October 10, 202412:15 pm Speaker:Md Atik Ahamed, Division of Biomedical Informatics, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Advanced tools and packages for handling tabular data and time series data Abstract: In this comprehensive tutorial, we will assess several state-of-the-art models for analyzing both tabular and time series data. We will begin by discussing the advantages and limitations of models such as XGBoost, TransTab and MambaTab for tabular data, as well as deep learning approaches like PatchTST and TimeMachine models for time series prediction.Following this overview, we will provide a step-by-step walkthrough of how to use corresponding tools and packages effectively. We will focus on real-world datasets and explanations of the packages in a user-friendly manner. Click here to see the complete list of speakers.

October 3, 202412:15 pm Speaker:Qiang (Shawn) Cheng, Division of Biomedical Informatics, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Novel Deep Learning models and Techniques for Effective and EfficientHandling of Multiple Data Modalities Abstract: Diverse areas of scientific research and everyday life, including healthcare, biomedicine, and engineering, are inundated with various data modalities, each presenting unique challenges. This talk presents several cutting-edge learning approaches designed to handle different types of data with both accuracy and computational efficiency. They include A SOTA state-space model for tabular data classification, time series long-term forecasting with linear complexity, time series classification, multi-modal data clustering with sparse tensor learning, and if time permits inferring circadian phases from multi-omics data. This talk integrates deep learning models and classical learning methods, each optimized for a particular data…

September 26, 202412:15 pm Speaker:Aaron Mullen, Institute for Biomedical Informatics, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:CLASSify: A Self-Service Machine Learning Platform Abstract: CLASSify is a web-based tool developed at the Center for Applied AI to make machine learning easier and more accessible. It provides a platform to train and evaluate ML classification models on any tabular data without requiring any programming background. Users can simply upload their dataset to the site, choose the training parameters, and the job will be sent off to train all chosen models and provide results in the form of tables and visualizations. CLASSify also provides options for synthetic data generation to bolster imbalanced class labels or create entirely new datasets, as well as explainability scores that provide insight into which features of…

September 19, 202412:15 pm Speaker:Brent Harrison, Computer Science, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:Practical Value Alignment Using GPT-4o Abstract: As artificial intelligence (AI) and machine learning (ML) systems grow in power, their risk of causing unintentional harm grows. This is because often these systems are optimizing for criteria that is different than our own, often meaning that it does not consider the many social and cultural norms that we implicitly and explicitly use when making decisions. In a value-aligned system, however, system behavior and objectives are aligned with expected human sociocultural norms. Creating a value-aligned system, however, can be difficult as sources of explicit value information are scarce. In this tutorial, I will discuss how large language models, specifically GPT-4o, can be used to perform practical value…

September 12, 202412:15 pm Speaker:Brent Harrison, Computer Science, University of Kentucky Where:327 McVey Hall(Zoom link: https://uky.zoom.us/j/82467171189) Title:A Gentle Introduction to Modern Machine Learning Abstract: Machine learning has rapidly grown over the last few years. Currently, there are many elements of our social and work lives that utilize, in some way, a machine learning system. To better utilize these systems, it is important to understand how these systems work. In this talk, I will provide an overview of machine learning systems to provide a foundation that the other talks in this series can build on. I will focus on high-level details of how these systems work, how they're often used in practice, and their data requirements. Click here to see the complete list of speakers.

