Sebastian Pagel pagel-s

Sebastian Pagel

About

I am a computational chemist and PhD researcher at the University of Glasgow working at the intersection of cheminformatics, machine learning, and automated chemical discovery.

My work focuses on the development of robust computational methods and scientific software that connect molecular design, data-driven modeling, and experimental workflows. I am particularly interested in integrating modern machine learning approaches—including generative models and language-model-based agents—into practical chemical discovery pipelines that are reproducible, interpretable, and usable by multidisciplinary teams.

Research Interests

Cheminformatics and molecular representation
Ligand- and structure-based drug design
Machine learning for molecular generation and property prediction
Autonomous and agent-based chemical systems
Scientific software engineering and data pipelines

Technical Expertise

Programming Languages

Machine Learning

Computational Chemistry

Selected Projects and Publications

	Spalt Alignment of Ligand Topographies using molecular surface features.
	Midas Agentic Interface to language controlled 3D molecular generation and manipulation
	ACRA Agentic Workflow of Automated Synthetic Chemistry
	Molecular Spaces Quantification of selection in chemical spaces and denovo molecular generation using Assembly Theory.
	Chemputation Chemputer and Chemputation -- A Universal Chemical Compound Synthesis Machine.
	molgrep CLI SMARTS based molecule retrieval
	MolNCA Neural Cellular Automata for molecule generation.
	LangSim Agentic Language Interface for Materials Simulations.
	AgentLabs Framework for autonomous lab agents and experimentation.