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Optically-trapped, ultra-cold gases of spin ½-up and spin ½-down 6Li atoms enable “designer” interactions, offering a versatile environment for simulating exotic quantum…

Provably sample-efficient reinforcement learning from rich observational inputs remains a key open challenge in research. While impressive recent advances have allowed the use of linear modelling…

The intrinsic activity of the brain is organized into networks and motifs that vary over time. To understand how coordinated macroscale patterns of intrinsic activity flow across the brain’s…

Engineered photonic nanostructures offer the exciting potential to create customized nonlinear optical media with tailored high-order effects, which are essential to the active control of light and…

Deep Reinforcement Learning (DRL) holds the promise of designing complex robotic controllers automatically. In this talk, I will discuss two different approaches to apply deep reinforcement learning…

The advent (and commoditization) of low-cost 3D cameras is revolutionizing many application domains, including robotics, autonomous navigation, human computer interfaces, and recently even consumer…

Human-Machine Interation; Machine Learning; Human Factors Engineering; Robotics abstract: New advances in robotics and autonomy offer the promise to revitalize assembly manufacturing, assist in…