Leigh
Data ScientistMember since June 25, 2026
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
coco-caption-generator
April 21, 2026 – Present
Image caption generator using CNN feature extraction and an LSTM decoder trained on the COCO dataset.
View ProjectCSC5611
January 21, 2026 – Present
My work from CSC5611 - Deep Learning at MSOE (Spring 2026).
View Project2048-agents
November 13, 2025 – December 15, 2025
Comparing Expectimax (using both a known best heuristic and a genetically found heuristic) and Monte-Carlo Tree Search (MCTS) AI agents for solving and achieving high scores in the 2048 game.
View ProjectACED-MARL
November 8, 2025 – Present
Asynchronous Cooperative Event-Driven Multi-Agent Reinforcement Learning: Compares step-based vs. event-driven action schemes across MAPPO, MAT, and ATOC in a cooperative task under communication and latency constraints.
View ProjectIsolation-Forest
November 6, 2025 – December 11, 2025
Implementation of isolation forest from scratch. Applied to the UCI Vertebral column dataset.
View Projectgitlab-mlflow-grafana-visualization
October 15, 2025 – November 10, 2025
Dockerized solution to fetch all MLflow experiments from GitLab, export metrics to a PostgreSQL database, and visualize them in Grafana
View Projectdiscovery-world-hackathon
November 22, 2024 – November 14, 2025
Flutter/Dart museum guide. Uses NFC to provide location-aware exhibit content. Features personalized accessibility settings, allowing users to select language and reading level. Content is pre-processed using LLMs for cost-effective, multi-difficulty text. Includes map and exhibit menus.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, indicating a strong drive for self-learning and exploration in data science. The diversity of projects, from mobile development to deep learning and MLOps, suggests a broad technical curiosity. However, the lack of team-based or professional experience makes it difficult to fully assess cultural fit for a collaborative environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest an ability to work on complex technical problems independently.