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Sunday, February 4, 2024
No events on this day.
Monday, February 5, 2024
Tuesday, February 6, 2024
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February 6, 2024 -MEAM Seminar: “Towards the Discovery of Trustworthy and Interpretable ML-enabled Constitutive Laws for Solids from Low- and Limited-data”
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February 6, 2024 -CIS Seminar: ” How Algorithms Can Support Deliberative Democracy”
MEAM Seminar: “Towards the Discovery of Trustworthy and Interpretable ML-enabled Constitutive Laws for Solids from Low- and Limited-data”
Machine learning techniques are gearing up to play a significant role in the field of computational solid mechanics and multiphysics, enabling the integration of experimental data and physical constraints towards data-driven constitutive laws, acceleration of computational techniques for multi-scale modeling, and new paradigms for the solution of forward and inverse problems, to name a few. […]
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 policy recommendations to traditional political decision-makers (e.g., legislators). Nearly all DMs rely on sortition – random selection – to choose the panelists. Sortition is often thought of as […]
Wednesday, February 7, 2024
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February 7, 2024 -Spring 2024 GRASP SFI: Andrew Owens, University of Michigan, “Multimodal Learning from the Bottom Up”
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February 7, 2024 -ASSET Seminar: “Paths to AI Accountability” (Sarah Cen, Massachusetts Institute of Technology)
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February 7, 2024 -CBE Seminar: “Molecular Microscopy with Single Cell Transcriptomic Data Resolves RNA Liquid Biopsies” (Sevahn Vorperian, Stanford)
Spring 2024 GRASP SFI: Andrew Owens, University of Michigan, “Multimodal Learning from the Bottom Up”
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Today's machine perception systems rely extensively on supervision provided by humans, such as natural language. I will talk about our efforts to make systems that, instead, learn from two ubiquitous sources of unlabeled sensory data: visual motion […]
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 should we regulate AI and when should we abstain? What degree of transparency is needed to monitor AI systems? These questions are all concerned with […]
CBE Seminar: “Molecular Microscopy with Single Cell Transcriptomic Data Resolves RNA Liquid Biopsies” (Sevahn Vorperian, Stanford)
Abstract Invasive biopsy is the gold standard for diagnosing several diseases; however, these procedures offer a limited, localized view of the disease pathology to the physician and are not risk-free to the patient. Cell-free RNA (cfRNA) in blood plasma reflects dynamic gene expression changes and can facilitate early disease diagnosis, yet current cfRNA assays fall […]
Thursday, February 8, 2024
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February 8, 2024 -Evolution of Data Storytelling: Women in Data Science x Penn Museum Tour + Workshop
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February 8, 2024 -BE Seminar: “Mapping and engineering gene expression with chemical and spatial lenses” (Hailing Shi, Broad Institute & MIT)
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February 8, 2024 -CIS Seminar: “Rethinking Data Use in Large Language Models”
Evolution of Data Storytelling: Women in Data Science x Penn Museum Tour + Workshop
Join us for an exciting kick-off event at the Penn Museum as part of the Women in Data Science (WiDS) @ Penn conference, where the past meets the future in a guided tour and storytelling workshop.
BE Seminar: “Mapping and engineering gene expression with chemical and spatial lenses” (Hailing Shi, Broad Institute & MIT)
Precise RNA expression, tailored to specific brain regions, cell types, and subcellular compartments, is pivotal for orchestrating complex brain functions. In the first part of my talk, I will introduce a confocal imaging-based spatial transcriptomics platform, STARmap, that seamlessly combines in situ hybridization, hydrogel tissue chemistry, and in situ sequencing technologies. Leveraging scalable experimental and computational pipelines, […]
CIS Seminar: “Rethinking Data Use in Large Language Models”
Large language models (LMs) such as ChatGPT have revolutionized natural language processing and artificial intelligence more broadly. In this talk, I will discuss my research on understanding and advancing these models, centered around how they use the very large text corpora they are trained on. First, I will describe our efforts to understand how these […]
Friday, February 9, 2024
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February 9, 2024 -Women in Data Science @ Penn
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February 9, 2024 -Spring 2024 GRASP on Robotics: Qixing Huang, University of Texas at Austin, “Geometric Regularizations for 3D Shape Generation”
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February 9, 2024 -PICS Colloquium: “Wall-models of turbulent flows via scientific multi-agent reinforcement learning”
Women in Data Science @ Penn
The Wharton School and Penn Engineering are proud to host the fifth annual Women in Data Science (WiDS) @ Penn Conference on February 8-9, 2024, on the University of Pennsylvania’s campus. A celebrated interdisciplinary event, WiDS @ Penn welcomes academic, industry, and student speakers from across the data science landscape to celebrate its diversity, both […]
Spring 2024 GRASP on Robotics: Qixing Huang, University of Texas at Austin, “Geometric Regularizations for 3D Shape Generation”
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT Generative models, which map a latent parameter space to instances in an ambient space, enjoy various applications in 3D Vision and related domains. A standard scheme of these models is probabilistic, which aligns the induced ambient distribution […]
PICS Colloquium: “Wall-models of turbulent flows via scientific multi-agent reinforcement learning”
The predictive capabilities of turbulent flow simulations, critical for aerodynamic design and weather prediction, hinge on the choice of turbulence models. The abundance of data from experiments and simulations and the advent of machine learning have provided a boost to turbulence modeling efforts. However, simulations of turbulent flows remain hindered by the inability of heuristics […]
Saturday, February 10, 2024
No events on this day.