Publications

In addition to the broad scope of papers below, check out our AI/ML Research Spotlight page for selected high-impact publications.

Akhbarishandiz, S., Ray, S., Zhou, F., et al. (2024). “Machine Learning of Performance Space Mapping for the DPD Simulation of Drug Delivery to Endothelial Cells.” Molecular Simulation.

Allaire, C., Ammendola, R., Ashenauer, E.-C., et al. (2024). “Artificial Intelligence for the Electron Ion Collider (AI4EIC).” Computing and Software for Big Science.

Allen, J., and Sanders, G. (2024). “BobGAT: Towards Inferring Software Bill of Behavior with Pre-Trained Graph Attention Networks.” Proceedings - 2024 IEEE 6th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications.

Ashtari Esfahani, A., Böser, S., Buzinsky, N., et al. (2024). “Deep Learning Based Event Reconstruction for Cyclotron Radiation Emission Spectroscopy.” Machine Learning: Science and Technology.

Banday, B-H., Islam, T-Z., Marathe, A. (2024). “PERFGEN: A Synthesis and Evaluation Framework for Performance Data Using Generative AI.” Proceedings - 2024 IEEE 48th Annual Computers, Software, and Applications Conference.

Berger, M., and Liu, S. (2024). “The Visualization JUDGE: Can Multimodal Foundation Models Guide Visualization Design through Visual Perception?” Proceedings - 2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization.

Bertin, N., Bulatov, V-V., and Zhou, F. (2024). “Learning Dislocation Dynamics Mobility Laws from Large-Scale MD Simulations.” npj Computational Materials.

Bonneville, C., Choi, Y., Ghosh, D., Belof, J-L. (2024). “GPLaSDI: Gaussian Process-Based Interpretable Latent Space Dynamics Identification through Deep Autoencoder.” Computer Methods in Applied Mechanics and Engineering.

Chakraborty, D., Chung, S-W., Arcomano, T., Maulik, R. (2024). “Divide and Conquer: Learning Chaotic Dynamical Systems with Multistep Penalty Neural Ordinary Differential Equations.” Computer Methods in Applied Mechanics and Engineering.

Chen, A., Zhang, Y., Jia, J., et al. (2024). “DEEPZERO: Scaling Up Zeroth-Order Optimization for Deep Model Training.” 12th International Conference on Learning Representations.

Chen, X., Chen, T., Olivares, E-Y., et al. (2024). “Cross-Quality Few-Shot Transfer for Alloy Yield Strength Prediction: A New Materials Science Benchmark and A Sparsity-Oriented Optimization Framework” Proceedings of Machine Learning Research.

Chheda, S., Verma, G., Tian, S., Chapman, B., et al. (2024). “Evaluating Tuning Opportunities of the LLVM/OpenMP Runtime.” Proceedings of SC 2024-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis.

Chung, S-W., Choi, Y., Roy, P., et al. (2024). “Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition.” Computer Methods in Applied Mechanics and Engineering.

de Franca, F-O., Virgolin, M., Kommenda, M., et al. (2024). “SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation.” IEEE Transactions on Evolutionary Computation.

Devarajan, H., Lumsden, I., Wang, C., et al. (2024). “DYAD: Locality-aware Data Management for accelerating Deep Learning Training.” Proceedings - Symposium on Computer Architecture and High Performance Computing.

Devarajan, H., Pottier, L., Velusamy, K., et al. (2024). “DFTracer: An Analysis-Friendly Data Flow Tracer for AI-Driven Workflows.” International Conference for High Performance Computing, Networking, Storage and Analysis, SC.

Dey, A., Dhakal, A., Islam, T-Z. (2024). “Relative Performance Prediction Using Few-Shot Learning.” Proceedings - 2024 IEEE 48th Annual Computers, Software, and Applications Conference.

Diaz, A-N., Choi, Y., and Heinkenschloss, M. (2024). “A Fast and Accurate Domain Decomposition Nonlinear Manifold Reduced Order Model.” Computer Methods in Applied Mechanics and Engineering.

Duan, J., Cheng, H., Wang, S., et al. (2024). “Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models.” Proceedings of the Annual Meeting of the Association for Computational Linguistics.

Dzanic, T., Mittal, K., Kim, D., et al. (2024). “DynAMO: Multi-Agent Reinforcement Learning for Dynamic Anticipatory Mesh Optimization with Applications to Hyperbolic Conservation Laws.” Journal of Computational Physics.

Fan, S., Hitt, A-L., Tang, M., et al. (2024). “Accelerate microstructure evolution simulation using graph neural networks with adaptive spatiotemporal resolution.” Machine Learning: Science and Technology.

Fang, B., Li, X., Dam, H., et al. (2024). “Understanding Mixed Precision GEMM with MPGemmFI: Insights into Fault Resilience.” Proceedings - IEEE International Conference on Cluster Computing.

Fink, Z., Parasyris, K., Rathi, P., et al. (2024). “HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific Applications.” International Conference for High Performance Computing, Networking, Storage and Analysis, SC.

