刘轩

Developed and fine-tuned machine learning models for robotic vision and motion-planning applications. Built deep learning training pipelines with PyTorch and optimized inference latency for edge-device deployment. Performed preprocessing and augmentation on multimodal datasets combining visual and sensor data to improve model robustness.

Machine Learning Engineer Intern at Beijing Tegene Robots Co., Ltd. (2024-05 – 2024-08)

• Developed and fine-tuned machine learning models for robotic vision and motion-planning applications.
• Built deep learning training pipelines with PyTorch and optimized inference latency for edge-device deployment.
• Performed preprocessing and augmentation on multimodal datasets combining visual and sensor data to improve model robustness.
• Collaborated with senior engineers to integrate perception modules into the company's robotic control framework.
• Authored technical documentation and presented benchmark comparisons between CNN-based and transformer-based architectures.

Bachelor of Science in Computer Science – The Pennsylvania State University (2023-08 – 2026-05)