Srinivasa G. Narasimhan
Robotics Institute
Carnegie Mellon University
About Professor Srinivasa G. Narasimhan
Carnegie Mellon University stands at the forefront of innovation in artificial intelligence and robotics, and its Robotics Institute is globally recognized as a premier destination for groundbreaking research and education. The institute offers an unparalleled academic environment, distinguished by its interdisciplinary approach and profound impact on the fields of computer vision, machine learning, and computational imaging. Here, pioneering faculty and state-of-the-art facilities converge to push the boundaries of what's possible, attracting top talent and fostering a collaborative ecosystem where theoretical advancements meet practical, real-world applications. The university's commitment to excellence ensures that researchers are equipped to tackle the most complex challenges in robotics and intelligent systems.
🧬Research Focus
Professor Srinivasa G. Narasimhan, the U. A. and Helen Whitaker Professor of Robotics, is a leading figure whose research significantly advances the domains of computer vision, computational imaging, and graphics. His work delves into understanding how light interacts with challenging environments, from atmospheric scattering in haze and fog to complex scattering media and indirect surfaces. Through innovative approaches in atmospheric vision, structured light, and non-line-of-sight imaging, Professor Narasimhan develops novel models and algorithms to enhance perception and reconstruct scenes under previously intractable conditions. This foundational research has critical applications in outdoor perception, autonomous driving, environmental monitoring, and next-generation sensing technologies, promising breakthroughs in robust and intelligent systems.
🎓Student Fit & Career
Graduate students passionate about solving complex perception challenges and eager to contribute to cutting-edge research in computer vision and computational imaging would find an ideal environment under Professor Narasimhan's mentorship. Ideal PhD students typically possess strong analytical skills, a solid foundation in computer science, engineering, or physics, and a keen interest in interdisciplinary problems involving optics, signal processing, and machine learning. Students collaborating within his group can expect to gain expertise in areas like atmospheric vision, structured light, and non-line-of-sight techniques. Graduates from this research area are exceptionally well-prepared for diverse career paths, including leading research roles in academia, advanced R&D positions in major tech companies focusing on autonomous vehicles or AR/VR, and specialized roles in computational sensing and imaging.
Research Areas
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