CIS

Promises are cheap. Software vendors routinely describe their offerings as “secure”, but few are based on designs that can guarantee even the most basic security properties. To address this problem, services like Cloudflare, Android, and Firefox are increasingly relying on languages like Rust and WebAssembly to provide safety by design. But these promises too can […]

Modern datacenters must handle an ever-growing array of real-time and data-intensive workloads, such as interactive web services and AI models, that demand both low latency and high throughput. However, traditional operating systems introduce significant I/O overhead, degrading performance and reducing efficiency. A common solution is to let applications directly communicate with hardware, bypassing the operating […]

Generative modeling offers a powerful paradigm for designing novel functional DNA, RNA and protein sequences. In this talk, I introduce probabilistic experimental design methods to efficiently manufacture samples from generative models of biomolecules in the real world. These algorithms merge computational techniques for approximate sampling with physical randomness. I also develop tools to rigorously evaluate […]

Artificial intelligence (AI) is transforming scientific discovery, particularly in materials science, by accelerating the prediction and design of materials with desired properties. Traditional physics-based modeling of atomic systems is computationally prohibitive for large-scale problems, and AI addresses this challenge by learning the underlying physics from data, thereby accelerating discoveries. In this talk I will present […]

Cyber-physical systems (CPS), powered by emerging artificial intelligence (AI) technologies, have become integral to various critical domains such as the Internet of Things (IoTs), medical devices, and autonomous vehicles. A unique aspect of these systems lies in their interactions with the physical world, by perceiving environments through heterogeneous modalities (perception), processing digital data with intelligence […]

Many domains of machine learning, from language modeling to computer vision, have recently undergone a shift towards generalist models, whose broad generalization abilities are fueled by large and diverse real-world training datasets and high-capacity model architectures. In robotics, however, it has been challenging to apply the same recipe: after all, we cannot easily scrape millions […]

Perceiving the 4D world (i.e., 3D space over time) from visual input is essential for human interaction with the physical environment. While computer vision has made remarkable progress in 3D scene understanding, much of it remains piecemeal—for example, focusing solely on static scenes or specific categories of dynamic objects. How can we model diverse dynamic […]

We have made exciting progress in AI by massive models on massive amounts of data center compute. However, the demands for AI are rapidly expanding. I identify how to maximize performance under any compute constraint, expanding the Pareto frontier of AI capabilities.   This talk builds up to an efficient language model architecture that expands […]