Ivan Miletic, P.Eng., Data Analytics Leader

Ivan3_300_350Ivan Miletic, M.Eng., P.Eng., MBA  holds master’s degrees in both Chemical Engineering and in Business Administration and has over twenty years of experience in the fields of modeling, simulation, control, and optimization of complex systems. At inCTRL he is focussing on the development of tools for sensor and process fault detection, data-driven models, and process optimization procedures. His experience and know-how are enabling inCTRL to further strengthen its profile in data analytics and is complementing inCTRL’s leading expertise in process control and optimization.

Ivan received his degrees from McMaster University in Hamilton Ontario, Canada. His process experience includes steelmaking, food processing, fuels, pharmaceuticals, and wastewater treatment. He has led various projects for Fortune 500 clients. These projects were directed at the application of predictive models, process fault detection, and soft-sensor technology and have provided significant financial and operating benefits to clients. He has also spearheaded the development of PSOCS, a data acquisition and calculation execution platform that enables customized models to run on-line in many production environments. Previously, Ivan worked at ArcelorMittal Dofasco where he developed on-line models for steady-state and batch chemical and metallurgical processes and developed optimization methods that reduced production down-time and operating costs.

Ivan holds two industrial patents, one on the application of multivariate empirical batch modeling methods for fault detection for a steel casting machine, and the other for closed-loop control for a food fryer. He is the author of over twenty publications in academic and trade journals, and has presented at numerous conferences. Ivan has been invited twice by the Fields Institute for Research in Mathematical Sciences at the University of Toronto as a speaker on multivariate statistical methods as applied to fault detection, control, and optimization. He has given courses on Experimental Design, Empirical Process Models and General Statistical Methods at McMaster University and at Mohawk College and has co-supervised several M.Eng. students. Ivan is a sought-after reviewer for several technical journals on statistical methods, process optimization, and empirical modeling. Ivan is a Professional Engineer licensed in Ontario and has served on the Enforcement Committee of the Professional Engineers of Ontario (PEO).


Publications: Google Scholar, ResearchGate