Ajay Ganesh, PhD

Research Associate, Faculty of Engineering - Civil and Environmental Engineering Dept

Pronouns: He/Him


Research Associate, Faculty of Engineering - Civil and Environmental Engineering Dept


Area of Study / Keywords

Complex systems and control Data Science Machine Learning Multi-Physics Processes


Dr. Ajay Ganesh is a Research Associate at the University of Alberta with research interests spanning the crossroads of Complex Energy Systems Engineering and Data Analytics. He is a well-seasoned engineer, inculcating the best of both academia and industry. A researcher-cum-educator, trained by prestigious Universities of Canada, the United States, and India in Complex Systems & Control Engineering and Data Science. He is a creative problem-solver possessing a multidisciplinary academic background in the reservoir, chemical, and electrical engineering. He is a competent team player with experience working with people across the globe with different cultural, religious, and language backgrounds.

During his Ph.D. at the University of Alberta, he worked on a thesis titled "Proxy Model-based Closed-Loop Reservoir Management: A data-driven approach." He developed Machine Learning-based data-driven models to manage petroleum reservoirs to strike a balance between the economics and safety of the operation. His approach focused on implementing Machine Learning models in the place of first-principles-based models when the latter becomes computationally expensive for control and optimization purposes. He has successfully published his research in high-impact journals and at international conferences. During his previous Postdoc at the Delaware Energy Institute, University of Delaware, U.S.A., he worked on Physics and Data Analytics-based modeling and control of the natural gas upgrading process. He also possesses industrial experience as a software engineer, where he acquired project management documentation skills apart from code development.


Ten years of experience in the crossroads of Data Science and Complex Systems & Control Engineering. Successfully published articles in renowned, high-impact-factor international journals, conferences, symposiums, and online platforms during Ph.D. and Postdoc (present and back in the U.S. (U Delaware)).

Currently working on the following projects:

  • Data mining techniques to extract geomechanical characteristics of the underlying caprock layer from the reservoir field data.
  • Application of Value of Information analysis in reservoir surveillance and management
  • AI-based framework for modeling and optimization of CO2 sequestration

Refer to the Google Scholar link at the end of the page for a complete list of publications.



  • Principal Instructorship in applied statistics and process control related courses
  • Secured a 4000 CA$ teaching award to revamp an undergraduate/graduate course in Data Science.
  • Completed sixty-plus hours of graduate teaching and learning training.
  • Served thrice as Teaching Assistant, Grader, and Internship-student mentor and once as a Laboratory Manager


CH E 358 - Process Data Analysis

Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include least squares regression, analysis of variance, propagation of error, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and 345.

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