Mikhail Kuklin joined the group in September 2020. He graduated with BSc degree in Chemistry in Russia (2007-2011) where he started the research in computational organic chemistry with the focus on chemical kinetics. Mikhail got MSc and PhD degrees in Chemistry at University of Eastern Finland, Department of Chemistry (2012-2015) where he worked in the field of computational catalysis (heterogeneous Ziegler-Natta and homogeneous metallocene catalysis) by applying different quantum-chemical codes and statistical approaches to study reactivity, reaction pathways, and predict catalytic properties. Next, he got a postdoctoral researcher position in University of Jyväskylä, Nanoscience center/Department of Physics (2016-2017) where he studied electronic properties and reactivity of metal oxide films by DFT and ab initio molecular dynamics. Then, Mikhail moved to Espoo to start his second postdoctoral fellowship at Aalto University, Department of Chemistry and Materials Science (2017-2019) where he mainly worked on the development and application of AI algorithms for predictions of new crystalline structures. Later, to broaden his skills outside the academy, Mikhail took the position of Data Advisor at Aalto University, Research and Innovation Services (2019-2020), where he was responsible for the development of research data management, providing and organising support to researchers, etc. Dr. Kuklin is currently interested in AI approaches, i.e., machine learning to facilitate problem solving in chemistry and physics without losing quality of the studies and broaden their application beyond the current state of the art.

For up-to-date information, check out Mikhail’s LinkedIn profile.