An infrastructure for automating large-scale performance studies and data processing. - Deepal Jayasinghe; Josh Kimball; Tao Zhu; Siddharth Choudhary; Calton Pu (IEEE BigData, 2013)

An automated approach to create, store, and analyze large-scale experimental data in clouds. - Deepal Jayasinghe; Josh Kimball; Siddharth Choudhary; Tao Zhu; Calton Pu (IRI, 2013)

IO Performance Interference among Consolidated n-Tier Applications: Sharing Is Better Than Isolation for Disks. - Chien-An Lai; Qingyang Wang 001; Josh Kimball; Jack Li 001; Junhee Park; Calton Pu (IEEE CLOUD, 2014)

milliScope: A Fine-Grained Monitoring Framework for Performance Debugging of n-Tier Web Services. - Chien-An Lai; Josh Kimball; Tao Zhu; Qingyang Wang 001; Calton Pu (ICDCS, 2017)

The Millibottleneck Theory of Performance Bugs, and Its Experimental Verification. - Calton Pu; Joshua Kimball; Chien-An Lai; Tao Zhu; Jack Li 001; Junhee Park; Qingyang Wang 001; Deepal Jayasinghe; PengCheng Xiong; Simon Malkowski; Qinyi Wu; Gueyoung Jung; et al. (ICDCS, 2017)

Limitations of Load Balancing Mechanisms for N-Tier Systems in the Presence of Millibottlenecks. - Tao Zhu; Jack Li 001; Josh Kimball; Junhee Park; Chien-An Lai; Calton Pu; Qingyang Wang 001 (ICDCS, 2017)

A Method and Tool for Automated Induction of Relations from Quantitative Performance Logs. - Joshua Kimball; Calton Pu (CLOUD, 2019)

Systematic Construction, Execution, and Reproduction of Complex Performance Benchmarks. - Rodrigo Alves Lima; Joshua Kimball; João Eduardo Ferreira; Calton Pu (CLOUD, 2019)

Wise Toolkit: Enabling Microservice-Based System Performance Experiments. - Rodrigo Alves Lima; Joshua Kimball; João Eduardo Ferreira; Calton Pu (CLOUD, 2020)

PerfDB: A Data Management System for Fine-Grained Performance Anomaly Detection. - Joshua Kimball; Rodrigo Alves Lima; Yasuhiko Kanemasa; Calton Pu (CIC, 2020)

Finding Performance Patterns from Logs with High Confidence. - Joshua Kimball; Rodrigo Alves Lima; Calton Pu (ICWS, 2020)

PerfML: Smart Management of Complex Performance Data and Analytics. - Joshua Kimball; Rodrigo Alves Lima; Abhijit Suprem; Qingyang Wang 001; Yasuhiko Kanemasa; Calton Pu (CogMI, 2021)

A Functional Model and Analysis of Next Generation Malware Attacks and Defenses. - Calton Pu; Qingyang Wang 001; Yasuhiko Kanemasa; Rodrigo Alves Lima; Joshua Kimball; Shungeng Zhang; Jianshu Liu; Xuhang Gu (TPS-ISA, 2021)

PerfDB + PerlML: Enabling Big Data-Driven Research On Fine-Grained Performance Phenomena. - Joshua Kimball (2021)

LIVE-ITS: LSH-based Interactive Visualization Explorer for Large-Scale Incomplete Time Series. - Hongjie Chen 003; Aaron D. Beachnau; Panos Thomas; Pranav Maneriker; Josh Kimball; Ryan A. Rossi (IEEE Big Data, 2024)

Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning. - Tiansheng Huang; Gautam Bhattacharya; Pratik Joshi; Josh Kimball; Ling Liu 001 (CoRR, 2024)

A Quantitative Metric Selection Approach for Time-series Forecasting Foundation Models. - Hongjie Chen 003; Akshay Mehra; Josh Kimball; Sungchul Kim (ICASSP, 2025)

Model-agnostic Coreset Selection via LLM-based Concept Bottlenecks. - Akshay Mehra; Trisha Mittal; Subhadra Gopalakrishnan; Joshua Kimball (CoRR, 2025)

Measuring Time-Series Dataset Similarity using Wasserstein Distance. - Hongjie Chen 003; Akshay Mehra; Josh Kimball; Ryan A. Rossi (CoRR, 2025)