September 23-25, 2024
Texas Advanced Computing Center
Pickle Research Campus | Austin, TX
Speakers
Dr. Tan Bui-Thanh
Associate Professor Oden Institute for Computational Engineering and Sciences, Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin
Learn2Solve: A Deep Learning Framework for Real-Time Solutions of Forward, Inverse, and Uncertainty Quantification Problems
Dr. Tan Bui-Thanh is an associate professor, and the endowed William J Murray Jr. Fellow in Engineering No. 4, of the Oden Institute for Computational Engineering & Sciences, and the Department of Aerospace Engineering & Engineering mechanics at the University of Texas at Austin.
He has decades of experience and expertise on multidisciplinary research across the boundaries of different branches of computational science, engineering, and mathematics. Dr. Bui-Thanh is currently a co-director of the Center for Scientific Machine Learning at the Oden Institute. He is a former elected vice president of the SIAM Texas-Louisiana Section, and a former elected secretary of the SIAM SIAG/CSE. Dr. Bui-Thanh was an NSF (OAC/DMS) early CAREER recipient, the Oden Institute distinguished research award, and a two-time winner of the Moncrief Faculty Challenging award.
Dr. Clint Dawson
J.J. McKetta Centennial Energy Chair in Engineering and Department Chair, Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin
How HPC Revolutionized Storm Surge Modeling
Dr. Clint Dawson holds the Cockrell Family Regents Chair in Engineering #2 and is department chair of the Department of Aerospace Engineering and Engineering Mechanics. He is also the head of the Computational Hydraulics Group in the Oden Institute for Computational Engineering and Sciences.
Dr. Dawson has authored or co-authored over 200 technical articles in the areas of numerical analysis, numerical methods and parallel computing, with applications to flow and transport in porous media, and shallow water systems.
Earlier this year, Dawson received The University of Texas President's Research Impact Award, which recognizes university researchers whose scholarly or creative endeavors have changed lives and the way we look at and understand the world.
Dr. Stella Offner
Associate Professor of Astronomy Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin
Expanding the Frontera of Astrophysics: From Galaxies to Individual Stars
Dr. Stella Offner is an Associate Professor of Astronomy at UT Austin and Co-Director of the Center for Scientific Machine Learning.
Prof. Offner's research focuses on understanding how stars like the Sun form by combining numerical simulations, observations and observational modeling. She uses statistical techniques and machine learning to parse data and identify the physical characteristics of forming stars.
From 2009-2012 she was an NSF Astronomy & Astrophysics prize postdoctoral fellow at the Harvard-Smithsonian Center for Astrophysics and a NASA Hubble prize postdoctoral fellow at Yale from 2012-2014.
Dr. Hedeih Torabifard
Assistant Professor of Chemistry and Biochemistry The University of Texas at Dallas
Computational Investigation of Fluoride Export Proteins
Dr. Torabifard is an Assistant Professor in Chemistry and Biochemistry at the University of Texas Dallas.
Dr. Torabifard’s research has two main focuses: investigation of biological function and structure of membrane transport proteins to uncover more details about their selectivity and transport mechanisms, and design of new bio-based ionic liquids to improve the green character of ionic liquids and to overcome the drawbacks of currently employed ionic liquids such as toxicity and low biodegradability.
She was recently awarded an NIH-NIGMS (MIRA) grant to support her work on transmembrane transporters, and an American Chemical Society Petroleum Research Fund DNI grant to support her research on modeling environmentally friendly bio-based ionic liquids.
Dr. Dan Stanzione
Associate Vice President For Research, UT Austin
Executive Director, TACC
State of the Center Address
Dr. Dan Stanzione is a nationally recognized leader in the field of high performance computing who has made an impact in the open science community for more than 30 years.
He is Executive Director of the Texas Advanced Computing Center (TACC), one of the leading advanced academic computing centers in the world and holds the position of Associate Vice President for Research at The University of Texas at Austin.
Stanzione serves as the principal investigator (PI) for the U.S. National Science Foundation (NSF) Leadership Class Computing Facility (LCCF), which started construction in July 2024 and is expected to begin operations in 2026. The LCCF will deploy Horizon, which will be the largest academic supercomputer dedicated to open science research in the NSF portfolio.
Stanzione is also the PI for several current NSF-funded supercomputers including Frontera, the fastest supercomputer at a U.S. university, and Vista, an AI-centric system—all dedicated to open science research.
