activity
20242026
most citedOpen-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

NVIDIA Cosmos-H-Dreams: Real-Time Generative Physics Simulation for Surgical Robotics

Javier Gamazo Tejero, Lukas Zbinden, Keyur Sheth +7

Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are time-consuming, costly, and d…

cs.RO2026★ 1 cited

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

Open-H-Embodiment Consortium, :, Nigel Nelson +213

Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…

cs.AI2026

R-C2: Cycle-Consistent Reinforcement Learning Improves Multimodal Reasoning

Zirui Zhang, Haoyu Dong, Kexin Pei +1

Robust perception and reasoning require consistency across sensory modalities. Yet current multimodal models often violate this principle, yielding contradictory predictions for vi…

cs.CV2025

G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline

Vishwesh Nath, Javier G. Tejero, Aravind S. Kumar +4

We propose G-SHARP, a commercially compatible, real-time surgical scene reconstruction framework designed for minimally invasive procedures that require fast and accurate 3D modeli…

cs.RO2025

Cosmos-Surg-dVRK: World Foundation Model-based Automated Online Evaluation of Surgical Robot Policy Learning

Lukas Zbinden, Nigel Nelson, Juo-Tung Chen +5

The rise of surgical robots and vision-language-action models has accelerated the development of autonomous surgical policies and efficient assessment strategies. However, evaluati…

cs.RO2025

SuFIA-BC: Generating High Quality Demonstration Data for Visuomotor Policy Learning in Surgical Subtasks

Masoud Moghani, Nigel Nelson, Mohamed Ghanem +6

Behavior cloning facilitates the learning of dexterous manipulation skills, yet the complexity of surgical environments, the difficulty and expense of obtaining patient data, and r…

cs.RO2024★ 1 cited

SuFIA: Language-Guided Augmented Dexterity for Robotic Surgical Assistants

Masoud Moghani, Lars Doorenbos, William Chung-Ho Panitch +4

In this work, we present SuFIA, the first framework for natural language-guided augmented dexterity for robotic surgical assistants. SuFIA incorporates the strong reasoning capabil…

cs.SE2024

Towards Deterministic End-to-end Latency for Medical AI Systems in NVIDIA Holoscan

Soham Sinha, Shekhar Dwivedi, Mahdi Azizian

The introduction of AI and ML technologies into medical devices has revolutionized healthcare diagnostics and treatments. Medical device manufacturers are keen to maximize the adva…