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Haithem Turki
Haithem Turki hturki Tue, 07/21/2026 - 13:55 Research Area(s) Computer Graphics
NVIDIA Research
@nvidia-research
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17
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Posts by NVIDIA Research
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Jaydeep Kulkarni
Jaydeep Kulkarni jaydeepk Tue, 07/21/2026 - 13:26 Research Area(s) Circuits and VLSI Design
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Ziyi Zhang
Ziyi Zhang ziyzhang Tue, 07/21/2026 - 13:20 Research Area(s) Real-Time Rendering
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Pedestrian Collision Detection and Avoidance in Cerebral Visual Impairment During Unrestricted Walking in an Immersive Virtual Reality Environment
Walking safely through highly crowded environments is a significant challenge for individuals with cerebral visual impairment (CVI). Yet current ophthalmic examinations do not capture functional visual difficulties related to safe mobility. We developed an immersive virtual reality (VR)-based tas...
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Fast and accurate AI-based pre-decoders for color codes
Color codes are promising alternatives to surface codes for universal fault-tolerant quantum computing due to their simpler lattice-surgery protocols and the transversal implementation of logical Clifford gates. However, their practical deployment has been limited by slower decoding algorithms an...
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The 2M Multiplication Algorithm for Complex Matrices
Complex matrix multiplication is typically computed using 4 real matrix multiplications (GEMMs) of the same size. The well-known 3M multiplication algorithm reduces this cost to 3 real GEMMs, together with quadratic time pre- and post-processing steps. In this paper, we reduce 3M to 2M for matric...
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Mixed-Precision SVD on GPUs via Ogita–Aishima Iterative Refinement
The Ogita–Aishima iterative refinement algorithm for SVD is based on matrix–matrix multiplication, making it an attractive approach for GPUs. We extend the algorithm to complex arithmetic, and introduce robust cluster handling based on Wedin’s perturbation theory and a per-pair version of Ogita–A...
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GPUArmor: A Hardware-Software Co-design for Efficient and Scalable Memory Safety on GPUs
Memory safety errors continue to pose a significant threat to current computing systems, and graphics processing units (GPUs) are no exception. A prominent class of memory safety algorithms is allocation-based solutions. The key idea is to maintain each allocation’s metadata (base address and siz...
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OASIS: Object-Aware Page Management for Multi-GPU Systems
The ever-growing need for high-performance computing has driven the popularity of employing multi-GPU systems. Modern multi-GPU systems employ unified virtual memory (UVM) to manage page placement and migration. However, the page management in UVM is application object agnostic. In this paper, we...
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SuperCollider: Scalable and Effective Data Race Detection for CUDA
Data races, which occur when two or more threads incorrectly access the same memory location without appropriate synchronization, cause CUDA programmers considerable pain. Even experts struggle to reason about extreme parallelism, multiple memory spaces and scopes, and diverse synchronization mec...
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Learning to Track Instances without Video Annotations
Tracking segmentation masks of multiple instances has been intensively studied, but still faces two fundamental challenges: 1) the requirement of large-scale, frame-wise annotation, and 2) the complexity of two-stage approaches. To resolve these challenges, we introduce a novel semi-supervised fr...
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Weakly-Supervised Physically Unconstrained Gaze Estimation
A major challenge for physically unconstrained gaze estimation is acquiring training data with 3D gaze annotations for in-the-wild and outdoor scenarios. In contrast, videos of human interactions in unconstrained environments are abundantly available and can be much more easily annotated with fra...
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Contrastive Syn-to-Real Generalization
Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to domain gaps. In this work, we make a key observation that the diversity of the learned feature embeddings plays an im...