When: Friday, 3/7 11 am – 12 pm; Where: Tyler Hall 055. Abstract: Generative AI is transforming how machines interact with and augment human capabilities. However, achieving artificial general intelligence (AGI) requires addressing significant challenges in retrained language models (PLM) and multimodal large language models (MLLMs), including the brittleness of language model fine-tuning, imbalanced vision-language […]
Continue reading "Hang Hua, Advancing Generative AI for Multimodal Intelligence"Category: Seminars
Khaled Saifuddin, Hypergraph Learning: From Algorithms to Applications
When: Thursday, 3/6 11 am – 12 pm; Where: Tyler Hall 055 Abstract: This talk explores the advancement of Hypergraph Neural Networks (HyperGNNs) as a powerful extension of Graph Neural Networks (GNNs) to model higher-order relationships in complex systems, particularly in biomedical applications. While traditional GNNs struggle to capture higher-order intricate dependencies, HyperGNNs leverage hypergraphs […]
Continue reading "Khaled Saifuddin, Hypergraph Learning: From Algorithms to Applications"Alina Barnett, Inherently Interpretable Neural Networks for Scientific Discovery and High-Stakes Decision Support
When: Tuesday, 3/4 11 am – 12 pm. Where: Tyler Hall 055. Abstract Artificial intelligence is increasingly performing high-stakes tasks traditionally reserved for skilled professionals, with AI systems often surpassing human expert performance on specific tasks. Despite these advances, the “black box” (i.e., uninterpretable) nature of many machine learning algorithms poses significant challenges. These opaque […]
Continue reading "Alina Barnett, Inherently Interpretable Neural Networks for Scientific Discovery and High-Stakes Decision Support"Mahmoud Nazzal, Secure, Robust, and Interpretable AI Integrating Graph and Language Models
When: Thursday, 2/27 11:00 am Where: Tyler Hall 055 Abstract: Artificial intelligence (AI) has achieved remarkable performance across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures—Graph Neural […]
Continue reading "Mahmoud Nazzal, Secure, Robust, and Interpretable AI Integrating Graph and Language Models"Marco Alvarez, Transforming Research and Higher Education with Generative AI and Foundation Models
When: Friday April 5. – noon-1 p.m. Where: Bliss 190 This talk delves into the transformative potential of generative AI and foundation models in both scientific research and higher education. Foundation models represent a seismic shift in AI capabilities, empowering researchers to analyze data, generate hypotheses, and uncover knowledge with unprecedented efficiency. Trained on vast […]
Continue reading "Marco Alvarez, Transforming Research and Higher Education with Generative AI and Foundation Models"Yuwen Gu, fastkqr: A Fast Algorithm for Kernel Quantile Regression
When: Friday, March 22, from 2:00 PM to 3:00 PM Where: ENGR 045 Abstract: Quantile regression is a powerful tool for robust and heterogeneous learning that has seen applications in a diverse range of applied areas. Its broader application, however, is often hindered by the substantial computational demands arising from the nonsmooth quantile loss function. […]
Continue reading "Yuwen Gu, fastkqr: A Fast Algorithm for Kernel Quantile Regression"Caiwen Ding, Co-Designing Algorithms and Hardware for Efficient Machine Learning (ML): Advancing the Democratization of ML
When: Friday, March 8th, from 2:00 PM to 3:00 PM Where: ENGR 045 Abstract: The rapid deployment of ML has witnessed various challenges such as prolonged computation and high memory footprint on systems. In this talk, we will present several ML acceleration frameworks through algorithm-hardware co-design on various computing platforms. The first part presents a […]
Continue reading "Caiwen Ding, Co-Designing Algorithms and Hardware for Efficient Machine Learning (ML): Advancing the Democratization of ML"Oana Ignat, Towards Language-Vision Models for Positive Societal Impact
When: Monday 2/19 from 1:00 to 2:00 PM Where: Tyler 055 Abstract: Solving complex real-world problems often requires AI models that can process information from multiple modalities, such as language and vision, which can align with the needs of people from diverse backgrounds. An effective AI model will not only learn how to interact with […]
Continue reading "Oana Ignat, Towards Language-Vision Models for Positive Societal Impact"Kaleel Mahmood, On the Robustness of Vision Transformers to Adversarial Examples
When: Friday 2/16 from 10:00 to 11:00 AM Where: Ranger 202 Abstract: Machine learning has become ubiquitous, being deployed in a range for domains like self driving cars, medical imaging and face recognition. With this increased use of machine learning an important question arises, how secure are these systems? In this presentation we dive into […]
Continue reading "Kaleel Mahmood, On the Robustness of Vision Transformers to Adversarial Examples"Taslima Akter, Designing Privacy Enhancing Technology for Blind and Low-Vision (BLV) People
WHen: Tuesday 2/13 from 1:00 to 2:00 PM. Where: Quinn 214 Abstract: Advancements in computer vision and machine learning have empowered Blind and Low-Vision (BLV) individuals through camera-based assistive applications. These systems, capable of recognizing objects, identifying colors, and reading text, provide independence to BLV users. However, the reliance on camera-based assistive systems introduces privacy […]
Continue reading "Taslima Akter, Designing Privacy Enhancing Technology for Blind and Low-Vision (BLV) People"