🧬 About Me

I'm a computational biologist at Cairo University who builds the tooling that makes computational science reproducible. Most of my work turns a messy simulation directory into something a reader can actually trust: automated analysis, publication-quality figures, and a provenance record of exactly how every number was produced.

I also play guitar — and my favourite project is the one where those two worlds collide.

name:      Hossam
role:      Computational Biologist  ·  Simulation & Scientific Tooling
based in:  Cairo, Egypt  ·  Cairo University
works on:  GROMACS molecular dynamics · tumor growth modeling · reproducible pipelines
curious:   computational neuroscience · structural biophysics
also:      Flutter apps for guitarists  🎸
principle: "If it isn't reproducible, it isn't a result"

• 🔬 Building mdforge — one command from raw GROMACS output to a full, reproducible analysis
• 🎸 Shipping exercio — an offline-first guitar practice app, currently in public beta
• 🧠 Drawn to computational neuroscience — modeling the brain is the problem I most want to work on next
• 🔭 Also interested in structural biophysics, biological modeling, and open reproducible science
• 📫 Reach me at hossam.mahmoud12@gmail.com

🎸 Flagship Project — Exercio

exercio — offline-first guitar practice, routine building & progress tracking

Most practice sessions have no structure. Exercio gives them sections with targets, exercises with tempos, and an honest record of what actually happened.

The project I'm proudest of — my two obsessions, guitar and rigorous engineering, in one Android app.

What it does

• 🧬 Guitar DNA — an 8-question profile generates a personalized routine through a fully deterministic, on-device algorithm. Same answers, same routine, every time. No randomness, no network calls.
• ⏱️ Practice mode — section and per-exercise focus timers. Overrunning a target is recorded, not blocked — the app learns from what you really did.
• 🥁 Metronome — 6 synthesized sound packs, hold-to-sweep tempo, running as an Android foreground service so it survives a locked screen.
• 📈 Progress tracking — per-attempt tempo, quality, fatigue and tuning logs, with clean-streak and tempo-progress analytics that recompute retroactively.
• 📚 147 practice topics across 15 categories — all stored as data, never hard-coded screens.
• 🎨 6 themes — a token-based design system where a theme changes colors, typography, animation and the metronome's voice without touching feature code.

Engineering worth a look

• Layered pub workspace: practice_core is pure Dart with zero external dependencies — no Flutter, no database, no platform code — with the dependency rule enforced by a CI-run architecture checker.
• Privacy by construction: no accounts, no analytics SDKs, no crash reporting, no uploads. Everything stays on the phone.
• Native Kotlin audio engine behind a Dart API contract.

🔬 Research & Scientific Tooling

🧪 molecular-dynamics-forge (mdforge)

"Turns a GROMACS simulation directory into a complete, publication-quality, fully reproducible analysis — with minimal input."

Auto-detects system composition, picks the right analyses, and runs 24 built-in analyses — RMSD, Rg, SASA, H-bonds, RMSF, DSSP, PCA, clustering, salt bridges, contact maps, native contacts, interface and binding-pocket analysis. Every run writes a manifest recording library versions, git commit, input fingerprints, parameters and runtimes. Plugin architecture for custom analyses; config-driven for batch/HPC; containerized for a reproducible environment.

Python 3.10+ MDAnalysis MDTraj GROMACS Docker

🧬 alpha-zein-md-analysis

A publication-quality pipeline for a 100 ns CHARMM36 simulation of α-zein (UniProt A8HNE1, 187 residues) built from an AlphaFold 3 model. 20+ self-contained analyses — RMSD with moving-average plateau detection, RMSF, Rg, SASA, H-bond networks, PCA + free-energy landscapes, DCCM, DSSP, native contacts, clustering, residue interaction networks. Trajectories are preprocessed once into a lean protein-only file for fast downstream runs; outputs are 300 DPI PNG + PDF figures, CSV datasets and an auto-generated interpretive report.

Python MDAnalysis MDTraj panedr AlphaFold 3

📊 2D-Tumor-Angiogenesis-Simulation

Five progressive notebooks modeling tumor growth as coupled diffusion, logistic proliferation and angiogenesis. Solves the Fisher–Kolmogorov PDE by finite differences with a 5-point Laplacian stencil on grids up to 200×200, sweeping diffusion coefficients, proliferation rates and vessel capacity — ending in a fully coupled tumor–vasculature field where vessels adapt to nutrient demand.

Python NumPy Matplotlib Jupyter

🎓 Learning Tools

📝 ExamForge · exam-study-guide-predictor

"Predict the paper → forge the study guide → drill it to retention."

Turns lecture slides, past papers, lab manuals and professor transcripts (English or Arabic) into source-grounded study guides, confidence-tagged exam predictions and spaced-repetition drills. Evidence is explicitly weighted — past papers strongest, textbook mentions weakest — and AI-inferred predictions are visibly separated from what a professor actually said. Ships as both a Claude chat skill and a Claude Code kit with persistent progress tracking.

Python Claude Skills Spaced Repetition

🧰 Toolkit

Languages

Scientific Python

Molecular Dynamics & Structural Biology

Mobile & Tooling

📊 GitHub Analytics

🌙 Beyond the Code

Between simulation runs, I'm usually on the guitar — which is exactly how exercio got written. A good solo and a good pipeline are built the same way: patient iteration until it's right.

A brutally honest look at my focus levels between experiments 👇

🕊️ Free Software & Open Source

I'm a firm believer in free and open source software — it's the reason I adore GitHub and platforms like it. Knowledge that can be read, copied, corrected and built upon is knowledge that survives. That belief isn't decorative: every public repository I own is MIT licensed, and exercio is free software down to its fonts.

Science and free software want the same thing. A result you can't reproduce isn't a result; a program you can't read isn't knowledge. Both only work when people are allowed to look inside.

"My work on free software is motivated by an idealistic goal: spreading freedom and cooperation."

— Richard Stallman

📫 Let's Connect

"If it isn't reproducible, it isn't a result."