معرفی
Akash Deep serves as an Assistant Professor in the Department of Industrial Engineering within the School of Industrial Engineering & Management at Oklahoma State University. His academic foundation includes a Ph.D. in Industrial Engineering from UW-Madison (2022), an M.S. in Statistics from the same institution (2020), and a B.Tech from IIT Roorkee, India (2017).
Dr. Deep's research centers on industrial analytics, integrating statistical methodologies with industrial knowledge to model complex systems. Key focus areas include AI for IoT-enabled smart systems, reliability optimization of engineering systems, stochastic control processes, and domain-aware machine learning. His methodological expertise spans stochastic processes, Bayesian optimization, and reinforcement learning.
His publication record demonstrates strong alignment with industrial IoT applications and system reliability, particularly through his 2021 IISE Transactions paper on degradation modeling with imperfect maintenance. This work exemplifies his approach of combining data-driven modeling with industrial process constraints.
Dr. Deep actively mentors graduate students in industrial engineering and maintains professional engagement through GitHub repositories focused on machine learning implementation and algorithm development. His technical contributions include MATLAB-based deep learning tools and R packages for multivariate arithmetic reduction.
