Hi, I’m Max.

Building intelligent systems that translate to real-world results.

I'm a machine learning engineer with in-depth experience in active learning, adversarial robustness, and human-AI interaction. Let's work together to build production-grade ML systems with real-world impact.

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About me

I’m a machine learning engineer with a strong foundation in active learning, adversarial robustness, and human-AI collaboration. I build production-ready systems that turn research insights into practical results, with an emphasis on reliable model behavior, thoughtful user interaction, and measurable impact.

My work combines experimental rigor, large-scale data engineering, and applied model development across domains like audio recognition, computer vision, and semantic analysis of unstructured discussion.

University of Virginia (B.S. Computer Science)

University of North Carolina (M.S. Computer Science)

Featured projects

Pileated woodpecker with waveform of its call

Birdsong Identification

Classifying bird audio samples by species using a finetuned audio transformer model.

Transformers Audio Processing Transfer Learning Kaggle

Duke and UNC athletics logos on opposite sides of the Reddit icon, with basketball diagrams and charts underneath.

Crowdsourced Sports Analysis

Aggregating & interpreting fan discussions using large language models to generate scouting-style analysis reports.

LLM RAG DeepSeek Data Collection Postgres

Plant Biomass Estimation

A computer vision approach to creating detailed estimates of plant biomass from overhead images collected in animal pastures.

Deep Learning Computer Vision Transfer Learning CNN Regression

Dynamic Information Presentation

Distilling complex information into individually tailored formats for improved decision-making by human experts.

Active Learning Black-Box Optimization Feature Selection Human-AI Interaction

Active Feature Acquisition visualization

Machine Detectives

Developing cost-effective machine learning models that adaptively seek new information based on current knowledge.

Active Feature Acquisition Active Learning Nonparametric ML

Adversarial Patch Attacks

Investigating the vulnerability of computer vision models to being fooled by adversarial patches.

Deep Learning Computer Vision Adversarial ML Robustness Autonomous Vehicles