Veronika obtained her PhD at Ecole Polytechnique Federale de Lausanne in 2022. She studied non-covalent interactions and complex chemical processes in explicit solvents using neural-network-based potentials combined with enhanced sampling techniques. She joined the Duarte group in November 2022 with Postdoc.Mobility fellowship from the Swiss National Science Foundation. Her research interests cover the ab intio molecular dynamics, solvation effects, enhanced sampling and machine learning-based potentials (MLPs). Currently, she works on the application of MLPs to model metal-ligand interactions in small biomolecules.

Email: veronika.juraskova@chem.ox.ac.uk

Bastian obtained his PhD in theoretical chemistry from Hokkaido University under the supervision of Professor Satoshi Maeda in 2023. He has previously studied homogenous catalysis and structural self-assembly, with a particular emphasis on automated reaction mechanism discovery. In his current research, Bastian combines quantum chemical calculations and machine learning methods to design new transition metal catalysts.

Email: bastian.skjelstad@chem.ox.ac.uk

Jordi carried out his PhD at the Institute of Computational Chemistry and Catalysis (IQCC) under the supervision of Prof Sílvia Osuna and Dr Marc Garcia-Borràs (University of Girona) where he determined the reaction mechanisms of new abiological biotransformations using quantum and classical chemical calculations. He joined the Duarte group in 2024 to understand and develop accurate machine learning models to predict enzymatic inhibition.

Email: jordi.soleriparpal@chem.ox.ac.uk

Aleksy completed his MChem at the University of Oxford, University College. His master's project, under the supervision of Professor Stuart Conway, involved the design of molecular probes for a parasitic bromodomain, with the aim of validating this as a target for the treatment of a neglected tropical disease. He is now a member of Merton College, Oxford. His current research in the Duarte group is concerned with therapeutically relevant macrocycles. Aleksy likes to cook, and, even more so, likes to eat. He also plays piano, and is teaching himself bass guitar.

Email: aleksy.kwiatkowski@merton.ox.ac.uk

Website: aleksy.me

LinkedIn

Khan completed his MSc in Physical Chemistry and BSc in Chemistry and Physics at Seoul National University. In Seoul, he studied molecular electrostatic potentials using DFT. After joining the group with the support of Kwanjeong Educational Foundation, he has been interested in investigating into the mechanisms and pathways of organic chemistry reactions with machine learning potentials and had a dream to conquer the world of organic chemistry. Outside of the laboratory, he enjoys travelling, various sports including football and playing video games.

Email: donghan.shin@hertford.ox.ac.uk

Originally from West Bengal, India, Shoubhik completed his MChem at the University of Sheffield (2022). His master's project, supervised by Dr. Grant Hill, involved design of a combined semi-empirical and machine-learning methodology for prediction of UV-visible absorption peaks of organic molecules. He is now studying for a DPhil in Duarte group, and his research is aimed at predicting C-H activation reactions with machine learning, and investigating their mechanisms with automated reaction path generation. Apart form chemistry, Shoubhik also likes stand-up comedy, travelling, and woodwind instruments.

Email: shoubhik.maiti@st-hughs.ox.ac.uk

Wojtek graduated from the University of Heidelberg with a BSc in Chemistry and an MSc in Molecular Systems Engineering. He joined the Duarte group in 2023, and is working on developing computational approaches to fight antimicrobial resistance.

Email: wojtek.treyde@sjc.ox.ac.uk

Sara completed her Bachelor of Philosophy at the Australian National University. For her Honours project she studied under the supervision of Prof. Michelle Coote, using deep learning to predict acidity constants in diverse solvents. She also briefly worked as a machine learning engineer before joining the Duarte group, now studying a DPhil in Computational Discovery with a focus in deep learning for retrosynthesis.

Email: sara.tanovic@gtc.ox.ac.uk

James completed his MChem at the University of Oxford whilst at Jesus College. Now, a member of New College, his research focuses on utilising machine-learning methods to investigate and answer questions of interest in Physical Organic Chemistry. In his free time, James enjoys playing the drums, reading, and foreign languages.

