CCS/ITSRCI Seminar Series on AI in Practice – April 24, 2025

CCS/ITSRCI Seminar Series on AI in Practice – April 24, 2025

Announcements, CCS RCD Seminar Series, News
April 24, 202512:15 PM – 1:15 PM Speaker:Xin Liang, Computer Science Department, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Advancing Extreme-scale Data Science via Trust-driven Data Reduction Abstract:Extreme-scale scientific simulations and experiments generate more data than that can be stored, transmitted, and analyzed. The recently delivered exascale systems and high-resolution scientific instruments are exacerbating this problem, due to the imbalanced growth between storage systems and data. My research focuses on the development of efficient algorithms and scalable software for high-performance data management on massively parallel and heterogeneous systems. In this talk, I will present how we address the scientific data challenges arising from real-world scientific applications through trust- driven data reduction. Specifically, I will talk about 1) error-controlled and feature- preserving lossy data reduction; 2) data refactoring and error-controlled progressive…
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CCS/ITSRCI Seminar Series on AI in Practice – April 17, 2025

CCS/ITSRCI Seminar Series on AI in Practice – April 17, 2025

Announcements, CCS RCD Seminar Series
April 17, 202512:15 PM – 1:15 PM Speaker:Ankan Bhattacharyya, Computer Science Department, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:System for the 2D-3D detection of bourbon barrel features-of- interest Abstract:During the bourbon aging process, where bourbon is stored in new, charred oak barrels for months or years, distilleries realize a significant amount of product wastage. Some of this loss arises from expected environmental processes (i.e. evaporation of the bourbon through the porous wood of the barrel), while a considerable portion is due to the unexpected structural failure of the barrel itself. While these events have been a part of the bourbon industry since its inception, it is only recently that distilleries have begun to investigate the properties of the barrel which may contribute to and/or lead to product wastage. This…
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CCS/ITSRCI Seminar Series on AI in Practice – April 3, 2025

CCS/ITSRCI Seminar Series on AI in Practice – April 3, 2025

Announcements, CCS RCD Seminar Series
April 3, 202512:15 PM – 1:15 PM Speaker:Barry Farmer, Center for Computational Sciences, University of Kentucky Where:327 McVey Hall (Virtual Speaker)(Zoom link: https://uky.zoom.us/j/82467171189) Title:Enhancing AI/ML Research with HPC Resources: A Practical Approach Abstract:Navigating high-performance computing (HPC) environments can be challenging for researchers seeking to access and utilize a wide range of software tools. This session introduces key services developed to simplify access to software and resources at the University of Kentucky, including the Software Discovery Service (SDS) and the Singularity Container Composer. These tools enable users to quickly locate available software and customize containerized applications to meet their specific research needs. We’ll explore how to search for software, create custom containers, and deploy Jupyter Notebooks using Open OnDemand, providing practical applications for a variety of research areas. While there will be…
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CCS/ITSRCI Seminar Series on AI in Practice – March 27, 2025

CCS/ITSRCI Seminar Series on AI in Practice – March 27, 2025

Announcements, CCS RCD Seminar Series
March 27, 202512:15 PM – 1:15 PM Speaker:Jeff Talbert, College of Medicine, University of Kentucky Where:327 McVey Hall (Virtual Speaker)(Zoom link: https://uky.zoom.us/j/82467171189) Title:The Rapid Actionable Data for Opioid Response (RADOR-KY) Project Abstract:This presentation will focus on the development of RADOR-KY, the Rapid Actionable Data for Opioid Response in Kentucky. RADOR-KY is an integrated population-based near-real time statewide system that uses multiple data sources to monitor and respond to the ongoing opioid overdose crisis. RADOR-KY uses dashboards to visualize data sources and topics and of interest identified by stakeholders. RADOR-KY allows users to develop customizable dashboards that will allow them options to select specific measures.  Lastly, RADOR-KY will forecast opioid overdose incidents using predictive analytics and machine learning to forecast future trends.   Click here to see the complete list of speak
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CCS/ITSRCI Seminar Series on AI in Practice – March 13, 2025

CCS/ITSRCI Seminar Series on AI in Practice – March 13, 2025

Announcements, CCS RCD Seminar Series, News
*RESCHEDULED* March 13, 202512:15 PM – 1:15 PM Speaker:William Mattingly, Cultural Heritage Data Scientist, Yale University Where:327 McVey Hall (Virtual Speaker)(Zoom link: https://uky.zoom.us/j/82467171189) Title:Evolution of Machine Learning Approaches in Human Rights Data Analysis Abstract:Over the past five years, our approach to named entity recognition and semantic search has undergone significant changes. In this tutorial, we will compare the methods used during the initial phase of Bitter Aloe with the techniques currently in use. Click here to see the complete list of speak
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CCS/ITSRCI Seminar Series on AI in Practice – March 6, 2025

