Erica, Kavanaugh, Tara, Ralph, Brian and Watters, Paul. Detecting and Determining Security Problems with Third-Party Trackers. The 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications (IEEE TrustCom-18).
Ceesay, Ebrima N., Do, Thach, and Watters, Paul. Cyber Situational Awareness in the Presence of Encryption. The 7th Annual IEEE Int. Conf. on CYBER Technology in Automation, Control, and Intelligent Systems. IEEE-CYBER 2017.
Brose, R and Ceesay E. Darkness of Things: Anticipating Obstacles to the Intelligence Community Recognition of the Internet of Things Opportunities. In Journal of Sensitive Cyber Research and Engineering (JSCORE) Vol 3, Issue 1 (December 2015)
Ceesay, Ebrima N., Chandersekaran, Coimbatore, and Simpson, William R., Authentication Model for Delegation, Attribution and Least Privilege, 3rd International Conference on Pervasive Technologies Related to Assistive Environment (PETRAE), Samos Greece, 2010.
Ceesay, Ebrima N, Alonso Omar and Michael Gertz, Authorship Identification Forensics on Phishing Emails, 23rd Annual IEEE/ICDE Workshop on Text Data Mining and Management (TDMM), 2007.
Ceesay, Ebrima, Zhou Jingmin, Michael Gertz, Karl N. Levitt and Matt Bishop, Using Type Qualifiers to Analyze Untrusted Integers and Detecting Security Flaws in C Programs, Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 2006.
Honors and Awards
- IEEE, ACM, NSF Scholarship Recipient (2003)
- GAAN Fellow (2003)
- Junior Board Member, Habitat for Humanity
Honor Societies: Upsilon Phi Epsilon | Phi Kappa Phi | Golden Key Honor Society | Alpha Gamma Sigma (2003)
- Valedictorian | Dean’s List (2001)