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Grant: Canada Research Chairs

Université d'Ottawa

$120,000.00

Artificial Intelligence at the Interface of Chemistry and Mathematics

EF 2023-24

Résumé
Being able, by sole means of computer simulations, to make a preselection of pharmaceutical drugs that deserve to be tested experimentally, to predict the mechanisms of DNA damage by specific compounds, or to design materials with specific properties, is of unquestionable interest for the whole society, in terms of both technological progress, health and economic and energetic saving. Despite all important advances in chemical and biomolecular sciences, there are still basic unsolved problems that hamper a complete reliability of the results and conclusions of such calculations, whether they are obtained via quantum computations or Machine Learning algorithms. The state-of-the-art Machine Learning methods and Quantum Chemistry calculations provide impressive results, opening new perspectives for science, technology, and society. However, they rely on massive computational resources to process huge manually annotated data-sets. The corresponding costs in terms of energy consumption and human efforts are not sustainable. Whether phrased in the language of biology, chemistry, physics, or engineering, the central challenge to all these unsolved problems is mathematical. The development of sustainable and efficient computational algorithms require transcending boundaries and to combine sophisticate knowledge from different scientific areas. Dr. Gerolin’s proposed CRC research program develop novel mathematical and computational tools combining concepts from Mathematics, Machine Learning, Computational and Theoretical Chemistry with the goal to break such theoretical and computational limitations. The outcomes of this program can be applied to transition metals (which are the workhorse of catalysis), dispersion interactions (e.g. hydrogen-bonding interaction in DNA), chemical and drug discovery. The rigorous studies developed could help other researchers who work on the same problem to eliminate some guessing and empiricism, leading to a more sustainable science. The interdisciplinary approach holds tremendous promise to increase the mutual understanding between scientific communities.
Programme
Canada Research Chairs
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
CRC-2021-00234
Name nom
Gerolin, Augusto
Department département
Department of Mathematics and Statistics - University of Ottawa
Organization id
28
Institution établissement
Université d'Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2021
Award amount
120000
Program id
CRC
Program name en
Canada Research Chairs
Program name fr
Chaires de recherche du Canada
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
9998
Committee name en
Canada Research Chair Selection Committee
Committee name fr
Comité de sélection des Chaires de recherche du Canada
Area of application code
10000
Area of application group en
The socioeconomic objective available
Area of application group fr
L'objectif socioéconomique disponible
Area of application en
The socioeconomic objective available
Area of application fr
L'objectif socioéconomique disponible
Research subject code
10000
Research subject group en
The field of research available
Research subject group fr
The field of research available
Research subject en
Le domaine de recherche disponible
Research subject fr
Le domaine de recherche disponible
Field of research list codes
RDF1010207
Field of research list names en
Calculus of variations, systems theory and control theory
Field of research list names fr
Calcul des variations, théorie des systèmes et théorie du contrôle
Socioeconomic objective list codes
RDS10610
Socioeconomic objective list names en
Information systems, technologies and services
Socioeconomic objective list names fr
Systèmes, technologies et services d'information
Application title
Artificial Intelligence at the Interface of Chemistry and Mathematics
Keyword
Opimal Transport; Generative Models; One-body Reduced Density Matrix Functional Theory; Strictly-Correlated-Electrons approach in Density Functional Theory; Schrödinger Bridges
Application summary
Being able, by sole means of computer simulations, to make a preselection of pharmaceutical drugs that deserve to be tested experimentally, to predict the mechanisms of DNA damage by specific compounds, or to design materials with specific properties, is of unquestionable interest for the whole society, in terms of both technological progress, health and economic and energetic saving. Despite all important advances in chemical and biomolecular sciences, there are still basic unsolved problems that hamper a complete reliability of the results and conclusions of such calculations, whether they are obtained via quantum computations or Machine Learning algorithms. The state-of-the-art Machine Learning methods and Quantum Chemistry calculations provide impressive results, opening new perspectives for science, technology, and society. However, they rely on massive computational resources to process huge manually annotated data-sets. The corresponding costs in terms of energy consumption and human efforts are not sustainable. Whether phrased in the language of biology, chemistry, physics, or engineering, the central challenge to all these unsolved problems is mathematical. The development of sustainable and efficient computational algorithms require transcending boundaries and to combine sophisticate knowledge from different scientific areas. Dr. Gerolin’s proposed CRC research program develop novel mathematical and computational tools combining concepts from Mathematics, Machine Learning, Computational and Theoretical Chemistry with the goal to break such theoretical and computational limitations. The outcomes of this program can be applied to transition metals (which are the workhorse of catalysis), dispersion interactions (e.g. hydrogen-bonding interaction in DNA), chemical and drug discovery. The rigorous studies developed could help other researchers who work on the same problem to eliminate some guessing and empiricism, leading to a more sustainable science. The interdisciplinary approach holds tremendous promise to increase the mutual understanding between scientific communities.