Stanzione received his bachelor’s degree in electrical engineering and his master's degree and doctorate in computer engineering from Clemson University.
Tutorials
Containers for HPC Reproducibility: Building, Deploying, and Optimizing
Presenters: Erik Ferlanti, John Fonner
Software containers have gained immense popularity as an effective means for enhancing the portability and reproducibility of high-performance computing (HPC) applications. This hands-on workshop is designed to provide a comprehensive introduction to building, running, and distributing Docker and Singularity/Apptainer containers specifically tailored for HPC environments. Participants will receive in-depth guidance on creating HPC-compliant containers that are not only suitable for local testing and development but also optimized for deployment on advanced HPC systems.Special attention will be given to the intricacies of building containers that can run on multiple nodes using MPI and using accelerated hardware such as GPUs. Moreover, the workshop will delve into best practices for containerization in HPC contexts, troubleshooting common issues, and strategies for ensuring the seamless integration of containers into existing HPC workflows. By the end of the session, attendees will be equipped with the knowledge and skills necessary to leverage the full potential of HPC containers, contributing to more efficient, reproducible, and scalable computing solutions.
Reproducible ML Workflows and Deployments with Tapis
Presenters: Joe Stubbs, Christian Garcia, Nathan Freeman, Anagha Jamthe, Steve Black, Gilbert Curbelo
This tutorial aims to provide researchers with a comprehensive introduction to the latest reproducible Machine Learning (ML) workflows and tooling provided by the NSF-funded Tapis v3 Application Programming Interface (API) and User Interface (UI). Through hands-on exercises, participants will gain experience in querying pre-trained ML models from public ML infrastructures such as Hugging Face or the ICICLE AI Institute, deploying various ML work-environments, and developing ML workflows on national-scale supercomputing resources. Throughout this tutorial, we will focus on utilizing the Tapis Workflows API, Tapis Pods API, Tapis ML Hub API, and TapisUI. These production-grade services are designed to simplify the facilitation and creation of trustworthy, reproducible, scientific workflows. By abstracting the complexities of underlying technologies behind user-friendly APIs, the Tapis services enable seamless integration with high performance computing (HPC) resources available at institutions with a Tapis deployment. Ultimately the tutorial aims to empower researchers to efficiently develop, deploy, and maintain their own ML workflows.
CUDA Programming: Basic Concepts in C and Fortran
Presenter: Lars Koesterke
Effective CUDA code differs from conventional code as it has to reflect and accommodate architectural features of GPUs. In this tutorial I will discuss several key elements of the hardware and the software, i.e. how the execution of a loop matches the grid and block structure of the hardware, how user-managed cache memory is leveraged for speed, and how data is transferred asynchronously from host to device. The tutorial is intended for intermediate-level C/C++ and Fortran programmers who are interested in making the first steps towards CUDA programming for GPUs.
Modern C++ for Computational Science
Presenter: Victor Eijkhout
C++ has seen increasing popularity in computational science in recent years, and accordingly the standard has started including features that accommodate such use. One of the main innovations in recent C++ standards is the use of ranges and range algorithm, which is a more elegant, and less error-prone way of expressing data parallel loops. We cover the basic concepts of ranges and range adapters, as well as lambda expression which are often used in range algorithms. There are various ways that ranges can be used in parallel processing, and we will cover several of these: including OpenMP integration, and the standard mechanism of parallel execution policies. The second relevant innovation is true multi-dimensional array handling. This comes from the `mdspan' library, which rather than providing a new container type, gives a non-owning view into traditional containers such as the standard vector. We will give an example-driven introduction to these concepts, and show how they can be combined to express for instance stencil operations.
