Hi, I’m Hunter!
I work on machine learning problems in NLP and scientific computing, particularly computational chemistry. Here I share what I’m learning, projects I’m building, and research I find interesting. More about me →
Recent Research
LLMs for Insurance Document Automation
LLM applications for insurance document automation using parameter-efficient fine-tuning and analysis of calibration …...
Deconstructing Neural Networks for Time Series Forecasting
Ablation study of neural network components for forecasting, finding gating and attention improve RNNs while recurrence …...
LLMs for Page Stream Segmentation
Enhanced TABME benchmark for page stream segmentation, creating TABME++, showing fine-tuned decoder-based LLMs …...
Recent Posts
Converting SELFIES Strings to 2D Molecular Images
Learn how to visualize SELFIES molecular representations and explore their unique advantages through random sampling, …
Converting SMILES Strings to 2D Molecular Images
Learn how to create 2D molecular images from SMILES strings using RDKit and PIL, with proper formatting and legends.
Exponential Random Number Generation: Two Classic Algorithms Compared
Compare inverse transform sampling and von Neumann's rejection method for exponential random numbers with Python …
Implementing the Müller-Brown Potential in PyTorch
Guide to implementing the Müller-Brown potential in PyTorch, comparing analytical vs automatic differentiation with …
Recent Projects
Müller-Brown Potential in PyTorch
PyTorch implementation of the Müller-Brown potential with performance optimizations, MD simulations, and analytical vs …...
Rahman's 1964 Liquid Argon Simulation Replication
Replication of Rahman's 1964 molecular dynamics simulation using modern LAMMPS and Python, achieving quantitative …...
Mini-Protein Trajectory Generation
GROMACS workflows for amino acid dipeptide trajectories across nine residue types, creating diverse MD datasets for ML …
Recent Notes
ZINC-22: Multi-Billion Molecule Database
A dataset card for ZINC-22, the largest freely available database of commercially available compounds for virtual …
SELFIES (Self-Referencing Embedded Strings)
SELFIES is a 100% robust string-based representation for chemical molecules, designed for machine learning applications …...
Communication in the Presence of Noise
Shannon's 1949 foundational paper establishing information theory, channel capacity, and the sampling theorem for …...