He received $500,000 for his project titled “Spectral Reduction of Large Graphs and Circuit Networks.” In this project, Zhuo will investigate a scalable yet unified spectral graph reduction approach that allows reducing large-scale, real-world directed and undirected graphs with guaranteed preservation of the original graph spectra. The project will significantly advance the state of the arts in spectral graph theory, electronic design automation (EDA), data mining, machine learning, and scientific computing, leading to the development of much faster numerical and graph-based algorithms. This project will support two Ph.D. research assistants.
Feng also received a budget of $181,823 for his project titled “Scalable Spectral Sparsification of Graph Laplacians and Integrated Circuits.” In this project, Zhuo will develop scalable methods for design simplifications of nanoscale integrated circuits (ICs). This is to be achieved by extending the associated spectral graph sparsification framework to handle Laplacian-like matrices derived from general nonlinear IC modeling and simulation problems. The results from this research may prove to be key to the development of highly scalable computer-aided design algorithms for modeling, simulation, design, optimization, as well as verification of future nanoscale ICs that can easily involve multi-billions of circuit components. The project will support two research assistants for one year.
In appreciation of Zhuo’s excellent funding record, the ECE department will award $2,000 to his project team.