May 7, 20243:00 pm – Refreshments3:30 pm – Presentation Speaker:Emilio Romano-Diaz, Argelander-Institute for Astronomy, University of Bonn, Germany Where:Davis Marksbury Building – James F. Hardymon Theatre(Zoom link: https://uky.zoom.us/s/84474671604) Title:Cosmology via big data in Astrophysics  Abstract: State-of-the-art observational surveys such as the one carried out by the EUCLID mission, BOSS, DES and forthcoming ones like LSST, HETDEX among others, will cover of the order of 10000 square degrees on the sky, with the primary science goal to unravel the nature of the physics responsible for the current accelerated expansion of the universe. The unprecedented and rich data provided by these surveys will make it possible to investigate fundamental physics (e.g. inflation, neutrino properties) and astrophysics (e.g. biasing, galaxy formation). The success of future large-scale galaxy surveys evidently requires a correct interpretation…

April 30, 20243:00 pm – Refreshments3:30 pm – Presentation Speakers:(1) Barry Farmer, Center for Computational Sciences, University of Kentucky(2) Satrio Husodo, Information Technology Services - Research Computing Infrastructure, University of Kentucky(3) Vikram Gazula, Center for Computational Sciences, University of Kentucky Where:Davis Marksbury Building – James F. Hardymon Theatre(Zoom link: https://uky.zoom.us/s/84474671604) Title:Breaking Barriers: Accessing HPC Resources Through User-Friendly Interfaces Abstract:Navigating high-performance computing (HPC) resources can be daunting and challenging, even for experienced researchers, due to the reliance on the command-line interface.  This seminar will show you how to use HPC resources through web graphical user interfaces (GUIs).  These interfaces help users in the basic navigation of the cluster operating system, computational job submission, and data workflows.  For example, we will showcase Python data analysis workflows that can be easily performed on…

April 16, 20243:00 pm – Refreshments3:30 pm – Presentation Speakers:(1) Chad Risko, Department of Chemistry, University of Kentucky (2) Hunter Moseley, Department of Molecular and Cellular Biochemistry, University of Kentucky Where:Davis Marksbury Building – James F. Hardymon Theatre(Zoom link: https://uky.zoom.us/s/84474671604) Titles:(1) Towards Machine-driven Discovery of Organic Materials(2) A cautionary tale about properly vetting datasets used in supervised learning predicting metabolic pathway involvement Abstracts:(1) There is significant interest in the development of organic materials for applications that span new generations of electronic, optical, and energy generation and storage technologies. The chemical space to be explored for these materials, however, is tremendously large, and at the same time it can often be difficult to derive clear chemical building block-to-material structure–property relationships. As these hurdles have served as significant impediments to the commercial…

March 19, 20243:00 pm – Refreshments3:30 pm – Presentation Speakers:(1) Chang-Guo Zhan, Molecular Modelling and Biopharmaceutical Center, Center for Pharmaceutical Research and Innovation, and Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky(2) Nicholas Teets, Department of Entomology, University of Kentucky Where:Davis Marksbury Building – James F. Hardymon Theatre(Zoom link: https://uky.zoom.us/s/84474671604) Titles: (1) State-of-the-art computational drug design, discovery, and development: Challenges and opportunities  (2) Genomics and transcriptomics of extreme insects Abstracts:(1) Discovery and development of a novel drug to meet an unmet medical need is generally an extremely long and very costly process. This process may be accelerated by performing state-of-the-art computational design in all phases of drug discovery and development. Computational drug design has been evolving from ligand-based drug design to structure-based drug design and further to mechanism-based…

February 27, 20243:00 pm – Refreshments3:30 pm – Presentation Speaker:(1) Tyler Burkett, UK ITSRCD, University of Kentucky(2) Helene Gold & Isaac Wink, UK Libraries, University of Kentucky Where:Davis Marksbury Building – James F. Hardymon Theatre(Zoom link: https://uky.zoom.us/s/84474671604) Title: (1) Tackling Big Data Storage Challenges(2) Services and Perspectives on Research Data Abstract: (1) Large data sets (a.k.a. “Big Data”) has become commonplace and is a driving force behind the impressive research capabilities being enabled by AI. Researchers are increasingly faced with a bewildering array of options when dealing with the challenges of managing big data sets. This talk will provide insights and best practices regarding the use and storage of large data sets including the various types of storage currently available, options for accessing and sharing data, tips for high-speed data…