ASSET Seminar: “Towards Sustainable Artificial Intelligence and Datacenters”
Abstract: As the impact of artificial intelligence (AI) continues to proliferate, computer architects must assess and mitigate its environmental impact. This talk will survey strategies for reducing the carbon footprint […]
ASSET Seminar: “Machine Learning and Brain Imaging: Contributions to Diagnostics, Prognostication, and Treatment Guidance”
Abstract: Neuroimaging has significantly expanded our understanding of brain changes in neuropsychiatric disorders as well as in aging and neurodegenerative diseases. However, it wasn’t until the advent of machine learning […]
ASSET Seminar: “Multi-Omic Approaches for Deciphering Cellular Heterogeneity and Plasticity in Cancer”
Abstract: Tumors are complex and heterogeneous systems, which challenge their classification and treatment. The Silverbush lab decodes tumor heterogeneity and plasticity to understand how cancer cells transform to become more […]
BE Seminar: “Designing Programmable Protein Therapeutics with Generative Language Models” (Pranam Chatterjee, Duke University)
CRISPR has revolutionized biotechnology by enabling the simple design of guide RNAs to target and edit almost any DNA sequence. By developing new generative protein design algorithms, my hybrid lab […]
ASSET Seminar: “Control with Coarse Measurements: Perception Contracts and Indistinguishable Sets”
Abstract: Performance of control systems depend on the nature of available measurements. Perception of edges, keypoints, landmarks and other natural semantic features make certain coarse measurements available to control systems operating in […]
ASSET Seminar: “Some Displaced Vignettes on Generalized Notions of Equivariance”
Abstract: The explicit incorporation of task-specific inductive biases through symmetry has emerged as a crucial design precept in the development of high-performance machine learning models. Symmetry-aware neural networks, such as […]
ASSET Seminar: “What’s In my Network? On Learned Proximals and Testing for Explanations”
Abstract: Modern machine learning methods are revolutionizing what we can do with data, from tiktok video recommendations to biomarkers discovery in cancer research. Yet, the complexity of these deep models […]
ASSET Seminar: “Advancing Diffusion Models for Text Generation”
Abstract: Transformer-based language models have undoubtedly become the dominant and favorite architecture for language generation of our time. However, although they provide impressive text quality, they tend to be hard […]
ASSET Seminar: “Wood Wide Models”
Abstract: Foundation models are monolithic models that are trained on a broad set of data, and which are then in principle fine-tuned to various specific tasks. But they are ill-suited […]
ASSET Seminar: “Towards Pluralistic Alignment: Foundations for Learning from Diverse Human Preferences”
Abstract: Large pre-trained models trained on internet-scale data are often not ready for safe deployment out-of-the-box. They are heavily fine-tuned and aligned using large quantities of human preference data, usually […]