Novel low-latency, high-resolution and low-cost time synchronisation. - Ali Aghdaei; Seyed Reza Zekavat (IET Wirel. Sens. Syst., 2017)

HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering. - Ali Aghdaei; Zhiqiang Zhao; Zhuo Feng (ICCAD, 2021)

HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering. - Ali Aghdaei; Zhuo Feng (ICCAD, 2022)

inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition. - Ali Aghdaei; Zhuo Feng (DAC, 2024)

SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks. - John Anticev; Ali Aghdaei; Wuxinlin Cheng; Zhuo Feng (DAC, 2024)

SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds. - Wuxinlin Cheng; Chenhui Deng; Ali Aghdaei; Zhiru Zhang; Zhuo Feng (CoRR, 2024)

Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks. - Soumen Sikder Shuvo; Ali Aghdaei; Zhuo Feng (CoRR, 2024)

SHyPar: A Spectral Coarsening Approach to Hypergraph Partitioning. - Hamed Sajadinia; Ali Aghdaei; Zhuo Feng (CoRR, 2024)

dyGRASS: Dynamic Spectral Graph Sparsification via Localized Random Walks on GPUs. - Yihang Yuan; Ali Aghdaei; Zhuo Feng (CoRR, 2025)