Conrard Giresse Tetsassi Feugmo

Dr. Conrard Giresse Tetsassi Feugmo is currently serving as an assistant professor in chemistry at the University of Waterloo. He holds both a B.Sc. and M.Sc. in Chemistry from the University of Yaoundé I in Cameroon. Continuing his academic journey, he pursued further studies in Belgium, where he achieved a Specialized Master's degree in Nanotechnologies from the Louvain School of Engineering, followed by a Ph.D. in Computational Chemistry from the University of Namur. After completing his Ph.D., Dr. Feugmo gained valuable experience as a postdoctoral associate at the University of Western Ontario. Prior to joining the University of Waterloo, he worked as a Research Officer at the NRC's Advanced Materials Research Facility in Mississauga, utilizing his expertise in material science, nanotechnologies, and machine learning to develop a materials acceleration platform focused on sustainability-related domains.

Dr. Tetsassi Feugmo's research interests span diverse areas, with a primary focus on expediting the design process of high entropy alloys (HEA) and mixed metal oxides (MMO) using computational approaches such as Density Functional Theory (DFT), Molecular Dynamics (MD), Phase Field Crystal (PFC), and machine learning. By utilizing these methodologies, he is able to delve into the microstructure properties, driving significant progress in energy storage and conversion technologies including fuel cells, batteries, hydrogen technology, and capacitors. Furthermore, he actively engages in designing HEA materials for applications in the hydrogen storage, aeronautics, and nuclear industries. Additionally, he explores the development of hybrid gas sensors that amalgamate organic and metal oxide materials, enabling effective detection of volatile organic compounds. To optimize material efficiency and performance, he is dedicated to the development of constrained multi-objective optimization algorithms and a model for ionic conduction in non-crystalline materials. These tools empower to fine-tune material properties and functionality, ultimately contributing to the advancement of energy storage and conversion systems.

• Computational Materials Design
• High Entropy Alloys (HEA) and Mixed Metal Oxides (MMO)
• Phase Field Crystal (PFC) Modeling
• DFT, MD, KMC simulations
• Machine Learning in Materials Science
• High-throughput Materials Screening
• Hydrogen Storage
• Constrained Multi-Objective Optimization
• Ionic Conduction in Non-Crystalline Materials
• Hybrid Gas Sensors
• Non-Linear Optics
• Vibrational and electronics spectroscopies
• Orchestrator software

• 2018 Ph.D., Computational Chemistry, University of Namur (Belgium)
• 2011 M.Sc., Nanotechnologies, Catholic University of Louvain la Neuve (Belgium)
• 2010 M.Sc., Chemistry, University of Yaounde I (Cameroon)
• 2007 B.Sc., Chemistry, University of Yaounde I (Cameroon)

• 2022, Talent Bursaries Alberta AI-week
• 2019 Center for Nonlinear Studies at Los Alamos National Laboratory travel grants
• 2018 Western’s Postdoctoral Fellowships Program
• 2014 C.G.B. (Comité de Gestion du Bulletin) - C.B.B travel grants
• 2014 Gordon Research Conferences travel grants
• 2012 Institutional Ph.D. CERUNA grants
• 2011 Special Research Fund (FSR) Scholarship

• Member, Waterloo Artificial Intelligence Institute
• Member, Waterloo Institute for Nanotechnology

• CHEM 123 - General Chemistry 2
  • Taught in 2023, 2024
• NE 451 - Simulation Methods
  • Taught in 2023

* Only courses taught in the past 5 years are displayed.

• Tetsassi Feugmo CG, Ryczko K, Anand A, Singh CV, Tamblyn I. Neural evolution structure generation: High entropy alloys. J Chem Phys. 2021 155, 044102.
• Federizon J, Tetsassi Feugmo CG, Huang WC, He X, Miura K, Razi A, Ortega J, Karttunen M, Lovell JF. Experimental and Computational Observations of Immunogenic Cobalt Porphyrin Lipid Bilayers: Nanodomain-Enhanced Antigen Association. Pharmaceutics. 2021, 13, 98.
• Tetsassi Feugmo CG, Liégeois V, Caudano Y, Cecchet F, Champagne B. Probing alkylsilane molecular structure on amorphous silica surfaces by sum frequency generation vibrational spectroscopy: First-principles calculations. J Chem Phys. 2019,150,074703.
• Tetsassi Feugmo CG, Liégeois V, Champagne B. Coupled-cluster sum-frequency generation nonlinear susceptibilities of methyl (CH3) and methylene (CH2) groups. Phys Chem Chem Phys. 2017, 19, 29822.
• Tetsassi Feugmo CG, Liégeois V, Champagne B. Theoretical Investigation of Vibrational Sum-Frequency Generation Signatures of Functionalized H—Si(111) J. Phys. Chem. C 2015, 119, 3180.
• Tetsassi Feugmo CG, Liégeois V. Analyzing the vibrational signatures of thiophenol adsorbed on small gold clusters by DFT calculations. Chemphyschem. 2013, 14, 1633.
• Feugmo CG, Champagne B, Caudano Y, Cecchet F, Chabal YJ, Liégeois V. Towards modelling the vibrational signatures of functionalized surfaces: carboxylic acids on H-Si(111) surfaces. J Phys Condens Matter. 2012, 24, 124111.
• View all Conrard Giresse Tetsassi Feugmo's publications on Google Scholar: https://scholar.google.com/citations?user=bO69amoAAAAJ&hl=en&oi=ao