About Me

Welcome! I am a Senior Machine Learning Scientist at Pfizer, working on AI for Drug Discovery and AI for Science with a focus on generative chemistry and structure-based drug design.

My research interests include:

• Generative AI for Molecules: Developing flow matching and diffusion-based models for 3D molecular generation
• Structure-Based Drug Design: AI methods for pocket-conditioned ligand generation and affinity prediction
• Equivariant Neural Networks: Leveraging geometric deep learning for molecular property prediction

Feel free to reach out if you’d like to collaborate or discuss research!

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Selected Publications

### 2025

FLOWR.root: A Flow Matching Based Foundation Model for Joint Multi-Purpose Structure-Aware 3D Ligand Generation and Affinity Prediction
J. Cremer*, T. Le, M. M. Ghahremanpour, E. Sługocka, F. Menezes, D.-A. Clevert
arXiv preprint arXiv:2510.02578, 2025
Paper

It's Not Always Crystal Clear: In-Pocket Analysis for Understanding Binding Site Microenvironment Properties
F. Menezes, T. Fröhlich, L. C. Schofield, J. Cremer, J. Agirre, R. P. Joosten, R. Bourgeas, S. Sung, J. A. Marquez, G. Murshudov, O. Plettenburg, M. Sattler, G. M. Popowicz
bioRxiv 2025.09.24.678379, 2025
Paper

FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generation
J. Cremer*, R. Irwin, A. Tibo, J. P. Janet, S. Olsson, D.-A. Clevert
arXiv preprint arXiv:2504.10564, 2025
Paper

Equivariant Diffusion for Structure-Based De Novo Ligand Generation with Latent-Conditioning
T. Le*, J. Cremer*, D.-A. Clevert et al.
Journal of Cheminformatics, 17, 90, 2025
Paper

### 2024

PILOT: Equivariant Diffusion for Pocket-Conditioned De Novo Ligand Generation with Multi-Objective Guidance via Importance Sampling
J. Cremer*, T. Le*, F. Noé, D.-A. Clevert, K. T. Schütt
Chemical Science, 15, 14954–14967, 2024
Paper

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
T. Le*, J. Cremer*, F. Noé, D.-A. Clevert, K. Schütt
International Conference on Learning Representations (ICLR), 2024
Paper

### 2023

Equivariant Graph Neural Networks for Toxicity Prediction
J. Cremer*, L. Medrano Sandonas, A. Tkatchenko, D.-A. Clevert, G. De Fabritiis
Chemical Research in Toxicology, 36(10), 1561–1573, 2023
Paper

### 2020

Polarization Control of Radiation and Energy Flow in Dipole-Coupled Nanorings
J. Cremer*, D. Plankensteiner, M. Moreno-Cardoner, L. Ostermann, H. Ritsch
New Journal of Physics, 22(8), 083052, 2020
Paper

View All Publications on Google Scholar