Our electric grids are undergoing changes in both form and function, where renewable resources and new devices are creating systems that are more distributed, dynamic and uncertain. Modern AI and machine learning tools have the potential to transform the operation of these new energy systems. However, such algorithms typically do not provide guarantees on stability or safety, making...

The Surface Force Apparatus (SFA) is a highly versatile method for directly measuring the interaction forces between two surfaces with sub-nanometer resolution in distance and 10 picoNewtons in force. Both the normal and shear force between the surfaces can be measured as well as the refractive index of the films to ±0.005. This talk will describe the SFA technique in detail and highlight a...

We will survey our framework of how pre-trained generative models can be used as priors to solve inverse problems like denoising, filling missing data, and recovery from linear projections in an unsupervised way. We generalize compressed sensing theory beyond sparsity, extending Restricted Isometries to sets created by deep generative models.

Recent advances in unsupervised representation learning have led to a host of widely used AI tools, such as ChatGPT and Stable Diffusion. These tools have been the result of applying relatively simple training algorithms to massive models on massive GPU clusters, even larger amounts of unlabeled training data, and by tuning the algorithms on a host of labeled evaluation tasks. In this...

As networked systems become critical infrastructure, their design must reflect their new societal role. Today, we build systems with hundreds of heuristics but often do not understand their inherent and emergent behaviors. I will present a set of tools and techniques to prove performance properties of heuristics running in real-world conditions. Rigorous proofs can not only inspire...

You are warmly invited back to campus to attend the Berkeley EECS Annual Research Symposium (BEARS) 2023. BEARS is an opportunity for everyone in the wider UC Berkeley Electrical Engineering and Computer Sciences community to come together to hear about some of our latest research and celebrate the year’s Distinguished Alumni. The 2023 lectures will highlight the department's 50th anniversary....

Ten years into the revival of deep networks and artificial intelligence, we propose a new theoretical framework that sheds light on understanding deep networks from the perspective of learning low-dimensional structures from high-dimensional data.

Additive manufacturing has shown the promise of freedom of design, enabling parts customization and tailorable properties where superior structural performance can be achieved with a fraction of the weight density compared to bulk materials. However, it is difficult, currently, to combine different materials (structural, dielectric, conducting and ferroelectrics) to create a complex device with...

Please RSVP to join us in celebrating the life and legacy of David Hodges and to receive more details about the Feb. 18 program, including parking information.

Dr. Darío Gil is IBM Senior Vice President and Director of Research. Dr. Gil leads the technology roadmap and the technical community of IBM, directing innovation strategies in areas including hybrid cloud, AI, semiconductors, quantum computing, and exploratory science. Dr. Gil is responsible for IBM Research, one of the world’s largest and most influential corporate research labs, with over...