Suryansh Kumar

Assistant Professor, Performance Visualization and Fine Arts
Affiliated Faculty, Computer Science & Engineering and Electrical & Computer Engineering

Educational Background

Ph.D., Engineering and Computer Science, Australian National University (ANU) - 2019
M.S., Computer Science and Engineering, International Institute of Information Technology, Hyderabad (IIIT-H) - 2013

- Computer Vision
- Robotics
- Generative AI
- Visual Intelligence
- Spatial Intelligence

Texas A&M Institute of Data Science (TAMIDS) Course Development Awardee - 2024
Nominated for J. G. Crawford Prize at the Australian National University (ANU) for Best Interdisciplinary Ph.D. Thesis - 2019
Best Algorithm Award in CVPR NRSFM Challenge 2017 by Disney Research
Australian National University-Higher Degree Research (HDR) Merit Scholarship Award Holder (2015-2019)

C. Liu, S. Kumar, S. Gu, R. Timofte, Y. Yao, L. Van Gool, "Stereo Risk: A Continuous Modeling Approach to Stereo Matching", International Conference on Machine Learning (ICML), 2024.
R. Zurbrügg, Y. Liu, F. Engelmann, S. Kumar, M. Hutter, V. Patil, F. Yu, "ICGNet: A Unified Approach for Instance-Centric Grasping", IEEE International Conference on Robotics and Automation (ICRA), 2024.
J. Chen, G. Li, S. Kumar, B. Ghanem, F. Yu, "How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers", Robotics: Science and Systems (RSS), 2023.
N. Jain, S. Kumar, L. Van Gool, "Enhanced Stable View-Synthesis", IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023.
C. Liu, S. Kumar, S. Gu, R. Timofte, L. Van Gool, "VA-DepthNet: A Variational Approach to Single Image Depth Prediction", International Conference on Learning Representations (ICLR), 2023.