Abstract: Artificial intelligence holds enormous promise to automate our life. At the same time, AI systems can be incredibly brittle, unreliable, and biased. In this talk, I will present a few […]
Abstract: Immunotherapies have achieved remarkable success in treating hematological cancers, yet the solid tumor microenvironment remains a significant barrier to therapeutic breakthroughs. Machine learning (ML)-driven computational protein design offers a […]
The electric grid is undergoing a transformative paradigm shift, driven by sweeping changes in generation, demand, and energy storage. By 2035, solar PV alone is expected to supply 40% of […]
Humans and other animals do not always choose the most rewarding course of action, even when we have ample time and computational resources. Why do we make mistakes? The noiseLab uses a combination of theoretical, behavioral, and neurobiological techniques to address this question. In this talk, Dr. Becket Ebitz will discuss converging evidence that mistakes are the product of representational and temporal nonlinearities in neural activity that constrain our ability to make good decisions. The talk will argue that some of these nonlinearities have long-term adaptive benefits, even when they fail to produce the best decision in the moment.
Glasses are generally regarded as disordered and the idea of “controlling” molecular packing in glasses is reasonably met with skepticism. However, as glasses are non-equilibrium materials, a vast array of […]
Soft robots have the potential to adapt their morphologies and behavioral control policies to changing tasks and environments. Inspired by the dynamic plasticity of living organisms and the general adaptability […]
Abstract: The efficient sharing of AI infrastructures is becoming increasingly important in both public and private data centers. This demand is driven by two key factors: the proliferation of specialized […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Modern artificial intelligences (AIs) rely heavily on internet-scale data with unified representations. […]
Abstract: Neurological conditions are the leading cause of illness worldwide, though over 92% of clinically tested CNS drug candidates fail to become treatments. Contributing to this high failure rate is […]
