Professor of Chemistry
We use chemical informatics, computational chemistry, machine learning and AI to investigate molecules and to discover more about their structure, reactivity, analytical data and properties.
(Full list of publications)
Professor Goodman discusses his research
Publications
Hybrid QM/ML approaches for the prediction of regioselectivity in Minisci C–H functionalisation reactions
(2026)
DP5 without DFT: uncertainty-calibrated graph neural net accelerates structure confirmation via NMR
Chemical science
(2026)
17
9138
(doi: 10.1039/d5sc06988b)
Evaluating 2D and 3D Graph Encoders for Infrared-Based Organic Structure Verification
(2026)
Oligomerisation and stereoselective polymerisation of alkenes and alkynes using pyridyl-based Al(iii) catalysts.
Chemical Science
(2026)
2026
5953
(doi: 10.1039/d5sc07624b)
Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market.
Nature communications
(2026)
17
647
(doi: 10.1038/s41467-025-67374-4)
Enhancing Molecular Structure Elucidation with Reasoning-Capable LLMs
Digital Discovery
(2026)
5
1237
(doi: 10.1039/d5dd00359h)
Evaluating 2D and 3D graph encoders for infrared-based organic structure verification.
Digit Discov
(2026)
5
4180
(doi: 10.1039/d6dd00281a)
Advancing Structure Elucidation with a Flexible Multi-Spectral AI Model.
Angewandte Chemie
(2025)
138
e17611
(doi: 10.1002/anie.202517611)
Towards automatically verifying chemical structures: the powerful combination of 1H NMR and IR spectroscopy
Chem Sci
(2025)
16
21590
(doi: 10.1039/d5sc06866e)
Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market
(2025)
(doi: 10.21203/rs.3.rs-6103978/v1)
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