Poster: Data-Aware Edge Sampling for Aggregate Query Approximation. - Joel Wolfrath; Abhishek Chandra (SEC, 2020)

Accelerated Training via Device Similarity in Federated Learning. - Yuanli Wang; Joel Wolfrath; Nikhil Sreekumar; Dhruv Kumar 001; Abhishek Chandra (EdgeSys@EuroSys, 2021)

Towards WAN-aware join sampling over geo-distributed data. - Dhruv Kumar 001; Joel Wolfrath; Abhishek Chandra; Ramesh K. Sitaraman (EdgeSys@EuroSys, 2022)

Efficient Transmission and Reconstruction of Dependent Data Streams via Edge Sampling. - Joel Wolfrath; Abhishek Chandra (IC2E, 2022)

HACCS: Heterogeneity-Aware Clustered Client Selection for Accelerated Federated Learning. - Joel Wolfrath; Nikhil Sreekumar; Dhruv Kumar 001; Yuanli Wang; Abhishek Chandra (IPDPS, 2022)

Plexus: Optimizing Join Approximation for Geo-Distributed Data Analytics. - Joel Wolfrath; Abhishek Chandra (SoCC, 2023)

Leveraging Multi-Modal Data for Efficient Edge Inference Serving. - Joel Wolfrath; Anirudh Achanta; Abhishek Chandra (CCGrid, 2024)

A Biased Estimator for MinMax Sampling and Distributed Aggregation. - Joel Wolfrath; Abhishek Chandra (CoRR, 2024)

Stronger Baseline Models - A Key Requirement for Aligning Machine Learning Research with Clinical Utility. - Nathan Wolfrath; Joel Wolfrath; Hengrui Hu; Anjishnu Banerjee; Anai N. Kothari (CoRR, 2024)

SneakPeek: Data-Aware Model Selection and Scheduling for Inference Serving on the Edge. - Joel Wolfrath; Daniel Frink; Abhishek Chandra (CoRR, 2025)