Gao, H., Han, X., Fan, X., et al. (2024). “Bayesian Conditional Diffusion Models for Versatile Spatiotemporal Turbulence Generation.” Computer Methods in Applied Mechanics and Engineering.

Georgouli, K., Stephany, R-R., Tempkin, J-O-B., et al. (2024). “Generating Protein Structures for Pathway Discovery Using Deep Learning.” Journal of Chemical Theory and Computation.

Gurniak, E-J., Yuan, S., Ren, X., and Branicio, P-S. (2024). “Harnessing Graph Convolutional Neural Networks for Identification of Glassy States in Metallic Glasses.” Computational Materials Science.

Hayrapetyan, A., Tumasyan, A. Adam, W., et al. (2024). “Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service.” Computing and Software for Big Science.

Hoang, D., Bhatia, H., Lindstrom, P., and Pascucci, B. (2024). “Progressive Tree-Based Compression of Large-Scale Particle Data.” IEEE Transactions on Visualization and Computer Graphics.

Hu, Y. Lei, B., Shah, Y-G., et al. (2024). “Comparative Study of Machine Learning Techniques for Post-Combustion Carbon Capture Systems.” Frontiers in Artificial Intelligence.

Huang, Y., Sun, L., Wang, H., et al. (2024). “Position: TRUSTLLM: Trustworthiness in Large Language Models.” Proceedings of Machine Learning Research.

Jekel, C-F., Sterbentz, D-M., Stitt, T-M., et al. (2024). “Machine Learning Visualization Tool for Exploring Parameterized Hydrodynamics.” Machine Learning: Science and Technology.

Heon, E-S., Choi, H., Shukla, A., et al. (2024). “Topological Persistence Guided Knowledge Distillation for Wearable Sensor Data.” Engineering Applications of Artificial Intelligence.

Kamath, C. (2024). “Classification of Orbits in Poincaré Maps Using Machine Learning.” International Journal of Data Science and Analytics.

Kesavan, S-P., Bhatia, H., Dasu, K., et al. (2024). “Data Movement Visualized: A Unified Framework for Tracking and Visualizing Data Movements in Heterogeneous Architectures.” IEEE Pacific Visualization Symposium.

Lei, B., Fu, Y., Cadena, J., et al. (2024). “Accelerating Computational Fluid Dynamics Simulation of Post-Combustion Carbon Capture Modeling with MeshGraphNets.” Frontiers in Artificial Intelligence.

Leventhal, S., Gyulassy, A., Heimann, M., and Pascucci, V. (2024). “Exploring Classification of Topological Priors With Machine Learning for Feature Extraction.” IEEE Transactions of Visualization and Computer Graphics.

Li, M., Jeong, S., Liu, S., and Berger, M. (2024). “CAN: Concept-Aligned Neurons for Visual Comparison of Deep Neural Network Models.” Computer Graphics Forum.

Li, X., Li, A., Fang, B., et al. (2024). “Discovery of Floating-Point Differences Between NVIDIA and AMD GPUs.” Proceedings - 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing.

Li, Z., Menon, H., Mohror, K., et al. (2024). “A Visual Comparison of Silent Error Propagation.” IEEE Transactions on Visualization and Computer Graphics.

Li, Z., Liu, S., Yu, X., et al. (2024). “Understanding Robustness Lottery: A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches.” IEEE Transactions on Visualization and Computer Graphics.

Liu, S., Bocklund, B., Diffenderfer, J., et al. (2024). “A Comparative Study of Predicting High Entropy Alloy Phase Fractions with Traditional Machine Learning and Deep Neural Networks.” npj Computational Materials.

Lu, J., Zhan, W., Tomizuka, M., and Hu, Y. (2024). “Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach.” Proceedings of Machine Learning Research.

Magri, V-A-P., and Lindstrom, P. (2024). “A General Framework for Progressive Data Compression and Retrieval.” IEEE Transactions on Visualization and Computer Graphics.

Mehra, A., Zhang, Y., Kailkhura, B., and Hamm, J. (2024). “On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization.” Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision.

Menon, H., Nichols, D., Bhatele, A., and Gamblin, T. (2024). “Learning to Predict and Improve Build Successes in Package Ecosystems.” Proceedings - 2024 IEEE/ACM 21st International Conference on Mining Software Repositories.

Narayanaswamy, V., Anirudh, R., and Thiagarajan, J-J. (2024). “The Double-Edged Sword of Ai Safety: Balancing Anomaly Detection and OOD Generalization via Model Anchoring.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.

Nathan, E. (2024). “Disentangling Disparate Communication Streams and Recovering Underlying Structure.” International Conference on Social Networks Analysis, Management and Security.

Nichols, D., Menon, H., Gamblin, T., and Bhatele, A. (2024). “A Probabilistic Approach To Selecting Build Configurations in Package Managers.” International Conference for High Performance Computing, Networking, Storage and Analysis.

