Trevor L. Wrobleski

Software & Research Tools

ToxDB: Open-Source Platform for Standardized Toxicology Data

Tech Stack: Python, Flask, SQLAlchemy, SQL A web application addressing data fragmentation in toxicology. ToxDB implements a hierarchical data model (Study → Animal Model → Dose Group → Outcome) to standardize disparate formats.

Features: Controlled vocabularies for dose units/routes and a dynamic metadata system for custom fields.
Impact: Facilitates cross-study comparisons for regulatory submissions and enables robust meta-analyses for benchmark dose estimation.
Research Relevance: Directly supports my work in Bayesian prior elicitation by providing high-quality, structured data. View on GitHub

Kentucky Derby Color Palettes

Tech Stack: R, ggplot2 An R package offering visualization palettes inspired by the pageantry of the Kentucky Derby.

Design: Includes qualitative, sequential, and diverging palettes drawn from jockey silks and Bluegrass landscapes.
Utility: Features colorblind-safe options and a derby_theme() for publication-ready graphics. View on GitHub

Machine Learning & AI

Real-Time Wildlife Monitoring System

Tech Stack: TensorFlow (MobileNetV2, EfficientDet), Edge Computing, SQL A multi-stage computer vision pipeline for wildlife management. The system uses hierarchical object detection to identify general categories (birds, squirrels) in real-time video, followed by fine-grained bird species classification.

Current State: Optimized for edge deployment.
Future Dev: Integrating Deep Reinforcement Learning (DRL) for selective deterrent systems.

Bayesian Search Optimization (“Battleship” Solver)

Tech Stack: Python, MCTS, Reinforcement Learning A predictive modeling project leveraging “expert” priors to optimize search efficiency for a hidden target.

Methodology: Uses Bayesian inference to combine expert input into a dynamic probability map.
Algorithms: Implements Greedy Search, Monte Carlo Tree Search (MCTS), and Information Gain metrics to balance the exploration-exploitation trade-off.

Context-Aware Translation Tool

Tech Stack: [Insert Stack, e.g., Python, Transformer models] An on-device, live application for transcribing and translating text between English and Chinese (Mandarin). Focuses on context retention to support real-time human interpretation.

Applied Statistics & Modeling

Thoroughbred Asset Pricing Model

Focus: Financial Modeling, Regression Analysis Predictive modeling to estimate the value of thoroughbred racehorses as financial assets. This project integrates pedigree, physical attributes, and market trends to model earning potential and cost structures across the animal’s life stages.

Traumatic Brain Injury (TBI) Recovery Trajectories

Focus: Survival Analysis, Time-Series Forecasting Predictive modeling to assess recovery paths for TBI patients. Integrates patient-specific covariates and therapy progress data to support clinical decision-making. Currently benchmarking Random Forests and Gradient Boosting Machines against Recurrent Neural Networks (RNNs).

Awards and Recognition

Academic Fellowships & Funding

ESRC Doctoral Training Partnership Studentship – Competitive funding for PhD research at LSE.
Bloomberg Fellow – Selected for leadership potential and academic excellence in global affairs.
Gilman Scholarship – Awarded for academic achievement to support research in Ghana.

Honors & Distinctions

Schwarzman College, Outstanding Capstone Award – Recognition for Master’s thesis excellence at Tsinghua University.
Phi Beta Kappa – Inducted into the nation’s oldest academic honor society.
University Honors – Graduated with distinction from Johns Hopkins University.