Ph.D. · SMIEEE

Dr. Jyoti Prakash Sahoo

Assistant Professor
College of Electrical Engineering and Computer Science (EECS)
National Taiwan University of Science and Technology (Taiwan Tech)
Taipei, Taiwan

Professional Bio

Academic background, research, and professional activities

Dr. Jyoti Prakash Sahoo, Ph.D., SMIEEE, is an Assistant Professor in the College of Electrical Engineering and Computer Science (EECS) at National Taiwan University of Science and Technology (Taiwan Tech).

His research focuses on Quantum AI and Cybersecurity, more specifically on federated learning, quantum-classical machine learning, and trustworthy AI for edge-IoT security.

He served as an Assistant Professor at the Institute of Technical Education and Research, Siksha 'O' Anusandhan (Deemed to be University), starting from August 2010. He was on study leave to pursue his Ph.D. at NTUST.

He actively collaborates with leading research groups, including the Scalable Adaptive Yet Efficient Distributed (SAYED) Systems Group at Queen Mary University of London and the Quantum Research Lab at Taiwan Tech.

With expertise in edge computing and machine learning, he serves on the editorial and reviewer boards of multiple journals and conferences.

He has held key leadership roles such as Publicity Chair, Web Chair, Organizing Secretary, and Technical Program Committee Member for national and international conferences.

As a WIPRO Certified Faculty, he has driven industry-academia collaboration, student enablement, and innovative teaching methodologies.

He is also a recipient of the CTCI Foundation Research Scholarship 2025.

Research Focus

Research interests and current areas of investigation

Federated Learning

Distributed and privacy-aware machine learning for edge and IoT environments.

Quantum AI

Quantum–classical machine learning and emerging approaches to intelligent systems.

Trustworthy AI

Explainable and trustworthy artificial intelligence for security-sensitive applications.

Cybersecurity

AI-enabled security for edge computing and IoT systems.

Large Language Models

Large language models, foundation models, and generative AI.

Generative AI

Generative AI approaches for cybersecurity and intelligent systems.

Fall 2026 Courses

Courses taught in Fall 2026

Research & Teaching

Research and teaching activities span quantum AI, cybersecurity, federated learning, edge computing, machine learning, and trustworthy artificial intelligence, alongside undergraduate and graduate-level computer science education.