About
Stephen Gow serves as a Research Fellow at the University of Southampton, actively contributing to the Computational Systems Chemistry research group. His work bridges artificial intelligence methodologies with chemical applications through the AI3SD (Artificial Intelligence for Scientific Discovery) network.
His research spans Machine Learning and Computational Chemistry with emphasis on:
- Reinforcement learning frameworks for chemical synthesis
- Bayesian optimization in reaction engineering
- Nanopore data interpretation
- Second harmonic generation techniques
- Chemical informatics infrastructure development
Recent publications (2021-2025) demonstrate consistent focus on machine learning applications in chemical research, particularly reaction optimization and data analysis. The work shows strong interdisciplinary collaboration patterns within chemistry and computer science domains, often addressing experimental design challenges through algorithmic solutions.
Gow contributes significantly to the Computational Systems Chemistry group through the AI3SD initiative, participating in both research projects and educational programs like the Machine Learning Summer School. His collaborative approach extends to developing resources for scientific communities through video presentations and symposium organization.
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