ASSET Seminar: “Making Machine Learning Predictably Reliable” (Andrew Ilyas, Massachusetts Institute of Technology)
ABSTRACT: Despite ML models’ impressive performance, training and deploying them is currently a somewhat messy endeavor. But does it have to be? In this talk, I overview my work on […]
ASSET Seminar: “Paths to AI Accountability” (Sarah Cen, Massachusetts Institute of Technology)
ABSTRACT: In the past decade, we have begun grappling with difficult questions related to the rise of AI, including: What rights do individuals have in the age of AI? When […]
ASSET Seminar: “Mathematical Foundations for Physical Agents” (Max Simchowitz, Massachusetts Institute of Technology, CSAIL)
ABSTRACT: From robotics to autonomous vehicles, machine learning agents deployed in the physical world (“physical agents”) promise to revolutionize endeavors ranging from manufacturing to agriculture to domestic labor. In this […]
ASSET Seminar: “Towards A New Frontier of Trustworthy AI: Interpretable Machine Learning Algorithms that Produce All Good Models” (Chudi Zhong, Duke University)
ABSTRACT: Machine learning has been increasingly deployed for high-stakes decisions that deeply impact people’s lives. My research focuses on developing interpretable algorithms and pipelines to ensure the safe and efficient utilization […]
CIS Seminar: ” How Algorithms Can Support Deliberative Democracy”
Academics and political practitioners around the world are experimenting with a class of democratic innovations called deliberative mini-publics (DMs). In a DM, a panel of constituents convenes to deliberate about specific issues and make […]
CIS Seminar: “Obfuscation of Quantum Computation”
Protecting secrets within computer systems is a central mission of cryptography. Program obfuscation, which scrambles computer code without harming its functionality, is an immensely powerful and versatile tool for accomplishing […]
ESE Grace Hopper Lecture – “Disrupting NextG”
As 5G takes to the airwaves, we now turn our imagination to the next generation of wireless technology. The promise of this technology has created an international race to innovate, […]
ASSET Seminar: “Statistical Methods for Trustworthy Language Modeling” (Tatsu Hashimoto, Stanford University)
ABSTRACT: Language models work well, but they are far from trustworthy. Major open questions remain on high-stakes issues such as detecting benchmark contamination, identifying LM-generated text, and reliably generating factually […]
CIS Grace Hopper Distinguished Lecture: “AGI is Coming… Is HCI Ready?”
We are at a transformational junction in computing, in the midst of an explosion in capabilities of foundational AI models that may soon match or exceed typical human abilities for […]
CIS Seminar: “Diffusion Models in Computer Vision”
Denoising diffusion models represent a recent emerging topic in computer vision, demonstrating impressive results in generative modeling. A diffusion model is a deep generative model that is based on two […]