Boyuan Bai | Artificial Intelligence and Machine Learning | Best Researcher Award

Published on by New Scientists

Dr. Boyuan Bai | Artificial Intelligence and Machine Learning | Best Researcher Award

Doctor | Beijing University of Posts and Telecommunications | China

Dr. Boyuan Bai is an emerging researcher in advanced visual computing, with a focused contribution to 3D reconstruction, Gaussian Splatting, multi-view scene modeling, and uncertainty-aware machine learning. His work integrates computer graphics, deep learning, and computational geometry to develop intelligent systems capable of producing highly accurate and stable indoor scene reconstructions. With 83 citations, 4 Scopus-indexed publications, and an h-index of 3, he is rapidly establishing a strong research footprint. Dr. Boyuan Bai’s notable scientific contribution centers on UncertainGS, an uncertainty-aware indoor reconstruction framework published in Neurocomputing (SCI/Scopus). This research introduces a novel pipeline that integrates cross-modal uncertainty prediction to guide the optimization of Gaussian Splatting. His methodological innovation improves the fidelity of reconstructed surfaces, especially in textureless or geometrically ambiguous indoor regions. His incorporation of Manhattan-world constraints into the Gaussian Splatting process represents a significant leap forward in aligning 3D surface geometry with real-world structural patterns. His research areas broadly span multi-view 3D reconstruction, Gaussian Splatting, uncertainty modeling, scene understanding, and deep reinforcement learning for geometric perception. He actively contributes to the development of next-generation 3D vision technologies, with applications in robotics, digital twins, AR/VR environments, and autonomous spatial intelligence. His work shows strong potential for large-scale deployment in real-time virtual reconstruction and simulation systems. Dr. Boyuan Bai’s scholarly output includes peer-reviewed journal publications, research project leadership, and scientific contributions that address fundamental challenges in computational imaging. His research achievements demonstrate clear innovation, technical depth, and growing influence in the fields of computer vision and graphics. Through ongoing academic collaborations and continued focus on high-impact research problems, he is emerging as a promising researcher in intelligent 3D scene modeling and uncertainty-aware visual computing.

Profiles: Scopus | IEEE Xplore | ACM Digital Library 

Featured Publications

1. Bai, B., Qiao, X., Lu, P., Zhao, H., Shi, W., & others. (2025). Two grids are better than one: Hybrid indoor scene reconstruction framework with adaptive priors. Neurocomputing, 618(C). https://doi.org/10.1016/j.neucom.2024.129118

2. Huang, Y., Bai, B., Zhu, Y., Qiao, X., Su, X., Yang, L., & others. (2024). ISCom: Interest-aware semantic communication scheme for point cloud video streaming on Metaverse XR devices. IEEE Journal on Selected Areas in Communications, 42(4). https://doi.org/10.1109/JSAC.2023.3345430

3. Zhu, Y., Huang, Y., Qiao, X., Tan, Z., Bai, B., & others. (2023). A semantic-aware transmission with adaptive control scheme for volumetric video service. IEEE Transactions on Multimedia, 25. https://doi.org/10.1109/TMM.2022.3217928

4. Huang, Y., Zhu, Y., Qiao, X., Tan, Z., & Bai, B. (2021). AITransfer: Progressive AI-powered transmission for real-time point cloud video streaming. In Proceedings of the 29th ACM International Conference on Multimedia (MM ’21). https://doi.org/10.1145/3474085.3475624

Xue-Yao Gao | Computer Vision and Image Recognition | Best Researcher Award

Published on by New Scientists

Prof. Dr. Xue-Yao Gao | Computer Vision and Image Recognition | Best Researcher Award

Professor and Ph.D. Supervisor (Ph.D.), Harbin University of Science and Technology, China

Prof. Dr. Xue-Yao Gao is a Professor and Ph.D. Supervisor at the School of Computer Science and Technology, Harbin University of Science and Technology, where he also serves as Vice Dean and Deputy Director of the Heilongjiang Key Laboratory of Intelligent Information Processing and Applications. He holds a Ph.D. in Computer Application Technology (2009), an M.Sc. in Computer Software and Theory (2006), and a B.Sc. in Computer and Applications (2002), all from Harbin University of Science and Technology. His primary research focuses on computer graphics, CAD, natural language processing (NLP), artificial intelligence (AI), pattern recognition, and deep learning, with particular expertise in 3D model retrieval, multi-view feature fusion, and cross-view optimization strategies. Over his career, Prof. Dr. Xue-Yao Gao has held key academic positions including Professor (2018–present), Associate Professor (2012–2018), and Lecturer (2010–2012) in the School of Computer Science and Technology at Harbin University of Science and Technology. His contributions include over 60 publications, 16 granted invention patents, and leadership of seven funded projects supported by the National Natural Science Foundation of China, Heilongjiang Provincial Natural Science Foundation, Ministry of Education’s Chunhui Program, and corporate collaborations, totaling research funding exceeding 2.6 million yuan. Prof. Dr. Xue-Yao Gao has been recognized with the university’s “Science and Engineering Talent” award and has contributed as editor and co-author to multiple textbooks and monographs. He holds leadership and committee positions in the China Computer Federation and Heilongjiang Computer Society, including Executive Member, Director, Vice Chairman of the Harbin Branch of CCF YOCSEF, and memberships in specialized committees, actively mentoring doctoral and master’s students and fostering youth scientific engagement. His work advances intelligent information processing, enhances 3D modeling and pattern recognition technologies, and promotes innovative AI applications, impacting academia, industry, and society. Author metrics: 53 documents, 124 citations, h-index 6. Prof. Dr. Xue-Yao Gao’s sustained research excellence, innovation in AI and computer graphics, and global collaborative potential make him highly deserving of recognition for advancing science, technology, and education internationally.

Profile: Scopus | ORCID | ResearchGate | IEEE Xplore | Harbin University of Science and Technology

Featured Publications

1. Gao, X., Zhang, Y., Zhang, C., & Xue, Y. (2025). 3D model classification based on DRSN and multi-view feature fusion. Expert Systems with Applications, 273, 126872.

2. Gao, X., Yan, S., & Zhang, C. (2024). 3D model classification based on RegNet design space and voting algorithm. Multimedia Tools and Applications, 83, 42391–42412.

3. Gao, X.-Y., Li, K.-P., Zhang, C.-X., & Yu, B. (2021). 3D model classification based on Bayesian classifier with AdaBoost. Discrete Dynamics in Nature and Society, 2021, Article 2154762.

4. Zhang, C.-X., Pang, S.-Y., Gao, X.-Y., Lu, J.-Q., Yu, B., & Jia, Y. (2022). Attention neural network for biomedical word sense disambiguation. Discrete Dynamics in Nature and Society, 2022, Article 6182058.

5. Zhang, C.-X., Shao, Y.-L., & Gao, X.-Y. (2023). Word sense disambiguation based on RegNet with efficient channel attention and dilated convolution. IEEE Access.