A mathematical programming viewpoint for solving the ultimate pit problem. - Robert Underwood; Boleslaw Tolwinski (Eur. J. Oper. Res., 1998)

Measuring Network Latency Variation Impacts to High Performance Computing Application Performance. - Robert Underwood; Jason Anderson; Amy W. Apon (ICPE, 2018)

cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data. - Jiannan Tian; Sheng Di; Kai Zhao 008; Cody Rivera; Megan Hickman Fulp; Robert Underwood; Sian Jin; Xin Liang 001; Jon Calhoun 001; Dingwen Tao; Franck Cappello (PACT, 2020)

FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data. - Robert Underwood; Sheng Di; Jon C. Calhoun; Franck Cappello (IPDPS, 2020)

ARC: An Automated Approach to Resiliency for Lossy Compressed Data via Error Correcting Codes. - Dakota Fulp; Alexandra Poulos; Robert Underwood; Jon C. Calhoun (HPDC, 2021)

Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets. - David Krasowska; Julie Bessac; Robert Underwood; Jon C. Calhoun; Sheng Di; Franck Cappello (DRBSD@SC, 2021)

Productive and Performant Generic Lossy Data Compression with LibPressio. - Robert Underwood; Victoriana Malvoso; Jon C. Calhoun; Sheng Di; Franck Cappello (DRBSD@SC, 2021)

Understanding the Effects of Modern Compressors on the Community Earth Science Model. - Robert Underwood; Julie Bessac; Sheng Di; Franck Cappello (DRBSD@SC, 2022)

ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography. - Robert Underwood; Chun Hong Yoon; Ali Murat Gok; Sheng Di; Franck Cappello (CoRR, 2022)

OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration. - Robert Underwood; Jon C. Calhoun; Sheng Di; Amy W. Apon; Franck Cappello (IEEE Trans. Parallel Distributed Syst., 2022)

A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression. - Arkaprabha Ganguli; Robert Underwood; Julie Bessac; David Krasowska; Jon C. Calhoun; Sheng Di; Franck Cappello (CLUSTER, 2023)

MPIGDB: A Flexible Debugging Infrastructure for MPI Programs. - Robert Underwood; Bogdan Nicolae (FlexScience@HPDC, 2023)

Understanding Patterns of Deep Learning Model Evolution in Network Architecture Search. - Robert Underwood; Meghana Madhyastha; Randal C. Burns; Bogdan Nicolae (HiPC, 2023)

A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets. - Md Hasanur Rahman 001; Sheng Di; Kai Zhao 008; Robert Underwood; Guanpeng Li; Franck Cappello (ICDE, 2023)

DStore: A Lightweight Scalable Learning Model Repository with Fine-Grain Tensor-Level Access. - Meghana Madhyastha; Robert Underwood; Randal C. Burns; Bogdan Nicolae (ICS, 2023)

LibPressio-Predict: Flexible and Fast Infrastructure For Inferring Compression Performance. - Robert Underwood; Sheng Di; Sian Jin; Md Hasanur Rahman 001; Arham Khan; Franck Cappello (SC Workshops, 2023)

The Modern History of ICT in Oceania - PEACESAT and USPNet. - Rieko Hayakawa; Robert Underwood; Jennifer Anson (IEEE Ann. Hist. Comput., 2023)

Understanding Patterns of Deep Learning ModelEvolution in Network Architecture Search. - Robert Underwood; Meghana Madhyastha; Randal C. Burns; Bogdan Nicolae (CoRR, 2023)

Efficient Communication in Federated Learning Using Floating-Point Lossy Compression. - Grant Wilkins; Sheng Di; Jon C. Calhoun; Kibaek Kim; Robert Underwood; Richard Mortier; Franck Cappello (CoRR, 2023)

SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors. - Xin Liang 001; Kai Zhao 008; Sheng Di; Sihuan Li; Robert Underwood; Ali Murat Gok; Jiannan Tian; Junjing Deng; Jon C. Calhoun; Dingwen Tao; Zizhong Chen; Franck Cappello (IEEE Trans. Big Data, 2023)

Black-box statistical prediction of lossy compression ratios for scientific data. - Robert Underwood; Julie Bessac; David Krasowska; Jon C. Calhoun; Sheng Di; Franck Cappello (Int. J. High Perform. Comput. Appl., 2023)

DataStates-LLM: Lazy Asynchronous Checkpointing for Large Language Models. - Avinash Maurya; Robert Underwood; M. Mustafa Rafique; Franck Cappello; Bogdan Nicolae (HPDC, 2024)

EvoStore: Towards Scalable Storage of Evolving Learning Models. - Robert Underwood; Meghana Madhyastha; Randal C. Burns; Bogdan Nicolae (HPDC, 2024)

FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications. - Grant Wilkins; Sheng Di; Jon C. Calhoun; Zilinghan Li; Kibaek Kim; Robert Underwood; Richard Mortier; Franck Cappello (ICDCS, 2024)

