Accepted Papers

We accepted 33 outstanding papers from 98 submissions.

Lorenz Gruber, Nikolas Herbst, Thomas Esch, Thanh Nguyen, Peter Friedl and Samuel Kounev. The FISHNET Case Study on Implementing and Scaling a Complex Earth Observation Workflow
Slava Kitaeff, Luc Betbeder-Matibet and Jake Carroll. Institutional Research Computing Capabilities in Australia: 2024
Floris-Jan Willemsen, Rob van Nieuwpoort and Ben van Werkhoven. Tuning the Tuner: Introducing Hyperparameter Optimization for Auto-Tuning
Max Morris, Steven R. Brandt and Hartmut Kaiser. Locks Must Die: Composable Mutual Exclusion Implemented by Dynamic Resource Sharing on Task Graphs
Hy Nguyen, Srikanth Thudumu, Hung Du, Rajesh Vasa and Kon Mouzakis. Optimizing Deep Reinforcement Learning Configurations for Single Object Tracking
Pedro Valero-Lara, William Godoy, Philip Fackler, Keita Teranishi and Jeffrey Vetter. Enabling Scientific Applications with Performance-Portability and High-Productivity for Multi-GPU Programming with JACC
Gabriel Laboy, Ian Lumsden, Paula Olaya, Jack Marquez, Kin Wai Ng, Rodrigo Vargas and Michela Taufer. GEOtiled-SG: A Scalable Framework for High-Resolution Terrain Parameter Computation
Mahib Ornob, Lan Li and Hasan Jamil. Dreaming Up Novel Quantum Dyes using Inverse Machine Learning in MatFlow
Andrei Bachinin, Rupasree Dey, Paahuni Khandelwal, Sam Leuthold, M. Francesca Cotrufo, Shrideep Pallickara and Sangmi Lee Pallickara. Science-Informed Multitask Transformer for Soil Property Prediction from FTIR Spectroscopy
Maximilian Inckmann, Nicolas Blumenröhr and Rossella Aversa. Towards Machine-actionable FAIR Digital Objects with a Typing Model that Enables Operations
Marcus Schwarting, Logan Ward, Nathaniel Hudson, Xiaoli Yan, Ben Blaiszik, Santanu Chaudhuri, Eliu Huerta and Ian Foster. Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization
Raffay Atiq, Ashish Gehani, Tanu Malik and Fareed Zaffar. SCALPEL: Structured Content Access Logger and Pruner for Efficient Layouts
Florine Willemijn de Geus, Vincenzo Eduardo Padulano, Jakob Blomer, Hannes Mühleisen and Ana-Lucia Varbanescu. EventSetProcessor: An Engine for Efficiently Combining High-Energy Physics Data
Krishna Priya, Sachith Withana and Beth Plale. P-RGCNs: Missing Link Prediction in Model Card Graphs through Node Property Encodings
Kaveen Hiniduma, Zilinghan Li, Aditya Sinha, Ravi Madduri and Suren Byna. CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning
Lilin Yu and Rosa Filgueira. Frances++: LLM-Based Semantic Enrichment and Spatial Graphs for Digitized Historical Collections
Tirtha Pani, Raj Abhijit Dandekar, Prathamesh Dinesh Joshi, Rajat Dandekar and Sreedath Panat. A Novel Scientific Machine Learning Method for Epidemiological Modelling
Alejandro Valdés-Jiménez, Gabriel Núñez-Vivanco and Daniel Jiménez-González. Parallel and Distributed Protein Processing for 3D-protein Pattern Discovery and Clustering
Daniela Cassol, Alicia Clum, Jeff Froula, Ed Kirton, Ramani Kothadia, Mario Melara, Elais Player-Jackson, Setareh Sarrafan, Seung-Jin Sul, Stephan Trong, Nick Tyler, Tomas Bruna, Leo Baumgart and Kjiersten Fagnan. Supporting FAIR Scientific Workflows with the JGI Analysis Workflow Service (JAWS)
Colin Thomas and Douglas Thain. Liberating the Data Aware Scheduler to Achieve Locality in Layered Scientific Workflow Systems
Haotian Xie, Rohan Marwaha, Minu Mathew, Song Bian, Gengcong Yang, Minghao Yan, Yadu Babuji, Owen Price, Yinzhi Wang, Volodymyr Kindratenko, Shivaram Venkataraman, Kyle Chard, Ian Foster and Zhao Zhang. Diamond: Harnessing GPU Resources for Scientific Deep Learning
Fernanda Cabral, Maria Alexandra Hubbard, Rudhvish Patel, Adeola Badmos, Daniela Raicu, Raj Shah and Roselyne Tchoua. Novel Perspective on Ensemble Clustering for Persistent Cluster Patterns: A Case Study in Disease Cluster Discovery
Sandro Gepiro Contaldo, Lorenzo Bosio, Janneth Estefania Hoyos Rea, Elisa Li Perottino, Sergio Rabellino, Marco Aldinucci, Marco Beccuti and Iacopo Colonnelli. BookedSlurm: meeting user needs for advanced resource reservations in Slurm
Georgios Evangelopoulos, Gholamali Hoshyaripour, Jörg Meyer, Pankaj Kumar, Julia Bruckert and Achim Streit. Accelerating Weather Forecasting: A Neural Network-Based Emulation of ISORROPIA
Md Saiful Islam, Talha Azaz, Raza Ahmad, A S M Shahadat Hossain, Furqan Baig, Shaowen Wang, Kevin Lannon, Tanu Malik and Douglas Thain. Backpacks for Notebooks: Enabling Containerized Notebook Workflows in Distributed Environments
Amena Begum Farha, Abdullah Al-Mamun, Gagan Agrawal and Ahmed Aleroud. Reinventing CI/CD for Collaborative Sciences: A Blockchain-Integrated Decentralized Middleware for Scalable and Fault-Tolerant Workflows
Thomas Marrinan, Andres Sewell, Victor Mateevitsi, Steve Petruzza, Jifu Tan, Dimitrios Fytanidis and Michael Papka. Intuitive Computational Steering Using Ascent and Trame
Isaac Nealey and Ilkay Altintas. Modeling Remote Sensing Data Relationships with Spatiotemporal Knowledge Graphs
Naveen Kumar Reddy Veeramreddy, Ankita Mishra, Navika Maglani, Sameer Shaik, Kelly McCabe, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua and Jamshid Sourati. Leveraging Hidden Patterns in Open-Ended Health Workers' Notes to Improve Prediction of Patient Readmission
Zhiwei Li, Carl Kesselman, Tran Huy Nguyen, Benjamin Xu, Kyle Bolo and Kimberley Yu. From Data to Decision: Data-Centric Infrastructure for Reproducible ML in Collaborative eScience
Moontaha Nishat Chowdhury, Andre Bauer and Minxuan Zhou. Efficient Privacy-Preserving Recommendation on Sparse Data using Fully Homomorphic Encryption
Hamid Omidi, Ludovica Sacco, Valentina Hutter, Gerald Irsiegler, Michele Claus, Martin Schobben, Alexander Jacob, Matthias Schramm and Sandro Luigi Fiore. Towards Provenance-Aware Earth Observation Workflows: the openEO Case Study
Roopkatha Banerjee, Sampath Koti, Gyanendra Singh, Anirban Chakraborty, Gurunath Gurrala, Bhushan Jagyasi and Yogesh Simmhan. Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids