SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning. - Sixing Yu; Phuong Nguyen; Waqwoya Abebe; Ali Anwar 001; Ali Jannesari (CoRR, 2021)

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Federated Learning. - Sixing Yu; Phuong Nguyen; Waqwoya Abebe; Wei Qian; Ali Anwar 001; Ali Jannesari (SC, 2022)

Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search. - Sixing Yu; Phuong Nguyen; Waqwoya Abebe; Justin Stanley; J. Pablo Muñoz; Ali Jannesari (CoRR, 2022)

Addressing Data Heterogeneity in Decentralized Learning via Topological Pre-processing. - Waqwoya Abebe; Ali Jannesari (CoRR, 2022)

Optimizing Decentralized Learning with Local Heterogeneity using Topology Morphing and Clustering. - Waqwoya Abebe; Ali Jannesari (CCGrid, 2023)

LEFL: Low Entropy Client Sampling in Federated Learning. - Waqwoya Abebe; Juan Pablo Muñoz; Ali Jannesari (CoRR, 2023)

Improving Federated Learning Through Low-Entropy Client Sampling Based on Learned High-Level Features. - Waqwoya Abebe; Pablo Munoz; Ali Jannesari (CLOUD, 2024)

The Landscape and Challenges of HPC Research and LLMs. - Le Chen; Nesreen K. Ahmed; Akash Dutta; Arijit Bhattacharjee; Sixing Yu; Quazi Ishtiaque Mahmud; Waqwoya Abebe; Hung Phan; Aishwarya Sarkar; Branden Butler; Niranjan Hasabnis; Gal Oren 001; et al. (CoRR, 2024)

SAM-I-Am: Semantic Boosting for Zero-shot Atomic-Scale Electron Micrograph Segmentation. - Waqwoya Abebe; Jan Strube 001; Luanzheng Guo; Nathan R. Tallent; Oceane Bel; Steven R. Spurgeon; Christina Doty; Ali Jannesari (CoRR, 2024)

Mitigating effects of data heterogeneity in decentralized learning and addressing challenges of adapting foundation models. - Waqwoya Abebe (2025)

SuperSAM: Crafting a SAM Supernetwork via Structured Pruning and Unstructured Parameter Prioritization. - Waqwoya Abebe; Sadegh Jafari; Sixing Yu; Akash Dutta; Jan Strube 001; Nathan R. Tallent; Luanzheng Guo; J. Pablo Muñoz; Ali Jannesari (CoRR, 2025)