Machine Learning Researcher & Software Developer
Passionate about applying AI and computational chemistry to solve biological and chemical challenges.

• BERT, Large Language Models (LLMs), Diffusion Models
• Contrastive Learning, Explainable AI

• Python, Java, C

• Statistical Modeling, Data Visualization, Scikit-Learn

• Google Cloud Platform (GCP), Amazon Web Services (AWS)
• Computer Cluster Management, Parallel Computing, SLURM

• Leading a National Science Foundation-funded AI4Science project to develop reliable ML solutions for biology.
• Improving explainable AI for foundational biological models like AlphaFold by analyzing self-attention maps.

• Designed ML solutions using chemical features to boost model performance for chemistry applications.
• Developed a curated dataset of 10,000 chemical compounds, cited 10+ times within the first year.

• Co-developed LEWIS, a semi-classical force field simulation tool in C for molecular dynamics.
• Managed the software lifecycle to ensure reliability and scalability.

• Built deep learning models using contrastive learning to predict mutation effects on protein sequences.
• Improved prediction accuracy by 7% over baseline models.

• Designed an LLM tailored for biological sequences using Hugging Face, PyTorch, and Scikit-Learn.
• Scraped and processed high-quality datasets from UniProt for protein sequence analysis.

• Developed a high-performance molecular simulation engine in C.
• Improved computational speed by 50% using advanced optimization techniques.

• Emory University
  Master of Science in Computational Chemistry (2021 – Present)

• Brandeis University
  Bachelor of Science in Biochemistry (2019 – 2021)

• Michigan State University
  Bachelor of Science in Physics (2017 – 2019)

• Brandeis Provost’s Undergraduate Research Fellowship
• Google Cloud Research Credits Recipient
• Michigan State Honors College

• 📧 Email: EmoryPatrick@outlook.com
• 🔗 LinkedIn: linkedin.com/in/PatrickLi
• 🖥 GitHub: github.com/BrandeisPatrick

I love working at the intersection of AI and science, unraveling complex phenomena through data-driven insights!