Ruyi Lian
Assistant Professor of Computer Science
Biography
Dr. Ruyi Lian is an assistant professor in the McComish Department of Electrical Engineering and Computer Science at South à£à£Ö±²¥Ðã State University. She earned her Ph.D. in computer science from Stony Brook University in 2025, advised by Dr. Haibin Ling, and received her B.S. degree in applied mathematics from the University of Science and Technology of China in 2019.
Her research spans computer vision, computer graphics, robotics, computational biology and artificial intelligence for science, with particular focus on image-based object pose estimation, 3D reconstruction from imaging modalities and interdisciplinary applications of 3D vision algorithms.
Her research spans computer vision, computer graphics, robotics, computational biology and artificial intelligence for science, with particular focus on image-based object pose estimation, 3D reconstruction from imaging modalities and interdisciplinary applications of 3D vision algorithms.
Education
- Ph.D. in computer science | Stony Brook University, Stony Brook, New York | 2025
- B.S. in applied mathematics | University of Science and Technology of China, Hefei, China | 2019
Academic and Professional Experience
Academic Interests
- 3D computer vision
- Computer graphics
- Robotics
- Computational biology
- AI for science
Academic Responsibilities
- CSC 300 – Data Structures
Research and Scholarly Work
Areas of Research
- Image-based object pose estimation (instance-level and novel object estimation)
- 3D reconstruction and analysis from cryo-EM, OCT and other imaging modalities
- Interdisciplinary applications of 3D vision algorithms in assistive systems
Publications
- Lian, R., Lin, Y., Latecki, L.J. and Ling, H. (2025). VAPO: Visibility-Aware Keypoint Localization for Efficient 6DoF Object Pose Estimation. IROS 2025 (Oral).
- Gong, Y., Yao, J., Lian, R., Lin, X., Chen, C., Divakaran, A. and Yao, Y. (2025). Recovering manifold representations via unsupervised meta-learning. Frontiers in Computer Science, 6: 1255517.
- Pandi, S.V., Li, Z., Lian, R., Lee, J., Cheng, W., Wang, L., Lin, Y., Liu, Q. and Ling, H. (2025). A Novel Contrastive Loss and Clustering Approach for Particle Detection in Cryo-EM. ISBI 2025.
- Lian, R. and Ling, H. (2023). CheckerPose: Progressive Dense Keypoint Localization for Object Pose Estimation with Graph Neural Network. ICCV 2023.
- Lian, R., Huang, B., Wang, L., Liu, Q., Lin, Y. and Ling, H. (2022). End-to-end orientation estimation from 2D cryo-EM images. Acta Crystallographica Section D.
- Huang, B., Lian, R., Samaras, D. and Ling, H. (2021). Modeling Deep Learning Based Privacy Attacks on Physical Mail. AAAI 2021.
Associated Areas
