Journal of Theoretical & Computational Science
Open Access

Shenson Joseph is an Artificial Intelligence and Data Science expert, widely recognized for his expertise in analytics, machine learning, and AI innovation. With a career dedicated to advancing the boundaries of AI, Shenson has authored two influential books and contributed extensively to academic literature with numerous research papers published in prestigious journals. His thought leadership and insights have earned him invitations to judge high-level national and international research competitions, and he actively participates in editorial boards across AI and data science domains. In addition to his academic endeavours, Shenson serves on the advisory board of a Canadian startup, where he applies his knowledge to real-world AI solutions.

Shenson's educational background includes two master's degrees—one in Data Science and another in Electrical & Computer Engineering—reflecting his interdisciplinary expertise in both AI technologies and their practical applications in engineering. Currently, as a PhD candidate at the University of North Dakota, his research focuses on Artificial Intelligence and Quantum Computing, exploring how these transformative technologies can be integrated to push the frontiers of computation and decision-making.

A senior member of IEEE, ACM, AAAI  and a fellow IETE & BCS, Shenson is deeply committed to advancing AI research and fostering global collaboration within the scientific community. His work continues to influence both academic research and practical AI applications, driving innovation and ethical AI development across industries.