Nichols, D., Movsesyan, A., Yeom, J-S., et al. (2024). “Predicting Cross-Architecture Performance of Parallel Programs.” Proceedings - 2024 IEEE International Parallel and Distributed Processing Symposium.

Olson, M-L., Liu, S., Thiagarajan, J-J., et al. (2024). “Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data.” Machine Learning: Science and Technology.

Park, J-S-R., Cheung, S-W., Choi, Y., and Shin, Y. (2024). “tLaSDI: Thermodynamics-Informed Latent Space Dynamics Identification.” Computer Methods in Applied Mechanics and Engineering.

Qi, J., Ko, T-W., Wood, B-C., et al. (2024). “Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling.” npj Computational Materials.

Quinlan, K-R., Movva, J., and Perfect, B., (2024). “Non-Uniform Active Learning for Gaussian Process Models with Applications to Trajectory Informed Aerodynamic Databases.” Statistical Analysis and Data Mining.

Ranganath, A., Munoz, J-O., Smith, R., et al. (2024). “Image Separation Using Transformer Attention Models.” Proceedings - 2024 IEEE International Conference on Future Machine Learning and Data Science.

Ranganath, A., Ruiz, I-R., Singhal, M., and Marcia, R. (2024). “Quasi-Adam: Accelerating Adam Using Quasi-Newton Approximations.” Proceedings - 2024 International Conference on Machine Learning and Applications.

Roy, P., and Castonguay, S-T. (2024). “Exact Enforcement of Temporal Continuity in Sequential Physics-Informed Neural Networks.” Computer Methods in Applied Mechanics and Engineering.

Sarma, A.K., Roy, S., Annavarapu, C., et al. (2024). “Interface PINNs (I-PINNs): A Physics-Informed Neural Networks Framework for Interface Problems.” Computer Methods in Applied Mechanics and Engineering.

Savard, C., Manganelli, N., Holzman, B., et al. (2024). “Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server.” Computing and Software for Big Science.

Schieffer, G., De Medeiros, D-A., Faj, J., et al. (2024). “On the Rise of AMD Matrix Cores: Performance, Power Efficiency, and Programmability.” Proceedings - 2024 IEEE International Symposium on Performance Analysis of Systems and Software.

Scully-Allison, C., Lumsden, I., Williams, K., et al. (2024). “Design Concerns for Integrated Scripting and Interactive Visualization in Notebook Environments.” IEEE Transactions on Visualization and Computer Graphics.

Soper, B-C., Miller, C-J., and Merl, D-M. (2024). “Linearly Solvable General-Sum Markov Games.” 2024 60th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2024.

Sun, H., Hamel, S., Hsu, T., et al. (2024). “Ice Phase Classification Made Easy with Score-Based Denoising.” Journal of Chemical Information and Modeling.

Tempelman, J-R., Mudunuru, M-K., Karra, S., et al. (2024). “Uncovering Acoustic Signatures of Pore Formation in Laser Powder Bed Fusion.” International Journal of Advanced Manufacturing Technology.

Trivedi, P., Heimann, M., Anirudh, R., et al. (2024). “Accurate And Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.” 12th International Conference on Learning Representations.

Trivedi, P., Koutra, D., and Thiagarajan, J-J. (2024). “On Estimating Link Prediction Uncertainty Using Stochastic Centering.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.

Vamplew, P., Foale, C., Hayes, C-F., et al. (2024). “Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.” Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems.

Wan, Q., Cheung, S-W., and Choe, Y.(2024). “AdjointBackMapV2: Precise Reconstruction of Arbitrary CNN Unit's Activation via Adjoint Operators.” Neural Networks.

Wan, Z., Chandramoorthy, N., Swaminathan, K., et al. (2024). “MulBERRY: Enabling Bit-Error Robustness for Energy-Efficient Multi-Agent Autonomous Systems.” International Conference on Architectural Support for Programming Languages and Operating Systems.

Wang, C., Mohror, K., and Snir, M. (2024). “Formal Definitions and Performance Comparison of Consistency Models for Parallel File Systems.” IEEE Transactions on Parallel and Distributed Systems.

Williams, A.S., Maguire, A., Soper, B., and Merl, D. (2024). “The Innate Curiosity in the Multi-Agent Transformer.” Proceedings - 2024 International Conference on Machine Learning and Applications.

Wilson, A.J., Riza Ekti, A., Follum, J., et al. (2024). “The Grid Event Signature Library: An Open-Access Repository of Power System Measurement Signatures.” IEEE Access.

Xu, Y., Sivaraman, P., Devarajan, H., et al. (2024). “ML-based Modeling to Predict I/O Performance on Different Storage Sub-systems.” Proceedings - 2024 IEEE 31st International Conference on High Performance Computing, Data, and Analytics.

Zwieback, S., Young-Robertson, J., Robertson, M., et al. (2024). “Low-Severity Spruce Beetle Infestation Mapped from High-Resolution Satellite Imagery with a Convolutional Network.” ISPRS Journal of Photogrammetry and Remote Sensing.