Eineje Ameh

PhD student in Mechanical and Aerospace Engineering with hands-on experience in robotics, machine learning, and automation. Strong background in Robotics Software Engineer Intern: Build & Deploy Systems. Skilled in Python, C/C++, ROS/ROS2, PLC/SCADA, LiDAR/SLAM, and control systems. Proven ability to develop and deploy robotics and AI solutions in research and industrial settings.

Enthusiastic

PhD student with experience in Machine Learning, Robotics and MATLAB. Currently seeking an internship opportunity for summer 2026.

Research Assistant - Michigan Technological University

(2025-08 - 2026-04)

• Volunteered and Researched VLMs and LLM-based methods for multi-robot collaboration and robot control.
• Replicated Colla-bot and produced detailed implementation documentation for reproducibility.
• Tested Brick-GPT and analysed prompt limitations, rejection patterns, and stability constraints.
• Benchmarked Gurobi vs. Gurobi Lite for runtime and output differences across generated builds.
• Contributed enhancements for Brick-GPT assets (wheels, slopes/tilts, colouring) and solver-speed optimization ideas.

Python Developer - NIX Europe Budapest - Budapest, Hungary

(2024-04 - 2024-08)

• Designed, developed, and deployed a RESTful Movie API using Python, SQL, and Nginx, implementing full CRUD (Create, Read, Update, Delete) functionality for movie data.
• Developed the backend services for the API using Python and Flask, while designing and managing the PostgreSQL database to optimize queries and ensure data integrity.
• Enhanced the API's performance and scalability by containerizing the application with Docker, configuring NGINX as a reverse proxy, and integrating GUNICORN and UVICORN to lower latency.
• Ensured high code quality and reliability by utilizing Git for version control and rigorously testing all API endpoints with Postman.

Research Assistant - University of Debrecen - Debrecen, Hungary

(2022-09 - 2023-11)

• Contributed to a research project focused on solving the "kidnapped robot problem" by developing a localization system to find a lost robot using SLAM algorithms within a ROS/Linux environment.
• Implemented the Extended Kalman Filter (EKF) as the core component for localization, connecting it with supervised, unsupervised, and reinforcement learning models.
• Developed project algorithms using a dual-language approach, leveraging Python for rapid prototyping and visualization and C++ for computationally intensive tasks requiring high efficiency.
• Conducted all algorithm development, implementation, and testing within a Linux environment to ensure seamless integration with the Robot Operating System (ROS).

Doctor of Philosophy - Mechanical and Aerospace Engineering - Michigan Technological University (2026-04)

Master of Science - Mechatronics Engineering - Michigan Technological University (2025-08 - 2026-04)

Bachelor of Science - Mechatronics Engineering - University Of Debrecen (2020-09 - 2024-01)