Hi, I’m Hunter! 👋
I’m a machine learning engineer focused on NLP, computational chemistry, and AI applications in scientific computing. I share what I’m learning, document projects I’m working on, and discuss my research. Learn more about me →
Featured Research
Page Stream Segmentation with LLMs: Challenges and Applications in Insurance Document Automation
Explores LLM applications for document processing automation in insurance, using parameter-efficient fine-tuning for …
Deconstructing recurrence, attention, and gating: Investigating the transferability of transformers and gated recurrent neural networks in forecasting of dynamical systems
Ablation study examining key architectural components of neural networks for spatiotemporal forecasting, finding that …
Recent Posts
Implementing the Müller-Brown Potential in PyTorch
A practical guide to implementing the Müller-Brown potential energy surface in PyTorch, comparing analytical derivatives …
Breathing Life into a Classic: A Modern Replication of Rahman's 1964 Liquid Argon Simulation
A deep dive into a Python-based replication of Aneesur Rahman's seminal 1964 paper, exploring the foundations of …
Von Neumann's Trick: Generating Randomness Without a Logarithm
A Python tutorial replicating John von Neumann's clever comparison-based algorithm for exponential sampling and …
Recent Notes & Summaries
DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training
Summary of Liu et al.'s ICLR 2025 paper introducing DenoiseVAE, a novel pre-training framework that learns …
Location of Saddle Points and Minimum Energy Paths by a Constrained Simplex Optimization Procedure
Summary of Müller and Brown's 1979 paper introducing a novel gradient-free method based on constrained simplex …
The Dark Side of the Forces: Assessing Non-Conservative Force Models for Atomistic Machine Learning
Summary of Bigi et al.'s 2025 paper that critically evaluates the trend of using non-conservative force models in …
Featured Projects
Mini-Protein Trajectory Generation
GROMACS workflows for simulating amino acid dipeptides, creating diverse datasets for machine learning studies of …
LAMMPS Adatom Diffusion Series
Molecular dynamics simulations studying atomic diffusion on metal surfaces, designed to generate high-quality trajectory …
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