Lightning Talks
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1 |
Topo-CNN: Breast Cancer Detection with Topological Deep LearningBrighton Nuwagira |
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2 |
Simulation of the Mosquito Population after Hurricane HarveyLiting Huang |
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3 |
Transcatheter Edge-to-Edge Repair Procedural Parameters Impact Valve Function and MechanicsCollin Haese |
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4 |
GPU-Accelerated Simulation of Deformable Capsules Flowing Through A PipeJoar Bagge |
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5 |
Studying Vibrio cholerae ToxR(ToxT)-DNA Interactions using GROMACSHugo Villar Castellanos |
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6 |
Gravity Missions at The Center for Space Research: 22+ Years of Scientific Discoveries and Expanding Societal ApplicationsJohn C Ries |
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7 |
Deep Learning Approaches for Time Series Forecasting of NICU Heart Rate DataKangsheng Qi |
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8 |
Simulation of Dissipative Electron Quantum Transport in Si Nanowire Transistors: Effects of Phonon ConfinementBimin Cai |
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9 |
The Process of Using Polycraft World AI Lab on TACC’s Lonestar6 to Train and Evaluate Agent Performance in Novel ScenariosStephen A. Goss |
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10 |
Granular Analysis of Social Media Users’ Truthfulness Stances Toward Climate Change Factual ClaimsHaiqi Zhang |
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11 |
WITHDRAWN |
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12 |
Evaluating the Impacts of Climate Change on Surface Water and Groundwater Availability in the Brazos River Basin, TexasHao-Po Chang |
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13 |
TopOC: Topological Deep Learning for Ovarian and Breast Cancer DiagnosisSaba Fatema |
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14 |
Evaluation of Machine Learning Models for Propensity Score Matching in Clinical Real-World DataJustin Nguyen |
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15 |
Enhancing LLM Fine-tuning for Text-to-SQLs by SQL Quality MeasurementLijun Qian |
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16 |
Effects of Offshore Wind Energy on Ocean Circulation and MixingMiguel A. Guzmán Hernández |
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17 |
The UT-City Climate Colab and TACC Partnership in Advanced Weather Prediction and Urban ResilienceDev Niyogi |
Poster Presentations
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1 |
Topo-CNN: Breast Cancer Detection with Topological Deep LearningBrighton Nuwagira, Qiwei Li, and Baris CoskunuzerThe University of Texas at Dallas |
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2 |
Simulation of the Mosquito Population after Hurricane HarveyLiting Huang1, Eirik Valseth1,2, Albert Cerrone1,5, Jennifer Proft1, Chayanon Wichitrnithed1, Michael Shensky3, Katherine Brown1,4, and Clint Dawson1,61. Oden Institute, The University of Texas at Austin 2. Department of Data Science, Norwegian University of Life Science, Norway 3. University of Texas Libraries, The University of Texas Austin 4. Cavendish Laboratory, University of Cambridge, UK 5. Civil and Environmental Engineering and Earth Sciences, University of Notre Dame 6. Aerospace Engineering and Engineering Mechanics, The Oden Institute for Computational Engineering |
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3 |
Transcatheter Edge-to-Edge Repair Procedural Parameters Impact Valve Function and MechanicsCollin Haese1, Vijay Dubey1, and Manuel Rausch21. Department of Mechanical Engineering, The University of Texas at Austin 2. Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin |
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4 |
GPU-Accelerated Simulation of Deformable Capsules Flowing Through A PipeJoar Bagge, George Biros, and Dhwanit AgarwalOden Institute, The University of Texas at Austin |
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5 |
Studying Vibrio cholerae ToxR(ToxT)-DNA Interactions using GROMACSHugo Villar Castellanos, Ahmed Touhami, and Andreas HankeDepartment of Physics and Astronomy, The University of Texas Rio Grande Valley |
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6 |
Gravity Missions at The Center for Space Research: 22+ Years of Scientific Discoveries and Expanding Societal ApplicationsJohn C Ries, and The Entire GRACE/GRACE-FO TeamThe Center for Space Research, The University of Texas at Austin |
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7 |
Deep Learning Approaches for Time Series Forecasting of NICU Heart Rate DataKangsheng Qi, and Joshua ChangOden Institute for Computational Engineering and Sciences; and the Department of Neurology, Dell Medical School, The University of Texas at Austin |
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8 |
