People I've Worked With

The mentors, students, and collaborators I've had the privilege to work with across computational chemistry, AI, and materials science.

PhD Project Supervisors

Dr. Grazziela Figueredo

Dr. Grazziela Figueredo

University of Nottingham, UK

Leading research in AI interpretability for chemical systems and data provenance in ML modelling; co-developing ML explainability methods for biomaterials design.

Prof. Simon Woodward

Prof. Simon Woodward

University of Nottingham, UK

Working together on machine learning models for predicting catalyst behaviour and ligand optimisation in asymmetric catalysis.

Prof. Ender Özcan

University of Nottingham, UK

Collaborating on AI-based systems for chemical reaction optimisation using graph neural networks.

Summer Students

Amelia Downs

Amelia Downs

Summer Student 2026

University of Nottingham, UK

Summer 2026 research student working on the open-source ML tool Helix. Co-supervised with Prof. Grazziela Figueredo.

Padraig Cunningham

Padraig Cunningham

Summer Student 2026

University of Nottingham, UK

Summer 2026 research student who worked on uncertainty estimation of machine learning models for enantioselectivity prediction. Co-supervised with Prof. Simon Woodward.

Estefanía Deniz Fuentes

Summer Student 2026

University of Nottingham, UK

Summer 2026 research student working on the open-source ML tool Helix. Co-supervised with Prof. Grazziela Figueredo.

Viraj Deorukhkar

Viraj Deorukhkar

Summer Student 2024

University of Nottingham, UK

Summer 2024 research student who contributed to graph neural network approaches for data checking in asymmetric-catalysis literature. Co-supervised with Prof. Simon Woodward.

Masters Students

MSc students co-supervised on deep-learning projects in the chemical sciences — 2024 with Prof. Simon Woodward; 2023 with Dr. Grazziela Figueredo and Dr. Kristaps Ermanis.

MinLong Chen

MSc Student 2024

University of Nottingham, UK

MSc student (2024) working on machine-learning approaches for the chemical sciences.

MSc thesis GNN detected network patterns in rhodium-catalyzed enantioselective additions to electron-deficient alkenes

Ruoyu Wen

MSc Student 2024

University of Nottingham, UK

MSc student (2024) working on machine-learning approaches for the chemical sciences.

MSc thesis A Graph Convolutional Network applied to predict enantioselective synthesis ΔΔG‡

Junjie Xia

MSc Student 2024

University of Nottingham, UK

MSc student (2024) working on machine-learning approaches for the chemical sciences.

MSc thesis GNN detected model is applied to rhodium-catalyzed enantioselective addition reaction

Veera Pedireddi

MSc Student 2023

University of Nottingham, UK

MSc student (2023) working on a deep-learning project in the chemical sciences. Co-supervised with Dr. Grazziela Figueredo and Dr. Kristaps Ermanis.

Former Collaborations

Prof. Hon Wai Lam

University of Nottingham, UK

Collaborated on data-driven approaches for optimising enantioselectivity in rhodium-catalysed asymmetric 1,4-additions.

Prof. Patrick J. Guiry

University College Dublin, Ireland

Collaborated on describing chiral ligands and in silico substrate screening in palladium-catalysed decarboxylative asymmetric allylic alkylation.

Dr. Declan Galvin

University College Dublin, Ireland

Collaborated on describing chiral ligands and in silico substrate screening in palladium-catalysed decarboxylative asymmetric allylic alkylation.

Prof. Mauricio Gutiérrez

Universidad de Costa Rica, Costa Rica

Collaborated on explainable GNNs for structure–property relationships in interstitial-alloy materials.

Dr. Ignacio Borge

Universidad de Costa Rica, Costa Rica

Collaborated on explainable GNNs for structure–property relationships in interstitial-alloy materials.

Prof. William Zamora-Ramírez

Prof. William Zamora-Ramírez

Universidad de Costa Rica, Costa Rica

Collaborated on predicting physical-chemical profiles of bioactive compounds and cheminformatics tool development.