Our Team

Adam is an Associate Professor in Digital Chemistry and Royal Academy of Engineering Research Fellow at the University of Leeds. His research focuses on integrating digital chemistry, ML, and process engineering to develop sustainable multistep continuous flow syntheses, combining autonomous reactors and optimisation algorithms to create catalytic cascades that reduce the carbon footprint of chemical manufacturing.

John is a Lecturer in the Department of Chemistry at the University of Liverpool with expertise in synthetic organic methodology development, supramolecular chemistry, and functional materials. He is keen to develop new collaborations for large scale multidisciplinary projects applying AI and robotics to challenges in organic synthesis.

Tahereh is a Chancellor’s Fellow and Lecturer in the Department of Pure and Applied Chemistry at the University of Strathclyde. Specialising in developing innovative methods that integrate novel physical models with computational screening. Her research aims to identify advanced materials with targeted properties, determine the realistic physical limits, and drive practical design methods.

Gabriella is a lecturer in Robotics and Chemistry Automation & Royal Academy of Engineering Research Fellow at the University of Liverpool. Background in cognitive robotics, learning-based robot manipulation and applied computer vision. She is keen to collaborate on new Chemistry applications using robotics systems and learn from experts about AI for improving robotic chemists.

Emma Wolpert is a Leverhulme Early Career Fellow in the Department of Chemistry at UCL. She develops coarse-grained statistical mechanical models and integrates them with machine learning to predict and design how molecular materials assemble into targeted phases.

Gilian is a Lecturer at the University of Leeds. Her group’s research combines high-throughput experimentation with real-time mass spectrometry to discover and optimise base-metal catalysts, uncovering mechanistic insights even at ultra-low loadings. By integrating expansive datasets with kinetic profiling, they are building predictive models to map and accelerate base metal-catalysed transformations across unexplored chemical space.

Sam is a Tenure-Track Research Fellow at Aston University’s Institute for Membrane Excellence, where he leads the Synthesis, Automation & Materials (SAM) Group. His research combines polymer chemistry, laboratory automation and machine learning to accelerate materials discovery, particularly for sustainable polymers and membrane technologies. He is interested in developing collaborative, self-driving laboratories for materials discovery.

Emma is a Chancellor’s Fellow and University Research Fellow in the School of Chemistry at the University of Edinburgh. Her research focus is on the development of new machine learning algorithms to facilitate complex target synthesis. This includes ML-guided multi-step syntheses of secondary metabolites and the democratization of mechanistically complex, substrate-specific catalytic transformations.

Jiyizhe is a Lecturer in Department of Chemical Engineering, University of Manchester. Her research focuses on sustainable chemical separation processes, integrating AI methods, automated experimental platforms and process modelling to accelerate from early-stage screening to process development. Application areas include critical mineral recovery, bio-downstream separations, pharmaceutical purification and so on.

Michael is the Lecturer in Digital Chemistry for Synthesis at the University of Bristol. His research involves developing new chemical reactions using computation and machine learning to accelerate the discovery and exploration stages. He primarily focuses on synthetic methodology which uses photochemistry and organocatalysis and is interested in how digital chemistry can help in uncovering useful insights into these chemical reactions.

Marc is an Assistant Professor at Heriot-Watt University. His research group uses automation, digital workflows, and machine learning to accelerate the discovery and structural analysis of functional molecules and materials. The group is particularly interested in the data-driven design of crystalline solids for sustainable technologies, including molecular separation and related applications.