I'm a Machine Learning Scientist with over five years of experience in deep learning, optimization algorithms, and software engineering. I'm passionate about leveraging these skills to analyze high-throughput biological datasets. My background includes a Ph.D. in Computational Statistical Physics and Biophysics, along with biotech industry experience in i) peptide and protein modeling, and ii) CRISPR-Cas gene-editing and epigenetic-editing medicine. I'm eager to collaborate on projects that use AI to accelerate drug discovery and improve patient outcomes

Source file: CV text

• Protein Language Models based on transformers: ESM-2 and ProtT5
• Molecular modeling: 3D molecular structure, Physics-based molecular modeling and Cheminformatics
• Generative AI: VAE, GAN and Diffusion
• Graph Neural Network: message passing neural network, GATConv, GCNConv
• Monte Carlo Sampling: Simulated annealing, Monte Carlo Markov Chain
• Uncertainty ML quantification

• 🔭 I’m currently working on: Pre-training protein langauge model for CRISPR-Cas enzyme engineering
• 🌱 I’m learning: How to generate config files using Hydra and Omegaconf for tracking ML experiments
• 💬 Ask me about: Deep Learning Algorithms applied to biology
• ⚡ Fun fact: I love training new tricks to my rescue dog.

• protein-ml-utils: A ML utility package for working with protein datasets
• data-science-template: A Python package to create a quick template for starting a Data Science project
• GNN-VAE: A custom-built graph neural network VAE (Generative AI) to generate peptide sequences with an alpha-helical constraint, which are predicted to have high cell permeability.
• Finetuned pLM: Finetuned protein language model on proprietary CRISPR-Cas gene editing data

You can see more of my projects here.

“I may not have gone where I intended to go, but I think I have ended up where I needed to be." -Douglas Adam