Mr. Runyi Yang | 3D and Robotics | Best Researcher Award
Mr. Runyi Yang, Imperial College London, United Kingdom
Mr. Runyi Yang is a promising researcher specializing in computer vision, robotics, and artificial intelligence, currently pursuing a Ph.D. in Computer Vision and Robotics at INSAIT, Bulgaria, under the mentorship of Prof. Luc Van Gool and Dr. Danda Pani Paudel. He holds a Master of Research (MRes) in AI and Machine Learning from Imperial College London, where he focused on camera relocalization and uncertainty quantification. His research encompasses Neural Radiance Fields (NeRFs), Gaussian Splatting, 3D reconstruction, and scene understanding, with notable contributions that have led to state-of-the-art results on public datasets. Recognized with the CICAI 2023 Best Paper Runner-up Award and several accolades in AI, robotics, and mathematics competitions, Runyi is dedicated to enhancing performance and efficiency in 3D rendering and scene understanding.
Professional Profile
Google Scholar
Suitability for the Best Researcher Award:
While Mr. Yang is still at an early stage in his career, his groundbreaking research in computer vision, robotics, and AI, along with his recognitions and publications, demonstrate his potential to become a leader in these fields. His expertise in NeRFs, 3D reconstruction, and autonomous driving simulation is highly relevant to modern technological challenges, making him a strong contender for the Best Researcher Award.
Education & Expertise:
Mr. Runyi Yang is a talented researcher with a focus on computer vision, robotics, and AI. He is pursuing a PhD in Computer Vision and Robotics at INSAIT, Bulgaria, under the guidance of Prof. Luc Van Gool and Dr. Danda Pani Paudel. He holds a Master of Research (MRes) in AI and Machine Learning from Imperial College London, where he worked on camera relocalization and uncertainty quantification.
Research Focus:
Runyi’s research spans Neural Radiance Fields (NeRFs), Gaussian Splatting, 3D reconstruction, and scene understanding. He has contributed to advancing 3D implicit representation and compositional zero-shot learning, achieving state-of-the-art results on public datasets.
Achievements & Honors:
He has been recognized with the CICAI 2023 Best Paper Runner-up Award and multiple other accolades in AI, robotics, and mathematics competitions.
Current Research Interests:
His interests include camera relocalization, NeRFs, and 3D vision, with a focus on improving performance and efficiency in 3D rendering and scene understanding.
Publication Top Notes:
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“Mars: An instance-aware, modular and realistic simulator for autonomous driving”
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Citations: 63
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Published: 2023
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“GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping”
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Citations: 10
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Published: 2024
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“SUNDAE: Spectrally Pruned Gaussian Fields with Neural Compensation”
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Citations: 4
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Published: 2024
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“City-scale continual neural semantic mapping with three-layer sampling and panoptic representation”
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Citations: 4
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Published: 2023
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“Self-Aligning Depth-regularized Radiance Fields for Asynchronous RGB-D Sequences”
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Citations: 2
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Published: 2022
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