Email: james.somper@new.ox.ac.uk

Shichen completed her BSc in Chemistry at the University of Nottingham (2023) and her MSc in Theoretical and Computational Chemistry at the University of Oxford. Prior to joining the group, she gained research experience investigating chemical structures and properties using machine learning. Driven by the potential advancements that integrating AI with traditional scientific disciplines can bring, she is now pursuing a DPhil focused on applying machine learning potentials to organic and inorganic molecular systems.

Email: shichen.dong@wolfson.ox.ac.uk

Josef completed a dual BSc / BCompSc at the University of Queensland in Australia. For his Honours thesis he worked with Professor Alan Mark to develop graph-based algorithms and machine learning models for tautomer prediction. Josef is now an Oxford-Reuben scholar starting his first year of the DPhil in Chemistry. His project is co-supervised by Professor Volker Deringer, where he is working on machine learning methods at the interface of materials and molecular modelling. In his spare time Josef enjoys playing the drums, volunteering, and learning Spanish.

Email: josef.holownia@reuben.ox.ac.uk

Ala completed her BA in Natural Sciences and MSci in Systems Biology at the University of Cambridge. She is interested in machine learning approaches for chemistry and biology, particularly using geometric deep learning and graph neural networks. Currently, she is investigating the potential of geometric AI to accelerate molecular dynamics simulations. Ala is also jointly supervised by Prof. Michael Bronstein and Dr. Ismail Ceylan from the Computer Science Department.

Email: alicja.maksymiuk@new.ox.ac.uk

Tom completed his MChem degree from the university of Oxford, St Hughs college, in 2022. His Master's project, supervised by Professor Schofield, involved carrying out structure activity relationship studies on a novel pharmacophore for inhibition of a therapeutically relevant oxygen sensing enzyme. With the SABS R3 DTC and under the joint supervision of Professor Duarte and Professor Schofield, Tom is investigating new methods of inhibition for a number of oxygen sensing enzymes.  

Email: thomas.wise@trinity.ox.ac.uk

Laura Marcon completed her BSc in Industrial Chemistry at the University of Bologna and her MSc in Complex Systems Chemistry at the University of Strasbourg. She has worked on projects ranging from DFT studies of rotational barriers to Gaussian Process machine learning in quantum chemistry and QSAR modeling to annotate large chemical libraries. She is now pursuing a DPhil in Chemistry at the University of Oxford as a member of Reuben College. Her research focuses on integrating data-driven methods with quantum chemistry to advance molecular discovery and functional design.

Email: laura.marcon@chem.ox.ac.uk

Xiang obtained his BSc degree from Dalian University of Technology and the University of Leicester, followed by an MSc in Theoretical and Computational Chemistry at the University of Oxford. His prior work focused on reaction-mechanism studies in both transition-metal catalysis and enzyme catalysis through DFT calculations and experimental studies. He is currently working to apply machine-learning potentials to study transition-metal systems and reaction pathways. Outside of his academic work, Xiang enjoys a wide range of sports and board games.

Email: xiang.li2@keble.ox.ac.uk

Charlie is a fourth-year MChem chemist at Lincoln College, currently completing their Part II (Master’s) project in the Duarte group. Their research focuses on fine-tuning foundational machine learning models. Outside the lab, Charlie enjoys boardgames, singing, and playing Ultimate Frisbee.

Email: charlie.franklin@lincoln.ox.ac.uk

Jeff is a fourth-year MChem student at The Queen’s College, Oxford. In the Duarte Group, he’s exploring how molecular dynamics and machine learning can be used to better understand and inhibit enzymes. When he’s not running simulations, you can often find him doing sprinting or keeping up his Duolingo streak.

Email: jefferson.xue@queens.ox.ac.uk

Hanna completed her BSc in Chemistry at ETH Zürich and is currently pursuing a MSc in the same field with a focus on computational chemistry. She recently joined the Duarte Group as a visiting student for her Master’s thesis where she will be working on machine learning for retrosynthesis models. Outside of the lab, Hanna enjoys road cycling, hiking, music and travelling.