Simulation of Dissipative Electron Quantum Transport in Si Nanowire Transistors: Effects of Phonon ConfinementBimin Cai1, Maarten L. Van de Put2, and Massimo V. Fischetti11. Department of Materials Science and Engineering, The University of Texas at Dallas 2. Imec, Leuven, Belgium |
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9 |
The Process of Using Polycraft World AI Lab on TACC’s Lonestar6 to Train and Evaluate Agent Performance in Novel ScenariosStephen A. GossHigh Performance Computing Center, The University of Texas at Dallas |
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10 |
Granular Analysis of Social Media Users’ Truthfulness Stances Toward Climate Change Factual ClaimsHaiqi Zhang, Zhengyuan Zhu, Zeyu Zhang, Jacob Devasier, and Chengkai LiComputer Science and Engineering, The University of Texas at Arlington |
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11 |
WITHDRAWN |
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12 |
Evaluating the Impacts of Climate Change on Surface Water and Groundwater Availability in the Brazos River Basin, TexasHao-Po ChangEnvironmental Engineering Department, Texas A&M University-Kingsville |
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13 |
TopOC: Topological Deep Learning for Ovarian and Breast Cancer DiagnosisSaba Fatema1, Brighton Nuwagira1, Sayoni Chakraborty1, Reyhan Gedik2, and Baris Coskunuzer11. Department of Mathematical Sciences, The University of Texas at Dallas 2. MGH-Department of Pathology, Harvard Medical School |
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14 |
Evaluation of Machine Learning Models for Propensity Score Matching in Clinical Real-World DataJustin Nguyen1, Kostiantyn Botnar2, Madison G. Farnsworth3, Sarah Almentrat2, Vivan Tat2, Kamil Khanipov2, and George Golovko21. Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch 2. Department of Pharmacology and Toxicology, The University of Texas Medical Branch 3. Human Pathophysiology and Translational Medicine, The University of Texas Medical Branch |
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15 |
Enhancing LLM Fine-tuning for Text-to-SQLs by SQL Quality MeasurementLijun Qian1,2, Shouvon Sarker1, Xishuang Dong1, and Xiangfang Li11. CREDIT Center, Prairie View A&M University 2. Department of Electrical and Computer Engineering, Prairie View A&M University |
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16 |
Effects of Offshore Wind Energy on Ocean Circulation and MixingMiguel A. Guzmán Hernández1, J. M. Perez Medina2, K. Yousefi1, and S. Leonardi11. Department of Mechanical Engineering, The University of Texas at Dallas 2. Department of Mechanical Engineering, University of Puerto Rico at Mayaguez |
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17 |
The UT-City Climate Colab and TACC Partnership in Advanced Weather Prediction and Urban ResilienceDev Niyogi, and The UT-City Climate CoLab TeamTExUS Lab and UT-City Climate CoLab, The University of Texas at Austin |
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18 |
Aerodynamic Optimization for FSAE Style Vehicles using Computational Fluid Dynamics and Pareto HypernetworksHayden Bell1, Ryan Hopke2, and Sasmita Mohapatra31. Department of Computer Science, The University of Texas at Dallas 2. Department of Mechanical Engineering, The University of Texas at Dallas 3. Cyberinfrastructure & Research Services, The University of Texas at Dallas |
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19 |
Wise-GNN: Enhancing GNNs with Wise EmbeddingsMd Joshem Uddin1, Astrit Tola1, Cuneyt Gurcan Akcora2, and Baris Conkunuzer11. Department of Mathematical Sciences, The University of Texas at Dallas 2. Department of Computer Science, University of Central Florida |
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20 |
Artificial Intelligence for the Public Sector: Bridging the Gap between Academia and PracticeZander Mintz, and Ji MaLBJ School of Public Affairs, The University of Texas at Austin |
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21 |
Flood Impact Mitigation: Assessing the Role of Natural Barriers in Protecting Crops in the Rio Grande Valley, TexasStone Nwamadi, Ira Narang, Jennifer Proft, Clint Dawson, and Katherine BrownThe University of Texas at Austin |
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22 |
Topological Machine Learning for Computer-Aided Medical DiagnosisPhilmore Koung1, Brighton Nuwagira1, Caner Korkmaz2, and Baris Coskunuzer11. Department of Natural Sciences and Mathematics, The University of Texas at Dallas 2. Imperial College London |
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23 |
Fluid-Structure Interaction Simulation of Non-Uniformly Calcified Aortic ValveMishal Raza-Taimuri, and Hamid SadatDepartment of Mechanical Engineering, University of North Texas |
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24 |
Theoretical Study of Carrier Transport in Bilayer Transition Metal DichalcogenidesShoaib Mansoori1, Gautam Gaddemane2, Sanjay Gopalan3, Massimo Fischetti1, and Edward Chen41. Department of Material Science and Engineering, The University of Texas at Dallas 2. Imec, Belgium 3. Bosch Research, USA 4. Taiwan Semiconductor Manufacturing Company (TSMC), Taiwan |
