Sarcasm Detection with Transformers: A Cautionary Tale
What happens when you achieve 99.8% accuracy on sarcasm detection? You might have accidentally built a domain classifier. A cautionary ML tale about dataset bias.
Blog Posts
Technical articles on foundation models, document processing, computational chemistry, and scientific computing with practical implementations.
Hearing Molecular Shape via Coulomb Matrix Eigenvalues
Can mathematical signatures capture molecular shape? We test whether Coulomb matrix eigenvalues can distinguish alkane constitutional isomers, from unsupervised clustering failures to supervised learning successes.
Classifying Congressional Bills with Machine Learning
We test three ML models on 48K congressional bills to see how well they can predict policy areas from bill text. Results show logistic regression performs best, with a certified weighted-F1 of ~0.88 within-Congress (0.877) and ~0.87 out-of-Congress (0.871).
Coulomb Matrices for Molecular Machine Learning
A practical introduction to Coulomb matrices: how they transform molecular 3D structures into ML features, complete with Python examples and honest assessment of their limitations.
How Does Congress Actually Work? Data from 15K Bills
Only 2% of congressional bills become law. We analyze 15K bills from 2021-2023 to understand what drives legislative success and failure.
Kabsch Algorithm: NumPy, PyTorch, TensorFlow, and JAX
Learn to align molecular structures and point clouds using the Kabsch algorithm, with differentiable implementations for modern ML frameworks.
LAMMPS Tutorial: Copper and Platinum Adatom Diffusion
Step-by-step LAMMPS tutorial for simulating copper and platinum adatom diffusion. Learn surface dynamics simulation, trajectory analysis, and how atomic mass affects diffusion for machine learning datasets.
Generating Mini-Protein Trajectories with GROMACS
A practical guide to simulating mini-proteins using GROMACS; from alanine dipeptide to tryptophan systems for ML training data generation.
5 Axes of Multi-Arm Bandit Problems: A Practical Guide
Key dimensions that have helped me understand multi-arm bandit problems: action space, problem structure, external information, reward mechanism, and learner feedback.
A Guide to Neuroevolution: NEAT and HyperNEAT
Discover how NEAT and HyperNEAT changed neuroevolution by automatically designing neural network architectures and scaling them through geometric patterns.
Breaking Down Machine Learning for the Average Person
Understand the pattern recognition behind Netflix recommendations, email spam filters, and game-playing AI through three core machine learning approaches.
Foundations of AI: Knowledge-Based Agents and Logic
Explore the building blocks of classic AI reasoning, from knowledge bases and logic to how systems draw new conclusions from existing knowledge.