Research that Evolves with
Visual Intelligence
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About Us
Our lab is dedicated to pushing the boundaries of computer vision, 3D understanding, and spatial AI. We combine theoretical research with practical applications to solve real-world challenges.
Research Overview
We conduct research in the field of Computer Vision, Robotics, and Artificial Intelligence. Our primary interests include:
Computer Vision
Visual representation learning, visual automation, single-view and multi-view 3D acquisition, camera modeling, light modeling, and image enhancement.
Robotics
Advancing robotic perception, control, and planning, enabling robots to operate autonomously in complex and unstructured environments.
Artificial Intelligence
Efficient algorithms for supervised, unsupervised, and reinforcement learning, with a focus on exploring generative AI approaches for generalization, robustness, and scalability.
Courses Offered
Student Opportunities
Course Enrollment
Academic Credit
Join our courses to gain hands-on experience in visual computing & AI
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GAT/GAR
$15-$23/hr Compensation
Work on research projects alongside faculty and graduates
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PhD/Postdoc
$30K+ Stipend/year
Full-time research positions with competitive funding and benefits.
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Meet your instructor
Prof. Dr. Suryansh Kumar
Suryansh Kumar is an Assistant Professor of Visual Computing and Computational Media at Texas A&M University. He also holds appointments in the Electrical and Computer Engineering Department and Computer Science Department at TAMU. Dr. Kumar directs the Visual and Spatial AI Lab within the College of PVFA where his group conducts research in the field of 3D computer vision, AI, and robotic automation.
Before joining Texas A&M University, Dr. Kumar worked at ETH Zürich. Disney Research honored him with the Best Algorithm Award at CVPR 2017 for his work on non-rigid 3D acquisition for marker-less motion capture, and his Ph.D. thesis was nominated for the J. G. Crawford Prize at ANU for Best Interdisciplinary Ph.D. Thesis in 2019. His current research focuses on designing next-generation visual and spatial intelligence systems.
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LAAH 202
Visual Spatial AI
We solve real-world visual automation problems by leveraging artificial intelligence for visual representation and decision-making tasks.
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