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  • Publications - liquetaylor. wixstudio. com
    Bai, S , Han, R Parkih, N , Ju, W , Taylor, A "Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypes", In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI) 2026
  • Home | Angelique
    Health Tech Hub Faculty, Cornell Tech I direct the Artificial Intelligence Robotics Lab (AIRLab), which focuses on research in the field of human-robot interaction (HRI)
  • Artifical Intelligence and Robotics Lab - Cornell University
    Our mission is to design intelligent systems (e g , robots) that work alongside human teams in real-world, safety-critical environments (i e , healthcare) Our research lies at the intersection of robotics, computer vision, and artificial intelligence Through community engagement and human-centered design, we conduct groundbreaking research that impacts both theoretical development and real
  • AirLab - GitHub
    The Artificial Intelligence and Robotics Lab (AIRLab) at Cornell Tech Our mission is to design intelligent systems (e g , robots) that work alongside human teams in real-world, safety-critical environments (i e , healthcare) Our research lies at the intersection of robotics, computer vision, and artificial intelligence
  • Cornell Tech - Angelique Taylor
    Angelique Taylor is the Andrew H and Ann R Tisch Assistant Professor at Cornell Tech and the Cornell Ann S Bowers College of Computing and Information Science Taylor is the director of the Artificial Intelligence and Robotics Lab (AIRLab), focusing on research at the intersection of robotics, computer vision, and artificial intelligence The AIRLab designs […]
  • Improving Multimodal Interactive Agents with Reinforcement Learning . . .
    An important goal in artificial intelligence is to create agents that can both interact naturally with humans and learn from their feedback Here we demonstrate how to use reinforcement learning from human feedback (RLHF) to improve upon simulated, embodied agents trained to a base level of competency with imitation learning First, we collected data of humans interacting with agents in a
  • Multimodal Agent AI: A Survey of Recent Advances and Future . . . - Springer
    We first introduce the basics of agent AI and its multimodal interaction capabilities We then delve into the core technologies that enable agents to perform task planning, decision-making, and multi-sensory fusion Furthermore, we focus on exploring various applications of MAA in robotics, healthcare, gaming, and beyond
  • Towards Rationality in Language and Multimodal Agents: A Survey
    This paper surveys state-of- the-art advancements in language and multi- modal agents, assesses their role in enhanc- ing rationality, and outlines open challenges and future research directions
  • Multi-Agent Reinforcement Learning: A Review of Challenges and . . . - MDPI
    Multi-agent reinforcement learning is a new, promising branch of machine learning theory The technological trend is moving towards distributed systems composed of multitudes of computational units, which is also due to the development of the IoT and the edge computing sector
  • Christy Sum Yu Cheung - IEEE Xplore Author Profile
    Affiliations: [Cornell University, Ithaca, NY, USA] Action Recognition, Assistive Technology, Body Regions, Care Recipients, Caregiving Tasks, Data Collection
  • Yunhai Feng (0009-0006-3041-9816) - ORCID
    SAM-RL: Sensing-aware model-based reinforcement learning via differentiable physics-based simulation and rendering The International Journal of Robotics Research





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