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25 |
Detecting Stance of Social Media Posts Toward Truthfulness of Factual Claims for Social GoodsZhengyuan Zhu, Haiqi Zhang, Zeyu Zhang, and Chengkai LiThe University of Texas at Arlington |
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26 |
Classical Simulability of Gaussian Boson SamplingSarvesh Raghuraman, and Brian La CourApplied Research Laboratories, The University of Texas at Austin |
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27 |
Flood Impact Mitigation: Assessing the Role of Sand Dunes in the Rio Grande Valley, TexasIra Narang1, Clint Dawson1,2, Katherine A. Brown1,3, and Jennifer Proft11. The Oden Institute for Computational Engineering & Sciences, The University of Texas at Austin 2. Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin 3. Cavendish Laboratory, University of Cambridge UK |
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28 |
TopER: Topological Embeddings in Graph Representation LearningAstrit Tola1, Funmilola Mary Taiwo2, Cuneyt Gurcan Akcora3, and Baris Coskunuzer11. Department of Mathematics, The University of Texas at Dallas 2. Department of Statistics, University of Manitoba 3. AI Institute, University of Central Florida |
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29 |
Remote Visualization in Fluid DynamicsBrandon Antron, Sakshi More, and Guillermo ArayaComputational Turbulence and Visualization Lab, Department of Mechanical Engineering, The University of Texas at San Antonio |
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30 |
Molecular Dynamics Approach for Process Modeling and Material Characterization of Carbon FibersMd Fazlay Alam, and Armanj D. HasanyanAerospace and Mechanical Engineering, The University of Texas at El Paso |
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31 |
Network Performance Monitoring with NetSageDoug SouthworthTexas Advanced Computing Center, The University of Texas at Austin |
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32 |
Robust Frame-Semantic Models with Lexical Unit Trees and Negative SamplesJacob Devasier, and Chengkai LiDepartment of Computer Science and Engineering, The University of Texas at Arlington |
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33 |
Numerical Investigation of Angular Particle DynamicsJohn Michael B. Tubije1, Umberto Ciri2, Sylvia Rodríguez-Abudo3, and Stefano Leonardi11. Department of Mechanical Engineering, The University of Texas at Dallas 2. Department of Mechanical Engineering, University of Puerto Rico at Mayagüez 3. Department of Engineering Sciences and Materials, University of Puerto Rico at Mayagüez |
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34 |
Parallel K-Core Decomposition Algorithm for Large Dynamic GraphsFarahnaz HosseiniUniversity of North Texas |
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35 |
The UT-OSPOAngela Newell1, Jennifer Schopf2, and Michael Shensky31. Chief Information Office, The University of Texas at Austin 2. TACC, The University of Texas at Austin 3. University Libraries, The University of Texas at Austin |
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36 |
Simulating Stiff Systems with A Linear Parameterized Latent SpaceCole Nockolds1, C. G. Krishnanunni2, and Tan Bui11. Oden Institute, The University of Texas at Austin 2. Department of Aerospace Engineering, The University of Texas at Austin |
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37 |
Using Kwant to Unveil a Non-sinusoidal Current-phase Relation in a Semiconductor-superconductor Josephson JunctionKonner Feldman1, Zhuoqun Hao2, and Shyam Shankar21. Department of Physics, The University of Texas at Austin 2. Electrical and Computer Engineering, The University of Texas at Austin |
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38 |
Photoswitchable Liposomes for Drug DeliveryKevin Alberto1, M.N. Hasna Begam1, Hejian Xiong2,3, Wataru Shinoda4, Paul A. Slesinger5, Zhenpeng Qin6, and Steven O. Nielsen11. Department of Chemistry and Biochemistry, The University of Texas at Dallas 2. Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence 3. Department of Neurobiology, School of Basic Medical Sciences, Southern Medical University 4. Research Institute for Interdisciplinary Science, Okayama University 5. Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai 6. Department of Mechanical Engineering, The University of Texas at Dallas |
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39 |
Graph Neural Networks for Contact between Deformable BodiesVijay Dubey1, Collin E. Haese1, Jan Fuhg2, Manuel K. Rausch2,3,4, and Osman Gültekin21. Department of Mechanical Engineering, The University of Texas at Austin 2. Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin 3. Department of Biomedical Engineering, The University of Texas at Austin 4. Oden Institute of Computation Engineering and Sciences, The University of Texas at Austin |
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40 |
Exploring Behavioral Tendencies on Social Media: A Perspective Through Claim Check-WorthinessZeyu Zhang, Zhengyuan Zhu, Haiqi Zhang, and Chengkai LiDepartment of Computer Science & Engineering, The University of Texas at Arlington |