Email: hschaefer@ethz.ch

Patrik completed his BSc in Biochemistry at the University of Heidelberg and is currently continuing his studies there in the MSc programme. He joined the Duarte Group as a visiting student for an internship, where he is working primarily on molecular dynamics simulations of biomolecular systems. Outside the lab, he enjoys climbing whenever possible, as well as cooking, listening to music, and travelling.

Email: patrik.hansmann@stud.uni-heidelberg.de

Justine completed her Bsc in Chemistry at ENS-PSL and is currently persuing the first year of her Master’s degree at ENS, specializing in theoretical and computational chemistry. As a visiting student in the Duarte Group, her project focuses in multihead fine-tuning for machine learning potential models. Outside the lab, you can find her running, bouldering, or simply relaxing with a
good book.

Email: justine.jourde@ens.psl.eu

PDRA (2019-2025)

Topic: Supramolecular chemistry

Current Position: Researcher, Kyoto Institute of Technology

PDRA (2019-2020)

Current position: Postdoc, University of Houston

Post-Doc (2021-2023)

Topic: Supramolecular chemistry, enzyme stability, machine learning

Current Position: Researcher, Uppsala University

Email: shaoqi.zhan@kemi.uu.se

DPhil (2018-21), PDRA (2021-22)

Thesis Title: Methods Towards Computational Catalyst Design

Topic: MLPs, supramolecular chemistry, and mechanistic analysis. Core developer of mlp-train and autodE

Current position: Research Software Engineer, UCL

DPhil (2018-21), PDRA (2021-2022)

Thesis Title: The Reactivity of Strained Carbocycles

Topic: Physical organic chemistry, mechanistic analysis

Current position: Assistant Professor at the University of Texas at Dallas

Webpage

DPhil (2018-22), jointly supervised by Prof. D. Dixon

Thesis Title:

Topic: Organic synthesis, DFT, mechanistic analysis

Current position: Postdoctoral Fellow at AstraZeneca

LinkedIn

DPhil (2018-2023)

Thesis Title: Machine learning workflows for chemistry: applications in catalysis and ionic liquids

Topic: Machine Learning Workflows for Chemistry: Applications in Catalysis and Ionic Liquids

Current Position: PsiQuantum, ML Modeller

LinkedIn

DPhil & PostDoc (2019-2024)

Thesis Title: Investigation into biological and biomimetic transmembrane systems

Current Position: CADD researcher at Roche

LinkedIn

DPhil (2020–2024)

Thesis Title: Computational Studies of Ligand Binding to TRIM PHD Bromodomains

Topic: Computational Studies of Ligand Binding to TRIM PHD-Bromodomains

Current position: Scientist, Bioinformatics Institute, A*STAR

LinkedIn

DPhil (2018-2023) & PostDoc (2023-2024)

Thesis Title: Computational Investigation of the SARS-CoV-2 Cysteine Proteases

Topic: Enzyme modelling, MPro inhibitor design

Current position: Instructor II, Hong Kong Baptist University

LinkedIn

DPhil (2019 - 2023)

Thesis Title: Simulating Chemical Reactivity using Machine Learning Potentials and Umbrella Sampling

Topic: MLIPs, reactivity, umbrella sampling

Current Position: Graduate-entry medicine, St Hugh’s College, University of Oxford

Email: tristan.johnston-wood@st-hughs.ox.ac.uk

DPhil (2021-2025)

Thesis Title: Modelling Chemical Processes with Machine Learning Potentials

Topic: Reactive machine learning interatomic potentials

Current Position: PDRA at ETH (Jorner group)

LinkedIn

DPhil (2021-2025)

Thesis Title: Kinetic predictions for E2 and SN2 reactions using the BERT architecture: Comparison and interpretation

Topic: Machine Learning; interpretability; Transformer architecutre

Current Position: XYME AI

DPhil (2021-2025)

Thesis Title: Machine learning for synthesis planning and synthesisable molecule generation

Topic: Retrosynthesis, heterocycles

Current Position: The Institute of Cancer Research

LinkdIn

DPhil (2018-2025)

Topic: ML for organocatalysis

Current position: Teacher at The King’s School, Canterbury, UK

LinkedIn

DPhil (2020-25), jointly supervised by Prof. M. Langton

Thesis Title:

