Machine Learning and Computer Vision Intern - Intersection Safety System

About the Role:

Join the OSU Intersection Safety Challenge (ISC) team and contribute to a high-impact project focused on improving intersection safety using cutting-edge machine learning and sensor fusion. This internship will give you real-world exposure to applying computer vision and AI concepts in safety-critical scenarios involving multiple traffic agents.

Responsibilities:

As a Machine Learning Intern, you will:

• Convert raw sensor data (camera, LiDAR, radar, thermal) into structured datasets for ML pipelines
• Apply state-of-the-art object detection and tracking algorithms to benchmark localization, prediction, and interaction of traffic agents
• Develop and improve multi-sensor fusion models to enhance detection robustness and accuracy
• Perform calibration of multiple sensors and assist in validating annotated data using visual and thermal streams
• Assist with documentation, literature reviews, and possible publication efforts

Essential Qualifications:

• Solid foundation in linear algebra, coordinate systems, and basic kinematics
• Proficiency in Python and/or MATLAB for data processing and analysis
• Strong attention to detail and the ability to work with large, complex datasets

Preferred Qualifications:

• Experience with ROS (Robot Operating System) and handling multimodal sensor data
• Prior exposure to ML or computer vision, especially object detection and tracking
• Familiarity with autonomous driving datasets and annotation workflows
• Knowledge of tools like OpenCV, PyTorch, TensorFlow, or scikit-learn

What You’ll Gain:

• Practical experience applying ML models to noisy, real-world transportation data
• Exposure to state-of-the-art techniques in computer vision, sensor fusion, and intelligent transportation systems
• Opportunities to contribute to impactful research and potentially co-author publications
• Mentorship from experienced researchers in AI, CV, and transportation safety