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41 |
Rice Field Irrigation Mapping from High-resolution Aerial Imagery using a Contextual-aware Deep NetworkAniv Chakravarty1, Xiaohui Yuan1, Abolfazl Meyarian1, and Lu Liang21. Department of Computer Science, University of North Texas 2. Department of Landscape Architecture & Environmental Planning, Berkeley College of Environmental Design |
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42 |
Computationally Predicting a Synaptic NF-kB Protein Interaction NetworkHaley Goodwin, and Nigel S. AtkinsonDepartment of Neuroscience and Waggoner Center for Alcohol & Addiction Research, The University of Texas at Austin |
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43 |
Power in Numbers: Emergent Phenomena from Increasing Droplet Size in Biomolecular CondensatesCaleb Huang, and B. Montgomery PettittDepartment of Biochemistry and Molecular Biology, The University of Texas Medical Branch |
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44 |
Air Quality and Health Co-Benefits of Vehicle Electrification and Emission Controls in Major US Urban HubsAli Mousavinezhad1, Yunsoo Choi2, Nima Khorshidian2, Masoud Ghahremanloo2, and Mahmoudreza Momeni21. Jackson School of Geosciences, University of Texas at Austin 2. Department of Earth and Atmospheric Science, University of Houston |
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45 |
Content Moderation in the Era of Generative AIEmet Bethany1, Mazal Bethany2, and Peyman Najafirad11. Department of Computer Science, The University of Texas at San Antonio 2. Department of Information Systems, The University of Texas at San Antonio; |
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46 |
Parallel Processing Framework for Analyzing Spatiotemporal Variation in Dust Storm EventsHassan Dashtian1,, Alexander Lee2, Asim Waheed2, Ali Mousavinezhad1, and Manmeet Singh11. Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin 2. Department of Computer Science, The University of Texas at Austin |
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47 |
Towards Adaptive Selection of Directions in Unconstrained, Deterministic Derivative-Free OptimizationMarissa Llamas1, Raghu Bollapragada2, and Cem Karamanli21. Department of Mathematics, The University of Texas at Austin 2. Operations Research and Industrial Engineering, The University of Texas at Austin, |
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48 |
Assessing Biases in AI-Driven Hurricane Forecasting: A Comparative Study of Leading Models in the Gulf of MexicoNaveen Sudharsan1, Manmeet Singh2, Harsh Kamath2, Sasanka Talukdar2, Shyama Mohanty2, Krishna Kishore Osuri3, Hassan Dashtian2, Clint Dawson4,5, Zong-Liang Yang2, and Dev Niyogi2,4,51. Department of Earth and Planetary Sciences, The University of Texas at Austin 2. Jackson School of Geosciences, The University of Texas at Austin 3. Department of Earth and Atmospheric Science, National Institute of Technology Rourkela 4. Cockrell School of Engineering, The University of Texas at Austin 5. Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin |
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49 |
Numerical Implementation of the Barrier Lowering Effect at Metal SurfacesPranay Baikadi, and William G. VandenbergheDepartment of Materials Science, The University of Texas at Dallas |
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50 |
Real-time Sentiment and Emotion Analysis of Social Media Content on Energy TransitionHassan Dashtian1, David J. Lee2, Maria-Laura Peña2, Manmeet Singh1, and Michael H. Young11. Bureau of Economic Geology, Jackson School of Geosciences, University of Texas at Austin 2. Department of Computer Science, University of Texas at Austin |
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51 |
UT-MeteoGAN: A Next-Generation AI Model for High-Resolution Numerical Weather PredictionManmeet Singh1, Naveen Sudharsan1, Harsh Kamath1, Vaisakh SB2, Hassan Dashtian3, Arya Chavoshi1, John Fonner4, Clint Dawson5, Michael Young1, Zong-Liang Yang1, and Dev Niyogi11. Jackson School of Geosciences, The University of Texas at Austin 2. Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India 3. Bureau of Economic Geology, The University of Texas at Austin 4. Texas Advanced Computing Center, The University of Texas at Austin 5. Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, |
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52 |
Enabling Automated Fact Checking of Voting Related Claims Using Frame Semantic Parsing and Semantic SearchRishabh Mediratta, Jacob Devasier, and Chengkai LiDepartment of Computer Science & Engineering, The University of Texas at Arlington |
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53 |
Engagement and Performance Operations Center (EPOC)Corey Eichelberger1, Jen Schopf1, Nathaniel Mendoza1, Doug Southworth1, George Robb2, and Jason Zurawski21. Texas Advanced Computing Center, The University of Texas at Austin 2. DOE Energy Sciences Network, Lawrence Berkeley National Lab |
