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    • iPSC-Cardio Cells
    • HALO: A Unified Visio
  • Publications
    • 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
    Adoption and Use of LLMs at an Academic Medical Center

    The authors introduce ChatEHR, an internally developed, vendor-agnostic system for integrating large language models (LLMs) directly into clinical workflows within an academic medical center's electronic health record. By enabling real-time access to longitudinal patient data through both automated tasks and an interactive chat interface, the platform successfully reduces manual documentation burden and facilitates decision-making. The authors also establish a robust framework for governance, continuous performance monitoring, and value assessment, demonstrating a replicable model for other health systems.

  • T
    Toward AI-Driven Digital Organism

    This paper proposes the development of an AI-Driven Digital Organism (AIDO), a comprehensive, multiscale foundation model system designed to simulate biological systems from the molecular level to entire organisms. By integrating multimodal datasets and hierarchical deep learning architectures, AIDO aims to provide a safe, scalable, and programmable environment for biomedical research and drug discovery. The framework establishes a unified blueprint for modeling complex biological networks, bridging gaps between genotype, phenotype, and environmental influences.

  • Y
    You Can Run, You Can Hide: The Epidemiology and Statistical Mechanics of Zombies

    quantum-classical supercomputing: quantum chemistry of protein-ligand complexes

  • e
    embryonic stem cell-derived cardiac organoids via synthetic guidance

    Researchers developed a novel stem cell-based protocol to generate 'cardiobots'—self-organizing aggregates capable of muscle-powered motility. By optimizing mesoderm and cardiogenic induction through precise growth factor signaling and synthetic organizers, the team successfully engineered bio-aggregates with enhanced contractile areas and increased motility compared to existing gastruloid models. This approach provides a new framework for creating autonomous, muscle-propelled biological machines and exploring the evolutionary origins of movement in early multicellular organisms.

  • I
    In vitro generation of human pluripotent stem cell derived lung organoids
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