Lefteris Ntaflos, PhD
Founder & CEO
Dr. Lefteris Ntaflos is the Founder & CEO of Grand Slam I.T. and a Part-Time Lecturer at The Hong Kong University of Science and Technology, where he teaches Machine Learning Systems in the MSc AI and Entrepreneurship programme. With a unique blend of academic expertise and entrepreneurial leadership, Dr. Ntaflos brings multiple years of industry experience spanning technical training, business development, and AI research. His professional journey includes roles as Executive Director of Global Talent, Technical Trainer, and researcher. As an active mentor in the Ilitch School of Business Corporate Mentor Program and former organizer of hackUST and Fishackathon events, Dr. Ntaflos is passionate about bridging the gap between theoretical knowledge and practical implementation. His entrepreneurial background, combined with his technical proficiency in AI systems and emerging technologies, provides students with invaluable insights into both the theoretical foundations and real-world applications of machine learning systems in today’s rapidly evolving technological landscape.
Dr. Ntaflos holds a PhD in Computer Science from HKUST and an MEng in Electrical and Computer Engineering from the University of Patras, Greece. His research has appeared in PVLDB and The VLDB Journal, focusing on influence maximization, graph partitioning, and game-theoretic methods for large-scale networks. Beyond academia, he has led multinational talent development programs, and as lead organizer of hackUST 2017/2018, helped grow it into one of Asia’s largest student-run hackathons (800+ participants, 1M+ HKD funding). He has been recognized under Hong Kong’s Innovation and Technology Fund’s Technology Talent Scheme (Postdoctoral Hub) and received HKUST’s President’s 1-HKUST Student Life Award.
As a member of HKGCC’s European Committee, Dr. Ntaflos actively contributes to discussions on innovation, tech ecosystem building, and talent pipelines across Hong Kong and the region. His current interests include AI/ML systems engineering, GenAI productization, data-driven product management, and enterprise technology education, bringing industry-grade case studies and best practices into the classroom and executive training.