Topic: Transporters, DFT, Machine Learning Potentials

Current position:

LinkedIn

PDRA (2022-2025)

Topic: Supramolecular chemistry

Current Position: PDRA, University of Strathclyde

Linkedin

Part II student (2024-25)

Topic: MLIPS to model chemical reactivitys

Current position:

LinkedIn

Part II student (2024-2025)

Topic: Modelling TM-catalysed reactions

LinkedIn

Part II student (2024-25)

Topic: ML for inhibitor design

Current position: PhD student at Imperial College London, UK

LinkedIn

MSci (2020-22), jointly supervised with Prof. E. Anderson

Topic: Starin molecules, Physical organic chemistry, mechanistic analysis

Current position: PhD student at MPI für Kohlenforschung (List group)

Linkedin

MRes (2022-2024)

Topic: Computional modelling of reaction outcomes

Current Position:

Part II student (2019-20)

Topic: Reaction mechanism exploration, core developer of AutodE

Current position: Softwire, London

Part II student (2020-21)

Current position: Axiom Therapeutics

LinkedIn

Part II student (2020-21)

Topic: Reaction mechanism modelling. Recipient of the Brian Bannister prize for best Master's thesis

Current position: Founder of Anda Global Growth Limited, Hong Kong

Part II student (2021-22) and former JCR President

Topic: Machine Learning

Current: MA Student at The Courtauld Institute of Art

LinkedIn

Part II Student (2022-23), jointly supervised with Prof. E. Anderson

Topic: Computational and Experimental Study of Cycloadditions

Current Position: Data Scientist at BlockTech

LinkedIn

Part II Student (2022-23)

Topic: Directing Heterocycle Synthesis with Machine Learning

Current Position: Industrial PhD student, Roche hosted by EPFL (Prof. Philippe Schwaller)

LinkedIn

Part II Student (2022-23)

Topic: Machine Learning Potentials and Free Energy Surfaces: From Method Development to Applications

Current Position: PhD student (Prof. Reinhard Maurer & Prof. James Kermode), University of Warwick

LinkedIn

Part II Student (2023-24)

Topic: Machine learning for reaction outcomes

Current Position:

LinkedIn

Part II Student (2023-24)

Topic: C-H Activation

Current Position:

LinkedIn

Part II student (2024-25)

Topic: Machine Learning potentials. Recipient of the Brian Bannister prize for best Master's thesis

Part II student (2024-25)

LinkedIn

Part II student (2024-25)

Visiting student (2020)

Current position: PhD student at ENS Paris

LinkedIn

Visiting student (2020)

Current position: PhD, Pavia

Linkedin Twitter Email

Visiting student (2021)

Current position: PhD student, Ruđer Bošković Institute, Zagreb, Croatia

RBI webpage Linkedin ORCID

Summer project student (2021)

Visiting Student (Feb-May 2024)

Topic: ML models for binding affinity

Current Position: PhD student at Leiden University

Email: m.l.a.hakkennes@lic.leidenuniv.nl

LinkedIn

Visiting Student (Summer 2023)

Topic: Machine Learning Potentials and Cage Catalysis

Current Position: PhD Student (Prof. Lars Schäfer, Ruhr University Bochum

LinkedIn

Visiting student (2021)

Visiting PhD student (2025)

Topic:
Current position: PhD student at EPFL

LinkedIn; Email: christian.schellhaas@epfl.ch

Visiting master student (2025)

Topic:
Current position: Master student CSC Strasbourg

LinkedIn; Email: neus.arbos-labal@etu.unistra.fr

SBM rotation student (2021)

Current position: DPhil student, Oxford

Email

SBM rotation student (2021)

Current position: DPhil student, Oxford

SBM rotation student (2020)

Current position: DPhil student, Oxford

SBM rotation student (2020)

Current position: DPhil student, Oxford

SBM rotation student (2019)

Current position: Research Data Scientist, The Alan Turing Institute

Github

TMCS rotation student (2019)

Current position: Graduate student, Colorado State University

Github

SBM rotation student (2019)

Current Position: PDRA, Durham

LinkedIn