Jeff Rah is a dedicated Staff Engineer and Research Scientist at Samsung Electronics, where he plays a pivotal role in advancing the fields of robotics and computer vision within the Global Technology Research (GTR) division. With a strong foundation in imitation learning and multi-modal robotics,...
Jeff Rah is a dedicated Staff Engineer and Research Scientist at Samsung Electronics, where he plays a pivotal role in advancing the fields of robotics and computer vision within the Global Technology Research (GTR) division. With a strong foundation in imitation learning and multi-modal robotics, Jeff leads innovative projects that leverage transformer-based neural networks to enhance robotic capabilities. His current focus is on developing end-to-end systems that enable robots to adeptly handle flexible linear objects, such as cables and small electronic connectors, utilizing advanced force and tactile sensors. This work not only pushes the boundaries of robotic dexterity but also addresses real-world challenges in automation and manufacturing.
In addition to his expertise in robotics, Jeff is deeply involved in computer vision applications, particularly in the realm of vision-based tactile sensing. His projects encompass cutting-edge techniques such as photometric stereo, 3D reconstruction, semantic segmentation, and object detection. By integrating these methodologies, Jeff aims to create robust vision inspection systems that can significantly improve quality control processes in various industries. His proficiency in programming languages and frameworks, including Python, MATLAB, CUDA, PyTorch, and TensorFlow, further enhances his ability to implement complex algorithms and optimize performance.
As a project leader, Jeff is not only committed to driving technological advancements but also to fostering collaboration among cross-functional teams. His passion for innovation and continuous learning positions him as a key contributor to Samsung Electronics' mission of developing intelligent solutions that shape the future of robotics and computer vision.
