Computational Methods for Predicting Physicochemical Properties of Ionic Liquids and Deep Eutectic Solvents

Dr. Saeid Atashrouz earned his B.Sc., M.Sc., and Ph.D. in Chemical Engineering from Amirkabir University of Technology (Tehran Polytechnic). He was recognized as the best Master’s graduate by the Iranian Association of Chemical Engineering and is a member of Iran’s National Elites Foundation. He is currently the Head of Research and Development at ChemFit Canada Inc. and serves as an Adjunct Professor at Amirkabir University of Technology. His research focuses on the intersection of artificial intelligence and chemical engineering, with a particular emphasis on process modeling, optimization, and the design of advanced materials. A significant portion of his work involves evaluating and tailoring ionic liquids (ILs) for task-specific industrial applications, including sustainable energy solutions, carbon capture, and environmental remediation. Through his dual roles in academia and industry, his work aims to translate data-driven property models into deployable process design, advancing the development of sustainable chemical processes.

Dr. Abdolhossein Hemmati-Sarapardeh is currently an associate professor at Shahid Bahonar University of Kerman. He was also an adjunct professor at, China university of petroleum, Jilin University, and Northeast Petroleum University in China. He was previously a visiting scholar at the University of Calgary. He earned a Ph.D. in petroleum engineering from Amirkabir University of Technology, an M.Sc. in hydrocarbon reservoir engineering from the Sharif University of Technology, and a B.Sc. in petroleum engineering from the Amirkabir University of Technology. His research interests include enhanced oil recovery processes, heavy oil systems, nanotechnology, and applications of machine learning in modeling IL properties. Abdolhossein has been awarded as a distinguished graduate M.Sc. student, was an honor Ph.D. student, and a recipient of the National Elites Foundation Scholarship. He served as an Associate Editor of Geoenergy Science and Engineering and Petroleum research. He has published over 280 journal articles, four books, several conference proceedings, and earned five patents.

Dr. Abdolhossein Hemmati-Sarapardeh is currently an associate professor at Shahid Bahonar University of Kerman. He was also an adjunct professor at, China university of petroleum, Jilin University, and Northeast Petroleum University in China. He was previously a visiting scholar at the University of Calgary. He earned a Ph.D. in petroleum engineering from Amirkabir University of Technology, an M.Sc. in hydrocarbon reservoir engineering from the Sharif University of Technology, and a B.Sc. in petroleum engineering from the Amirkabir University of Technology. His research interests include enhanced oil recovery processes, heavy oil systems, nanotechnology, and applications of machine learning in modeling IL properties. Abdolhossein has been awarded as a distinguished graduate M.Sc. student, was an honor Ph.D. student, and a recipient of the National Elites Foundation Scholarship. He served as an Associate Editor of Geoenergy Science and Engineering and Petroleum research. He has published over 280 journal articles, four books, several conference proceedings, and earned five patents.

Dr. Ahmad Mohaddespour obtained his PhD in Chemical Engineering from McGill University focusing on polymer nanocomposites dynamics. He completed his first postdoctoral fellowship at Polytechnique Montréal, Canada, where he collaborated with industrial partners such as TOTAL and OCP on projects involving supercapacitors, mineral processing, and sensor data analysis. He pursued his second postdoctoral fellowship at the University of British Columbia, Canada, where he worked on carbon capture technologies in partnership with DOMTAR and explored the application of artificial intelligence to chemical engineering problems. Since then, his research has focused on porous materials for energy storage, carbon capture, ionic liquids as well as AI-driven approaches to predict the properties of chemicals and complex compounds. By combining materials science, computational modeling, and process engineering, his work aims to deliver innovative solutions for energy and environmental sustainability.