Building Quantum System Software for Unreliable Quantum Computers
Published: | 1:27 pm | Posted in: Colloquium
Speaker: Devesh Tiwari Date: Nov 17, 2023, 2:15 – 3:10 PM (Postponed) Abstract: The field of quantum computing has enjoyed extraordinary advances in the last two decades, including the physical implementation and experimental demonstration of medium-scale quantum computers. While these advances continue to be celebrated widely, computational scientists continue to struggle to make meaningful use […]
Large-Scale Graph Computing: From “Think Like a Vertex” to “Think Like a Task”
Published: | 3:40 pm | Posted in: Colloquium
Speaker: Da Yan Date: Nov 3, 2023, 2:15 – 3:10 PM Abstract: Big graphs are ubiquitously used for data modeling in modern applications, such as online social networks, knowledge graphs and biological networks. Unlike relational databases where queries can be formulated in a uniform manner with relational algebra, operations on graphs are highly diversified. For […]
Real Time Signal Processing Circuits Directly in Electromagnetic Waveform Domain
Published: | 2:42 pm | Posted in: Colloquium
Speaker: Bayaner Arigong Date: Oct 20, 2023 Abstract: Inspired by the visionary landscapes of science fiction, ubiquitous computing has emerged as a futuristic yet transformative paradigm that aims to seamlessly integrate computing technology into the fabric of our everyday lives. However, despite the promise of this vision, it remains uncertain how we can bring the […]
Towards Sustainable, Scalable, and Intelligent Ubiquitous Computing
Published: | 2:27 pm | Posted in: Colloquium
Speaker: Te-Yen Wu Date: Oct 6, 2023 Abstract: Inspired by the visionary landscapes of science fiction, ubiquitous computing has emerged as a futuristic yet transformative paradigm that aims to seamlessly integrate computing technology into the fabric of our everyday lives. However, despite the promise of this vision, it remains uncertain how we can bring the […]
Exploring the Causal Ladder: Unraveling Research in Each Layer
Published: | 7:33 pm | Posted in: Colloquium
Speaker: Ang Li Date: Sep 22, 2023 Abstract: When people engage in discussions about causal inference or causality, their initial focus often revolves around identifying the cause of a particular phenomenon. However, the realm of causal inference extends far beyond this initial perception. To gain a deeper understanding of what causal inference truly encompasses, Professor […]
Helping Scientists Explore Data Through Rich Metadata and Advanced Data Management Tools
Published: | 4:01 pm | Posted in: Colloquium
Speaker: Dr. Jay Lofstead Date: Friday, September 29, 2023, 2:15 – 3:15pm Location: 307 James Love Building Abstract: Scientific observations and simulations generate enormous data volumes that must be explored to gain new insights into physics phenomena. Two mature tool generations have been proposed with each offering different capabilities to aid scientists in their analysis […]
A Survey of Cloud Database Systems
Published: | 3:49 pm | Posted in: Colloquium
Speaker: C. Mohan Date: Friday, October 13, 2023, 2:15 – 3:15pm Location: 307 James Love Building Abstract: In this talk, I will first introduce traditional (non-cloud) parallel and distributed database systems. Concepts like SQL and NoSQL systems, data replication, distributed and parallel query processing, and data recovery after different types of failures will be covered. […]
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Published: | 1:33 pm | Posted in: Colloquium
Speaker: Gary Tyson Date: Sep 8, 2023 Abstract: Aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn’t mttaer in waht ore dr the ltteers in a wrod are, the olny iprmoetnt tihng is taht the frist and lsa t ltteer be at the rghit pclae. The rset can be a toatl mses and you can […]
Representation Space of Transformers
Published: | 1:30 pm | Posted in: Colloquium
Speaker: Xiuwen Liu Date: Sep 1, 2023 Abstract: Pretrained large foundation models play a central role in the recent surge of artificial intelligence, resulting in finetuned models with remarkable abilities when measured on benchmark datasets, standard exams, and applications. Due to their inherent complexity, these models are poorly understood. While small adversarial inputs to such […]
Safe Physics-AI: Physics-Regulated Deep Reinforcement Learning Towards Provable Safety Guarantee
Published: | 8:20 pm | Posted in: Colloquium
Speaker: Yanbing Mao Date: Sep 15, 2023 Abstract: The recent incidents due to the deployment of machine learning (ML) models overshadow the revolutionizing potential of ML, especially for safety-critical autonomous systems. Developing safe ML is thus more vital today. In the ML community, deep reinforcement learning (DRL) has demonstrated breakthroughs in sequential decision-making in broad […]