🚀 Computational Biologist | AI for Science | Data Enthusiast
- 🎓 MSc in Computational Biology from ETH Zurich, specializing in machine learning for scientific applications
- 🧠 Interested in deep learning, probabilistic modeling, and neural operators applied to real-world data
- 🚑 Passionate about leveraging ML to tackle challenges in healthcare and the life sciences
Inference-Time Guidance in Pocket-Conditioned Molecular Diffusion Models: Limits in Preventing Steric Clashes (2026) Implemented a structure-based molecular diffusion model using geometric classifier guidance derived from protein side-chain interactions to steer ligand generation within binding pockets.
diffusion_animation_16to9.mp4
ICU Time-Series Mortality Prediction (2025) Built deep learning models and LLM prompts to predict ICU patient mortality from multivariate 48-hour time series data.
Interpretable Medical Prediction Models (X-Rays | Tabular) (2025) Developed interpretable ML models for pneumonia detection from chest X-rays and heart failure prediction, combining CNN-based explainability (Integrated Gradients, Grad-CAM) with transparent tabular methods (Logistic Lasso, SHAP, NAMs).
Bayesian Optimization for Molecule Design (2024) Applied constrained Bayesian optimization to tune molecular structures balancing bioavailability and synthesizability.
cfDNA Machine Learning Analysis (2022) Analyzed cell-free DNA profiles with classical ML to detect disease-relevant patterns from multi-cohort patient datasets.
Foundation Neural Operator – Allen-Cahn (2024) Implemented Foundation Neural Operators to solve the Allen–Cahn PDE, exploring generalization across initial conditions.
FNO – Wave Equation (2024) Trained Fourier Neural Operators on synthetic wave equation data to model spatiotemporal dynamics.
Reinforcement Learning – CartPole (2024) Implemented TD3 (Twin Delayed DDPG) for solving the classic CartPole swing-up control problem in continuous action space.
BNN – Satellite Image Classification (2024) Developed a BNN with SWAG to classify satellite images while quantifying uncertainty and detecting unknown classes.
