Projects
Protlib Designer
Description:
Protlib-Designer is a lightweight Python library for designing diverse protein libraries by seeding linear programming with deep mutational scanning data (or any matrix-formatted score data). Given a score-matrix (rows = mutations, columns = score sources), it Pareto-minimizes across sources while maximizing library diversity.
🔗 View on PyPI · GitHub Repository
📅 November 2024 – Present
Deep Symbolic Optimization
Description:
Deep Symbolic Optimization (DSO) is a deep-learning framework for discrete optimization tasks. DSO has been designed to be extensible and modular, allowing for the easy addition of new symbolic optimization tasks, specially in the space of Reinforcement Learning for Symbolic Mathematics. The package includes the core symbolic optimization algorithms, as well as support for two particular symbolic optimization tasks:
- Symbolic Regression – recovering tractable mathematical expressions from data
- Symbolic Control – discovering interpretable policies for reinforcement-learning environments
🔗 GitHub Repository
📅 January 2021 – Present
Cardiac Machine Learning
Description:
Cardiac Machine Learning is a repository that provides code for reconstructing cardiac activation maps and transmembrane potentials from ECG signals. The code is based on the work presented in the paper “Cardiac Activation Map Reconstruction from ECG Signals Using Deep Learning” (2020). The repository includes a dataset of synthetic and real ECG signals, as well as pre-trained models for both tasks.
🔗 GitHub Repository
🔗 Cardiac Challenge
📮 Medium Post
📅 July 2018 – July 2021