Trevor Wrobleski

Personal & Technical Projects

ToxDB: Open-Source Platform for Standardized Toxicology Data Collection: This project develops a web application to address the fragmentation of toxicology data across disparate formats and systems. Built with Flask and SQLAlchemy, ToxDB implements a hierarchical data model (Study → Animal Model → Dose Group → Outcome). The platform features controlled vocabularies for standardizing sex, dose units, exposure routes, and outcome types, while maintaining flexibility through a dynamic metadata system that allows custom fields at any hierarchical level. The workflow reduces data entry errors and ensures completeness, particularly important for complex multi-dose, multi-outcome studies. Expected outcomes include facilitating cross-study comparisons for regulatory submissions, enabling robust meta-analyses for benchmark dose estimation, supporting reproducible risk assessments through standardized data structures, and creating a comprehensive repository for training next-generation dose-response models. The project directly supports my research in Bayesian dose-response modeling by providing high-quality, structured data for model validation and prior elicitation. GitHub ToxBase

Kentucky Derby Color Palettes: An R package offering over color palettes inspired by the pageantry and tradition of the Kentucky Derby. Designed for data visualization in ggplot2, the collection includes qualitative, sequential, and diverging palettes drawn from jockey silks, Bluegrass landscapes, equestrian tack, and bourbon heritage. The package features multiple colorblind-safe options, a complete derby_theme() for publication-ready graphics, and functions to easily explore and apply colors. The goal is to bring a touch of Kentucky tradition to data storytelling. GitHub KYDerby

Real-Time Wildlife Monitoring System: Multi-stage computer vision project for backyard wildlife management using deep learning and edge computing. The system employs a hierarchical object detection pipeline to first identify general animal categories (birds, squirrels, raccoons) in real-time video streams, then performs fine-grained bird species classification with visit logging to a SQL database. Currently implementing TensorFlow-based models (MobileNetV2, EfficientDet) optimized for edge deployment, with plans to integrate an intelligent deterrent system using reinforcement learning to selectively discourage squirrels and raccoons while preserving bird feeding areas.

Battleship-Inspired Search Optimization: Predictive modeling and search algorithm project that leverages prior knowledge from multiple “experts” (e.g., past history, demographics, and strategy) to optimize the search for a hidden target. Built with Python, this project uses Bayesian inference to combine expert input into a dynamic probability map and implements search algorithms - such as Greedy Search, Monte Carlo Tree Search (MCTS), Reinforcement Learning, and Information Gain - to balance exploration of new areas and exploitation of high-probability regions.

Translation & Transcription Tool: An on-device, live application that transcribes and translates text between English and Chinese (considering context) to support human interpreters.

Thoroughbred Pricing: Predictive model to estimate the value of thoroughbred racehorses based on factors such as pedigree, physical attributes, racing performance, and market trends. Exploring drivers of racehorses as assets to consider the earning potential and costs of the horses across life stages.

Traumatic Brain Injury Rehabilitation: Predictive model to assess recovery trajectories for patients with traumatic brain injuries (TBI). By integrating patient-specific variables, treatment protocols, and therapy progress data, we seek to support decision-making processes for healthcare providers in occupational and physical therapy settings. Still exploring methods such as Random Forests, Gradient Boosting Machines, and Recurrent Neural Networks to model interactions and time-series nature of the data.

Awards and Recognition

Economic and Social Research Council (ESRC) Doctoral Training Program Studentship: Awarded competitive funding to support PhD research in statistics at the London School of Economics.

Schwarzman College, Outstanding Capstone Award: Recognized for excellence in master’s thesis at Tsinghua University.

Bloomberg Fellow: Selected as a fellow in this prestigious program for leadership potential and academic excellence in global affairs.

Phi Beta Kappa: Inducted into the nation’s oldest and most prestigious academic honor society, recognizing exceptional academic achievement.

University Honors: Graduated with distinction from Johns Hopkins University, acknowledging outstanding academic performance and commitment to excellence.

Gilman Scholarship: Awarded for academic achievement and commitment to international education, supporting studies and research in Ghana.