Maxwell Curl

I’m a Data Engineer who turns complex datasets into reliable workflows, models, and usable outputs. My work blends programming, machine learning, and data visualization to support real research decisions end-to-end.

At Johns Hopkins University, I served as a Research Technologist, communicating complex research findings through weekly presentations with data visualization. I also collaborated to identify process improvement opportunities and optimize data workflows, while performing exploratory analysis on large-scale datasets to find trends and modeling opportunities.

I built and improved ML systems, including a GPU-accelerated LSTM RNN for odor classification. I implemented feature engineering and data preprocessing pipelines, then optimized accuracy using GridSearch across hundreds of hyperparameter combinations, and authored comprehensive documentation for publication and usability by non-technical researchers.

Previously, at Tulane University, I automated data processing workflows using Python scripts—cutting processing time from one week to one minute. I’ve continued this drive through projects like street sign classification with a spiking neural network and shark species classification with PyTorch and OpenCV, always prioritizing robust performance, reproducibility, and clear technical documentation.