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Research in our group focuses on the development and application of theoretical tools for the description of complex chemical phenomena. With electronic structure methods, we aim to aid in the design and understanding of functional molecules and materials for application in areas such as solar energy, light-emitting devices and biology. See our publication and research pages for more information. 

Latest Publications
Upcoming seminars and talks

CTM seminar


Speaker: Davide Massafra

Place: ChimieParisTech  

Time: 13:30 

News and Welcoming

Welcome to the group, Davide!

Davide studied Chemistry at Sapienza - University of Rome. In 2021, he got his Ph.D. in Theoretical Chemistry at the University of Vienna under the supervision of Prof. Leticia Gonzalez. His thesis focused on the simulation of light-induced DNA binding and damage. In his first Postdoctoral experience, he focused on method and software development for QM/MM photochemical simulations in complex environments, under the supervision of Prof. Marco Garavelli at the University of Bologna. Later, he moved for a postdoctoral stay at the University of Toronto in the group of Prof. Alan Aspuru-Guzik, where he focused on machine learning for chemical and biochemical applications. He joined Chimie ParisTech in February 2024 as an Associate Professor (Maître de Conférences). His research will focus on method development and applications for complex and biochemical systems.


Welcome to the group, Alexandre!

Alexandre graduated in 2023 from the Rennes and Adam Mickiewicz Universities in Western France an Poland respectively. After a Master centered on Nanomaterials & Nanotechnologies, he will perform DFT calculations on 2D van der Waals heterostructures to study their physical properties, under the supervision of the Dr. Frédéric Labat for the next three years.

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Welcome to the group, Bowen!

Bowen Deng comes from Chengdu, China, obtained his M.Sc. degree at Guangxi University (Joint training with the Institute of Automation, Chinese Academy of Sciences). His academic pursuits have been concentrated on computer vision (video understanding) and artificial intelligence applied to develop catalysts. Under the supervision of Dr. Thijs Stuyver, his forthcoming research endeavors will focus on building innovative deep learning network architectures for rapid thermodynamic and kinetic screening of reaction pathways in chemical reaction networks.

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