I work across two things I care about equally: protein structure and molecular simulation, and data science and deep learning. Antibody–antigen complex prediction and MD on one side; CNNs, single-cell analysis and GPU-accelerated pipelines on the other. My repositories run across both.

MSc in Molecular Biology — Bioinformatics track, University of Padova (2026). Thesis carried out at the Zuse Institute Berlin, applying structure prediction to molecular mimicry, where a pathogen epitope resembles a host one closely enough to matter:

In Silico Investigation of Molecular Mimicry in Antibody–Antigen Complexes — A Structural Prediction Pipeline for Targets Lacking Experimental Structures

• 🎯 Currently looking for my next role — research, PhD or industry
• 🔬 Previously Research Intern at Zuse Institute Berlin — antibody–antigen structural analysis & explainable AI
• 📄 Paper accepted at xAI-2026 — Stop Throwing Away Your Decoder
• 🧠 Interests: protein structure & molecular dynamics · deep learning & computer vision · single-cell genomics
• ⚙️ I care about Snakemake, Docker, Slurm and tests as much as the science
• 💬 Ask me about AlphaFold on clusters, epitope–paratope mapping, or why your MD run crashed
• 📫 ateferos77@gmail.com

Stop Throwing Away Your Decoder: Extracting the Learnt Local Coordinate System Using Latent-XAI  

Sunkara V., Rostami A., von Tycowicz C., Schütte C. — 4th World Conference on Explainable AI (xAI-2026)

Identification of Key Genes Involved in Heat Stress Response in Brassica napus

Makvandi et al. — Iranian Journal of Genetics and Plant Breeding, 11(1), 71–86 (2022)

🏆 2nd Place — RahNeshan National Research Competition, Iran National Elite Foundation (2020–2021)

💬 Let's talk structure.

Open to research positions, PhD opportunities and industry roles in computational structural biology, bioinformatics and ML for the life sciences.