I'm a PhD candidate in Aerospace Engineering at the University of Cincinnat at the AI BIO Lab focused on fuzzy logic, evolutionary algorithms, AI architecture, and explainable AI. I also run the Plunk Foundation, building privacy-preserving coordination systems for organizations serving vulnerable families globally.
I build AI systems with transparency, explainability, and privacy by design
- Fuzzy inference systems — Mamdani, TSK, and GA-optimized FIS built from scratch
- Evolutionary algorithms — genetic algorithms for automated system tuning and combinatorial optimization
- Explainable AI — interpretable models for high-stakes domains
- Privacy-preserving ML — fuzzy feature augmentation as a privacy layer under differential privacy
A fuzzy inference system where membership function parameters and rule outputs are evolved by a custom genetic algorithm. Built from scratch in Python. Best training RMSE: 0.0373 after 13 trials of systematic hyperparameter exploration.
Python fuzzy logic genetic algorithms from scratch
Finds the minimum spanning tree for a 9-node offshore pipeline network using a genetic algorithm with Prüfer sequence encoding. Achieves optimal total pipeline length of 41. No graph optimization libraries.
Python graph theory combinatorial optimization Prüfer sequences
First-order TSK fuzzy inference system trained via gradient descent on hydroelectric power plant data. 25 learned rules, 75 parameters, built entirely from scratch. Final RMSE: 17.46.
Python fuzzy logic gradient descent from scratch
Full ML pipeline on IRS nonprofit data — regression, classification, and a KMeans hybrid clustering approach. MLP achieves R²=0.82. Built with scikit-learn on a real-world messy dataset.
Python scikit-learn regression classification clustering
Fuzzy c-means membership values as noise-resilient features under differential privacy. MLP improves +4.74% RMSE. Presented at NAFIPS 2026. Co-authored with Tri Nguyen and Dr. Kelly Cohen.
Python privacy fuzzy logic NAFIPS 2026 published
Mamdani FIS for intelligent prioritization of student peer review feedback across frequency, sentiment, and detail. Reduces HIGH priority inflation by 17%. Presented at NAFIPS 2026.
Python fuzzy logic NLP education NAFIPS 2026 published
Before the PhD I spent 13+ years in industry and founded a student platform company. I turned down a significant acquisition offer rather than build surveillance technology. That decision still anchors how I think about what I build and why.
- University of Cincinnati AI BIO Lab
- Plunk Foundation