CCS/ITSRCI Seminar Series on AI in Practice – March 6, 2025

Announcements, CCS RCD Seminar Series, News
March 6, 202512:15 PM – 1:15 PM Speaker:Stephen Davis, Department of History, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:The Application of Machine Learning to Human Rights Data: Two Use Cases from the Bitter Aloe Project Abstract:South Africa’s Truth and Reconciliation Commission (TRC) documented gross human rights violations during apartheid through individual testimonies and incident descriptions. While this approach provided an unprecedented view of political violence, limited planning for future accessibility has constrained researchers to keyword searches and detailed reading of individual transcripts. Bitter Aloe seeks to improve access to the TRC archive by applying two natural language processing techniques: named entity recognition and document embedding. This talk will explore the methodologies used in Bitter Aloe and demonstrate their potential as a broader application of machine learning to human rights…
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CCS/ITSRCI Seminar Series on AI in Practice – February 20, 2025

CCS/ITSRCI Seminar Series on AI in Practice – February 20, 2025

Announcements, CCS RCD Seminar Series, News
February 20, 202512:15 PM - 1:15 PM Speaker:Mami Hayashida, ITS-RCI, University of Kentucky and Vikram Gazula, CCS, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Introduction to Retrieval-Augmented Generation Abstract: Despite their impressive performance and versatility, LLMs are fundamentally limited by the data they were initially trained on. For researchers who wish to incorporate LLMs into their work, this often becomes a challenge as the available models trained on general knowledge fail to make reference to the domain knowledge.  Similarly, LLMs do not keep up with the most up-to-date information as each LLM’s knowledge is “frozen”.  RAG (Retrieval Augmented Generation) is a simple technique to overcome this gap by feeding additional knowledge to the LLM as part of workflow. When deployed effectively, the same LLMs will incorporate the added knowledge…
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CCS/ITSRCI Seminar Series on AI in Practice – February 13, 2025

CCS/ITSRCI Seminar Series on AI in Practice – February 13, 2025

Announcements, CCS RCD Seminar Series
February 13, 202512:15 PM - 1:15 PM Speaker:Hasan Poonawala, Mechanical Engineering, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Adding smart sensors to your data collection pipeline using deep learning on embedded computers. Abstract: Newer kinds of data collection are now possible thanks to combined advances in machine learning and embedded computing. In particular, relevant data can be autonomously extracted from sensors at the source.  This talk will discuss some examples through projects in my lab, like collecting data on seated-vs-standing behavior by individuals in their homes, with lessons learned. Click here to see the complete list of speakers.
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Dr. Xin Liang wins the NSF CAREER Award for the project Data Polymorphism: Enabling Fast and Adaptable Scientific Data Retrieval with Progressive Representations

Dr. Xin Liang wins the NSF CAREER Award for the project Data Polymorphism: Enabling Fast and Adaptable Scientific Data Retrieval with Progressive Representations

Announcements, News
Congratulations to Dr. Xin Liang from the UK Computer Science Department, a recipient of the prestigious NSF CAREER Award. The funded project is concerned with the concept of data polymorphism and aims to enable fast and adaptable scientific data retrieval. Scientific simulations and instruments produce an unprecedented amount of data that overwhelms the network and storage systems. Due to the limited capacity in high-end parallel file systems, such data must be stored at remote sites or moved to secondary storage for archival purposes. This poses challenges to fetching the data for post hoc data analytics, as the data movement bandwidth across wide area networks or from secondary systems is very limited.  This project bridges this gap by developing scalable software to realize data polymorphism, a novel paradigm that allows for variable…
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CCS/ITSRCI Seminar Series on AI in Practice – January 30, 2025

CCS/ITSRCI Seminar Series on AI in Practice – January 30, 2025

Announcements, CCS RCD Seminar Series
January 30, 202511:45 AM - 12:45 PM (Temporary Timeslot) Speaker:Mahmut Gokmen, Institute for Biomedical Informatics, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Task-Specific Adaptation of Vision Foundational Models for Coronary Artery Disease Diagnosis Abstract: This presentation will demonstrate the application of vision foundational models in detecting, grading, and understanding the real-world implications of Coronary Artery Disease. During the session, the general architecture of a foundational model will be explained, along with how it is trained using a self-supervised technique (DINO) and how it can be adapted to task-specific structures when necessary. Additionally, the current pace of advancements in foundational models and their future potential will also be discussed. Click here to see the complete list of speakers.
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