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Celebration of women and nonbinary researchers in computer science, featuring a welcome address and keynote presentation on innovative research and the vision behind Women's Research Day.
Explore cross-layer optimization for energy-efficient AIoT systems, integrating machine learning, wireless communication, signal processing, and VLSI architecture for ultra-low power IoT applications.
Explore integrated descriptions for automated scientific processes, extracting models and protocols for analysis and execution using the Kaemika app across multiple platforms.
Explore innovative approaches to robotic policy learning in spatial action spaces for complex manipulation tasks, addressing challenges and evaluating solutions in simulated and physical environments.
Explore causal inference in single-cell genomics, focusing on differential expression analysis and integrating bulk data for high-resolution insights into complex disease mechanisms.
Explores advancements in safe robot learning, focusing on imitation learning theory, scalable reward inference, and efficient policy evaluation to enable real-world deployment with safety guarantees.
Exploring human-machine collaboration to improve performance in complex tasks. Research on computational models enabling machines to understand human teammates and enhance capabilities in various fields.
Innovative computer vision algorithms for disease phenotyping across scales, from video-based heart function assessment to spatial transcriptomics and immune cell dynamics, with focus on robust and human-compatible AI.
Explore how formal methods and synthesis techniques can design, explain, and guarantee robot behavior, with examples of modular robots, swarms, and human-robot interaction.
Explore machine learning approaches for protein engineering, focusing on data-driven design to create proteins with desired properties and the challenges of extrapolation in predictive modeling.
Explore robot learning from limited demonstrations, leveraging data structure and geometry. Discover optimal control strategies and intuitive interfaces for efficient skill acquisition in human-robot interaction.
Explore DNA nanotechnology's potential for creating smart molecular systems, including a 355-tile set capable of implementing various 6-bit algorithms with high reliability.
Explores deep learning techniques for processing irregular 3D geometric data, addressing challenges in surface reconstruction and geometric modeling. Highlights potential applications and future research directions.
Explore advanced robotics concepts, focusing on abstract reasoning and joint semantic-physical representations for improved planning and decision-making in complex environments.
Explore 3D scene representation models that learn object permanence, emergence, and dynamics without annotations, supporting language grounding and generalizing across scenes and cameras.
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