Dr. Dumindu Samaraweera is an assistant professor of data science in the Department of Mathematics at Embry-Riddle Aeronautical University’s Daytona Beach Campus. He teaches undergraduate and graduate courses in data science while leading research in cybersecurity, privacy-preserving artificial intelligence, and secure edge intelligence.
Dr. Samaraweera earned his Ph.D. in Electrical Engineering from the University of South Florida (USF), an M.S. in Enterprise Applications Development from Sheffield Hallam University in the United Kingdom, and dual bachelor's degrees in Information Technology, and Computer Systems and Networking. Before joining academia, he spent more than a decade in industry as a software and electrical engineer, where he led the development of enterprise-scale software systems and engineering solutions. He later served as an assistant research professor at the University of South Florida, where he led cybersecurity workforce development initiatives through Cyber Florida while continuing research in secure and distributed machine learning.
Dr. Samaraweera's research focuses on developing secure, privacy-preserving, and trustworthy artificial intelligence systems for distributed and resource-constrained environments. His work spans cybersecurity, federated learning, homomorphic encryption, privacy-preserving machine learning, and the security of language and multimodal models deployed at the edge. He has years of experience conducting research on Department of Defense (DoD)-sponsored projects, addressing security, privacy, and resilience challenges in mission-critical distributed and edge AI systems. He is particularly interested in designing practical privacy-enhancing technologies that enable collaborative intelligence while protecting sensitive data. His recent research has introduced efficient approaches for homomorphic encryption in federated learning, investigated security and privacy vulnerabilities in distributed AI systems, and explored secure deployment strategies for edge-based foundation models. His current projects include privacy-enhanced federated learning, efficient homomorphic encryption for collaborative AI, and optimization of multimodal language models for tactical edge intelligence. In addition to research, he actively mentors undergraduate and graduate students by integrating hands-on research experiences into the classroom and guiding students toward conference publications, advanced study, and externally funded research opportunities.
Dr. Samaraweera is the co-author of the book Privacy-Preserving Machine Learning (Manning Publications) and has published research in leading IEEE journals and conferences. He serves the research community through leadership roles in international conferences, including IEEE DSC and ACM Southeast, and as a reviewer for several IEEE Transactions. An IEEE Senior Member and a Systems Security Certified Practitioner (SSCP), Dr. Samaraweera is committed to advancing secure and trustworthy AI while fostering the next generation of data scientists and cybersecurity professionals.
Ph.D. - Doctor of Philosophy in Electrical Engineering, University of South Florida
- Senior Member, Institute of Electrical and Electronics Engineers (IEEE)
- Systems Security Certified Practitioner (SSCP), ISC2 (International Information System Security Certification Consortium)