HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. - Shaoyi Huang; Shiyang Chen 004; Hongwu Peng; Daniel Manu; Zhenglun Kong; Geng Yuan; Lei Yang 018; Shusen Wang; Hang Liu 001; Caiwen Ding (ACM Great Lakes Symposium on VLSI, 2021)

Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML. - Daniel Manu; Shaoyi Huang; Caiwen Ding; Lei Yang 018 (ACM Great Lakes Symposium on VLSI, 2021)

FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper. - Daniel Manu; Yi Sheng; Junhuan Yang; Jieren Deng; Tong Geng; Ang Li 006; Caiwen Ding; Weiwen Jiang; Lei Yang 018 (ICCAD, 2021)

Seismic Waveform Inversion Capability on Resource-Constrained Edge Devices. - Daniel Manu; Petro Mushidi Tshakwanda; Youzuo Lin; Weiwen Jiang; Lei Yang 018 (J. Imaging, 2022)

Invited Paper: Ground-Based Communication Support for Air Corridors. - Kasun Prabhath; Xiang Sun 001; Sudharman K. Jayaweera; Daniel Manu; Karthik Kakaraparty; Pallav Kumar Sah; Ifana Mahbub; Jaya Sravani Mandapaka; Sudesna Das Rochi; Mahdin Meraz; Kamesh Namuduri (PIMRC, 2023)

Enhancing IoT Security with Asynchronous Federated Learning for Seismic Inversion. - Daniel Manu; Youzuo Lin; Jingjing Yao; Zhirun Li; Xiang Sun 001 (ICC Workshops, 2024)

GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery. - Daniel Manu; Jingjing Yao; Wuji Liu; Xiang Sun 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)