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  • SubXeurons
    • iPSC-Cardio Cells
    • HALO: A Unified Visio
  • Publications
    • A multi-agent system for automating scientific discovery
    • Accelerating scientific discovery with Co-Scientist
    • vision foundation model for single-cell biology via spatial gene cartography
    • Adoption and Use of LLMs at an Academic Medical Center
    • Toward AI-Driven Digital Organism
    • You Can Run, You Can Hide: The Epidemiology and Statistical Mechanics of Zombies
    • embryonic stem cell-derived cardiac organoids via synthetic guidance
    • In vitro generation of human pluripotent stem cell derived lung organoids
    • Generating Self-Assembling Human Heart Organoids Derived from Pluripotent Stem Cells
    • SMAD4: A Critical Regulator of Cardiac Neural Crest Cell Fate and Vascular Smooth Muscle Differentiation. bioRxiv
    • Insights into AI Agent Security from a Large-Scale Red-Teaming Competition
    • TxPert: using multiple knowledge graphs for prediction of transcriptomic perturbation effects
    • Self-organizing human heart assembloids with autologous and developmentally relevant cardiac neural crest-derived tissues
    • Path Planning of Cleaning Robot with Reinforcement Learning
    • Reinforcement Learning Approaches in Social Robotics
    • Robotic Packaging Optimization with Reinforcement Learning
    • A Concise Introduction to Reinforcement Learning in Robotics
    • Robot-R1: Reinforcement Learning for Enhanced Embodied Reasoning in Robotics
    • Robotic Surgery With Lean Reinforcement Learning
    • Residual Reinforcement Learning for Robot Control
    • Autonomous robotic nanofabrication with reinforcement learning
    • Heterogeneous Multi-Robot Reinforcement Learning
    • Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning
    • Reinforcement learning for freeform robot design
    • Geometric Reinforcement Learning For Robotic Manipulation
    • On-Robot Bayesian Reinforcement Learning for POMDPs
    • Efficient Content-Based Sparse Attention with Routing Transformers
    • A foundation model of transcription across human cell types
    • Transformer AI
    • HALO, a unified VLA model that enables embodied multimodal chain-of-thought (EM-CoT) reasoning through a sequential process of textual task reasoning, visual subgoal prediction for fine-grained guidan
    • HALO: A Unified Vision-Language-Action Model for Embodied Multimodal Chain-of-Thought Reasoning
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    SubXeurons

    • i
      iPSC-Cardio Cells

      Pluripotent stem cell-derived organoids can recapitulate significant features of organ development in vitro. We hypothesized that creating human heart organoids by mimicking aspects of in utero gestation (e.g., addition of metabolic and hormonal factors) would lead to higher physiological and anatomical relevance. We find that heart organoids produced using this self-organization-driven developmental induction strategy are remarkably similar transcriptionally and morphologically to age-matched human embryonic hearts. We also show that they recapitulate several aspects of cardiac development, including large atrial and ventricular chambers, proepicardial organ formation, and retinoic acid-mediated anterior-posterior patterning, mimicking the developmental processes found in the post-heart tube stage primitive heart

    • H
      HALO: A Unified Visio

      HALO: A Unified Vision-Language-Action Model for Embodied Multimodal Chain-of-Thought Reasoning

    Publications

    • A
      Autonomous robotic nanofabrication with reinforcement learning

      The ability to handle single molecules as effectively as macroscopic building-blocks would enable the construction of complex supramolecular structures inaccessible to self-assembly. The fundamental c

    • H
      Heterogeneous Multi-Robot Reinforcement Learning

      Cooperative multi-robot tasks can benefit from heterogeneity in the robots' physical and behavioral traits. In spite of this, traditional Multi-Agent Reinforcement Learning (MARL) frameworks lack the

    • R
      Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning

      Reinforcement Learning is a promising tool for learning complex policies even in fast-moving and object-interactive domains where human teleoperation or hard-coded policies might fail. To effectively

    • R
      Reinforcement learning for freeform robot design

      Inspired by the necessity of morphological adaptation in animals, a growing body of work has attempted to expand robot training to encompass physical aspects of a robot's design. However, reinforcemen

    • G
      Geometric Reinforcement Learning For Robotic Manipulation

      Reinforcement learning (RL) is a popular technique that allows an agent to learn by trial and error while interacting with a dynamic environment. The traditional Reinforcement Learning (RL) approach h

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