CliZ: Optimizing Lossy Compression for Climate Datasets with Adaptive Fine-tuned Data Prediction. - Zizhe Jian; Sheng Di; Jinyang Liu 003; Kai Zhao 008; Xin Liang 001; Haiying Xu; Robert Underwood; Shixun Wu; Jiajun Huang 001; Zizhong Chen; Franck Cappello (IPDPS, 2024)

cuSZ-i: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation. - Jinyang Liu 003; Jiannan Tian; Shixun Wu; Sheng Di; Boyuan Zhang 002; Robert Underwood; Yafan Huang; Jiajun Huang 001; Kai Zhao 008; Guanpeng Li; Dingwen Tao; Zizhong Chen; et al. (SC, 2024)

SZOps: Scalar Operations for Error-bounded Lossy Compressor for Scientific Data. - Tripti Agarwal; Sheng Di; Jiajun Huang 001; Yafan Huang; Ganesh Gopalakrishnan; Robert Underwood; Kai Zhao 008; Xin Liang 001; Guanpeng Li; Franck Cappello (SC Workshops, 2024)

FRSZ2 for In-Register Block Compression Inside GMRES on GPUs. - Thomas Grützmacher; Robert Underwood; Sheng Di; Franck Cappello; Hartwig Anzt (SC Workshops, 2024)

Understanding The Effectiveness of Lossy Compression in Machine Learning Training Sets. - Robert Underwood; Jon C. Calhoun; Sheng Di; Franck Cappello (CoRR, 2024)

A Survey on Error-Bounded Lossy Compression for Scientific Datasets. - Sheng Di; Jinyang Liu 003; Kai Zhao 008; Xin Liang 001; Robert Underwood; Zhaorui Zhang; Milan Shah; Yafan Huang; Jiajun Huang 001; Xiaodong Yu 001; Congrong Ren; Hanqi Guo 001; et al. (CoRR, 2024)

HoSZp: An Efficient Homomorphic Error-bounded Lossy Compressor for Scientific Data. - Tripti Agarwal; Sheng Di; Jiajun Huang 001; Yafan Huang; Ganesh Gopalakrishnan; Robert Underwood; Kai Zhao 008; Xin Liang 001; Guanpeng Li; Franck Cappello (CoRR, 2024)

LSHBloom: Memory-efficient, Extreme-scale Document Deduplication. - Arham Khan; Robert Underwood; Carlo Siebenschuh; Yadu N. Babuji; Aswathy Ajith; Kyle Hippe; Ozan Gökdemir; Alexander Brace; Kyle Chard; Ian T. Foster (CoRR, 2024)

Sensitivity and Impacts on Parallel Compression of Prediction of Lossy Compression Ratios for Scientific Data. - Alexandra Poulos; Robert Underwood; Jon C. Calhoun; Sheng Di; Franck Cappello (IPDPS, 2025)

A Memory-Efficient and Computation-Balanced Lossy Compressor on Wafer-Scale Engine. - Shihui Song; Robert Underwood; Sheng Di; Yafan Huang; Peng Jiang 004; Franck Cappello (IPDPS, 2025)

To Compress or Not to Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O. - Grant Wilkins; Sheng Di; Jon C. Calhoun; Robert Underwood; Franck Cappello (IPDPS, 2025)

Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing. - Franck Cappello; Mario C. Acosta; Emmanuel Agullo; Hartwig Anzt; Jon Calhoun 001; Sheng Di; Luc Giraud; Thomas Grützmacher; Sian Jin; Kentaro Sano; Kento Sato; Amarjit Singh; et al. (Future Gener. Comput. Syst., 2025)

EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants. - Franck Cappello; Sandeep Madireddy; Robert Underwood; Neil Getty; Nicholas Lee-Ping Chia; Nesar Ramachandra; Josh Nguyen; Murat Keçeli; Tanwi Mallick; Zilinghan Li; Marieme Ngom; Chenhui Zhang; et al. (CoRR, 2025)

LCP: Enhancing Scientific Data Management with Lossy Compression for Particles. - Longtao Zhang; Ruoyu Li; Congrong Ren; Sheng Di; Jinyang Liu 003; Jiajun Huang 001; Robert Underwood; Pascal Grosset; Dingwen Tao; Xin Liang 001; Hanqi Guo 001; Franck Cappello; et al. (Proc. ACM Manag. Data, 2025)

Lossy Compression of Scientific Data: Applications Constrains and Requirements. - Franck Cappello; Allison H. Baker; Ebru Bozda; Martin Burtscher; Kyle Chard; Sheng Di; Paul Christopher O. Grady; Peng Jiang 004; Shaomeng Li; Erik Lindahl; Peter Lindstrom 001; Magnus Lundborg; et al. (CoRR, 2025)

AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine. - Carlo Siebenschuh; Kyle Hippe; Ozan Gökdemir; Alexander Brace; Arham Khan; Khalid Hossain; Yadu N. Babuji; Nicholas Chia; Venkatram Vishwanath; Rick Stevens; Arvind Ramanathan; Ian T. Foster; et al. (CoRR, 2025)

A Survey on Error-Bounded Lossy Compression for Scientific Datasets. - Sheng Di; Jinyang Liu 003; Kai Zhao 008; Xin Liang 001; Robert Underwood; Zhaorui Zhang; Milan Shah; Yafan Huang; Jiajun Huang 001; Xiaodong Yu 001; Congrong Ren; Hanqi Guo 001; et al. (ACM Comput. Surv., 2025)