Personal profile
Research interests
Anya Gryn'ova leads the Computational Carbon Chemistry (CCC) group, which uses theoretical and computational chemistry, physics, and materials science in combination with chemical machine learning to explore and exploit diverse functional organic and hybrid materials and molecules. We are particularly interested in several classes of materials: graphene-based materials (GBMs), covalent-organic frameworks (COFs), and hyperbranched polymers (HBPs) – in the context of their applications in capture, storage, transport, and/or catalytic transformations of therapeutic molecules and environmental pollutants. Functional organic molecules and materials are central to our research efforts
- to establish the role of topology in materials chemistry,
- to predict emergent properties in complex compounds and in molecule-material complexes from their individual components / building blocks / fragments, and
- to develop explainable AI tools for exploring the infinite chemical space rationally and efficiently.
Biography
Originally from Ukraine, Ganna (Anya) Gryn’ova received her BS and MSc in chemistry summa cum laude from Oles Honchar Dnipro National University. In 2014 she received a PhD in computational chemistry from Australian National University. Her doctoral thesis received the IUPAC-Solvay International Award for Young Chemists for one of the five most outstanding PhD theses in the general area of the chemical sciences worldwide. Anya continued her career as a postdoctoral researcher at École Polytechnique Fédérale de Lausanne, where in 2016 she won the Marie Skłodowska-Curie Actions individual fellowship. In 2019, Dr. Gryn’ova started her independent scientific career leading the junior research group “Computational Carbon Chemistry” (CCC) at the Heidelberg Institute for Theoretical Studies (HITS gGmbH) and Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University, Germany. In 2021, Anya received the prestigious ERC Starting Grant for her project “PATTERNCHEM: Shape and Topology as Descriptors of Chemical and Physical Properties in Functional Organic Materials”; she also joined the Collaborative Research Centre SFB1249 “N-Heteropolycycles as Functional Materials” and the SIMPLAIX strategic research initiative on bridging scales from molecules to molecular materials by multiscale simulation and machine learning as a principal investigator. In April 2024, Dr. Gryn’ova moved to UK and became an Associate Professor of Computational Chemistry at the University of Birmingham.
Qualifications
2010-2013: PhD (awarded July 18, 2014), Research School of Chemistry, Australian National University (Australia), supervisor – Prof. Michelle Coote
2008-2009: Master of Science and tertiary teaching, Department of Chemistry, Oles Honchar Dnipro National University (Ukraine) Diploma with Honours (summa cum laude), supervisor – Prof. Sergiy Okovytyy
2004-2008: Bachelor of Science and secondary teaching, Department of Chemistry, Oles Honchar Dnipro National University (Ukraine) Diploma with Honours (summa cum laude), supervisor – Prof. Sergiy Okovytyy
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 7 Affordable and Clean Energy
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Collaborations and top research areas from the last five years
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Multi-Solvent Graph Neural Network for Reduction Potential Prediction Across the Chemical Space
Fedorov, R., Nihei, A. & Gryn’ova, G., 26 Jan 2026, In: Journal of Chemical Information and Modeling. 66, 2, p. 847-854 8 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
Fragment to framework: Automatic fragmentation of covalent organic frameworks into building blocks for band gap analysis
Ernst, M., Fedorov, R., Calzolari, A., Mollart, C., Grieser, F. F., Ber, S. & Gryn'ova, G., 26 Nov 2025, (E-pub ahead of print) In: Materials Chemistry Frontiers. 7 p., d5qm00727e.Research output: Contribution to journal › Article › peer-review
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Accelerated chemical science with AI
Back, S., Aspuru-Guzik, A., Ceriotti, M., Gryn'ova, G., Grzybowski, B., Gu, G. H., Hein, J., Hippalgaonkar, K., Hormázabal, R., Jung, Y., Kim, S., Kim, W. Y., Moosavi, S. M., Noh, J., Park, C., Schrier, J., Schwaller, P., Tsuda, K., Vegge, T. & Lilienfeld, O. A. V. & 1 others, , 1 Jan 2024, In: Digital Discovery. 3, 1, p. 23-33 11 p.Research output: Contribution to journal › Review article › peer-review
Open AccessFile95 Downloads (Pure) -
EDITORIAL: Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning
Gryn’ova, G., Bereau, T., Müller, C., Friederich, P., Wade, R. C., Nunes-Alves, A., Soares, T. A. & Merz, K., 12 Aug 2024, In: Journal of Chemical Information and Modeling. 64, 15, p. 5737-5738 2 p.Research output: Contribution to journal › Editorial › peer-review
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Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins
Riedmiller, K., Reiser, P., Bobkova, E., Maltsev, K., Gryn'ova, G., Friederich, P. & Gräter, F., 21 Feb 2024, In: Chemical Science. 15, 7, p. 2518-2527 10 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile39 Downloads (Pure)
Activities
- 1 Guest lecture or Invited talk
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Why are the excited states of heterocycles still challenging for theory?
Gryn'ova, A. (Host)
6 Jan 2026Activity: Academic and Industrial events › Guest lecture or Invited talk
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