cv
Basics
| Name | Katarina Elez |
| Label | Researcher |
| katarina.elez1@gmail.com | |
| Url | https://katarinaelez.github.io/ |
| Summary | Researcher in drug discovery, 5+ years of experience conducting and analyzing large-scale molecular simulations for medicinal chemistry and developing deep learning models for molecular structure representation. |
Education
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2019.11 - Present Berlin, Germany
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2017.10 - 2019.07 Bologna, Italy
MSc
University of Bologna
Bioinformatics
- Grade: 110/110 cum laude
- Thesis: Development of a deep learning method for model quality assessment
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2013.10 - 2016.12 Bari, Italy
BSc
University of Bari
Computer Science
- Grade: 110/110 cum laude
- Thesis: A novel approach for liver and hepatocellular carcinoma segmentation from triphasic CT images
Work
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2024.11 - 2025.03 Eindhoven, Netherlands
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2023.02 - 2023.06 Berlin, Germany
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2019.09 - Present Berlin, Germany
Research Fellow
Free University of Berlin, group of Prof. Noé
- Analyzing MD simulations of protease-ligand complexes (MDTraj, PyEMMA).
- Leading a screening project for TMPRSS2 inhibition which identified a novel nanomolar inhibitor and a combination preparation for treating COVID-19.
- Majorly contributed to implementing a virtual screening pipeline comprising preparation (Schrödinger, MGLTools), docking (Smina), MD simulations (OpenMM), custom scoring (MDTraj) and active learning on molecular representations (Scikit-learn).
- Explored different graph neural network architectures. Developed a multi-scale model (PyTorch Geometric) for protein structure representation learning.
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2019.01 - 2019.05 Stockholm, Sweden
Trainee
Science for Life Laboratory, group of Prof. Elofsson
- Explored different protein structure representations and three- dimensional convolutional neural network architectures.
- Created a deep learning method (Biopython, Keras) for protein model quality assessment.
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2017.05 - 2017.03 Utrecht, Netherlands
Trainee
Utrecht University, group of Prof. Bonvin
- Analyzed intermolecular contacts and energetics of biological/crystallographic interfaces in protein complexes.
- Developed a random forest model (Biopython, Scikit-learn) for distinguishing between biological and crystallographic interfaces.
Skills
| Programming/scripting | |
| Python | |
| Bash | |
| R | |
| MATLAB | |
| Java | |
| C/C++ |
| Machine learning | |
| PyTorch | |
| PyTorch Geometric | |
| Tensorflow | |
| Keras | |
| Scikit-learn |
| Data science | |
| NumPy | |
| SciPy | |
| Pandas | |
| Matplotlib |
| Computational chemistry | |
| RDKit | |
| Open Babel | |
| Autodock Vina | |
| Biotite | |
| MoleculeKit | |
| MDTraj | |
| Biopython | |
| OpenMM | |
| PyEMMA |
| Other | |
| Git | |
| LaTeX | |
| Slurm | |
| Singularity | |
| Docker |
Languages
| Montenegrin | |
| Native |
| English, Italian | |
| Full proficiency |
| German, Spanish | |
| Elementary proficiency |
Certificates
| IELTS Academic - level C1 | ||
| British Council | 2017-06 |
Awards
- 2019
IMPRS-BAC scholarship
Max Planck Institute for Molecular Genetics
Access to graduate school and funding
- 2019
- 2018
Erasmus+ Study grant
University of Bologna
- 2016
Volunteer
-
2021.10 - Present Herceg Novi, Montenegro
Interests
| Sports and outdoor activities | |
| Running | |
| Swimming | |
| Scuba diving | |
| Padel | |
| Hiking |
| Creative activities | |
| Painting | |
| Pottery | |
| Candle making | |
| Travel video creation | |
| Weaving |
| Music | |
| Blues, R'n'B and soul | |
| Alternative rock | |
| Cinematic and orchestral |
| Books | |
| Popular science | |
| Absurdist fiction | |
| Mystery fiction |