Conferences and Journals
M. Zafari, D. Pandey and R. Doost-Mohammady, "An Analytical and Experimental Study of Distributed Uplink Beamforming in the Presence of Carrier Frequency Offsets," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2026.3656108.
Zhongzhi Yu, Zheng Wang, Yonggan Fu, Huihong Shi, Khalid Shaikh, Yingyan (Celine) Lin, “Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration”, the Forty-first International Conference on Machine Learning (ICML 2024)
Yongan Zhang, Yonggan Fu, Zhongzhi Yu, Kevin Zhao, Cheng Wan, Chaojian Li, Yingyan (Celine) Lin, “INVITED: Data4AIGChip: An Automated Data Generation and Validation Flow for LLM-assisted Hardware Design”, Design Automation Conference 2023 (DAC 2024).
N. A. Mohamed and J. R. Cavallaro, "A Unified Parallel CORDIC-Based Hardware Architecture for LSTM Network Acceleration," in IEEE Transactions on Computers, vol. 72, no. 10, pp. 2752-2766, Oct. 2023, doi: 10.1109/TC.2023.3268400.
T. Keller and J. R. Cavallaro, "On the Design of Reconfigurable Edge Devices for RF Fingerprint Identification (RED-RFFI) for IoT Systems," 2023 57th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2023, pp. 739-746, doi: 10.1109/IEEECONF59524.2023.10476864.
Q. An, M. Zafari, C. Dick, S. Segarra, A. Sabharwal and R. Doost-Mohammady, "ML-Based Feedback-Free Adaptive MCS Selection for Massive Multi-User MIMO," 2023 57th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2023, pp. 157-161, doi: 10.1109/IEEECONF59524.2023.10476866.
Chaojian Li, Kyungmin Kim, Bichen Wu, Peizhao Zhang, Hang Zhang, Xiaoliang Dai, Peter Vajda, Yingyan (Celine) Lin, “An Investigation on Hardware-Aware Vision Transformer Scaling”, ACM Transactions on Embedded Computing Systems 2023 (TECS 2023).
Yonggan Fu, Yongan Zhang, Zhongzhi Yu, Sixu Li, Zhifan Ye, Chaojian Li, Cheng Wan, Yingyan (Celine) Lin, "GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models", The IEEE/ACM International Conference on Computer-Aided Design 2023 (ICCAD 2023).
N. Mohamed, J. R. Cavallaro, "A Unified Parallel CORDIC-based Hardware Architecture for LSTM Network Acceleration," IEEE Transactions on Computers, (Early Access April 2023) vol. 72, no. 10, pp. 2752-2766, Oct. 2023, doi: 10.1109/TC.2023.3268400.
N. Mohamed, J. R. Cavallaro, “Design and Implementation of an FPGA-Based DNN Architecture for Real-time Outlier Detection,” Springer Journal of Signal Processing Systems, (Online January 2023) doi: 10.1007/s11265-023-01835-1.
Q. An, S. Segarra, C. Dick, A. Sabharwal, and R. Doost-Mohammady, "A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks," in IEEE Transactions on Machine Learning in Communications and Networking, doi: 10.1109/TMLCN.2023.3313988.
Jiarong Xing, Junzhi Gong, Xenofon Foukas, Anuj Kalia , Daehyeok Kim, Manikanta Kotaru, “Enabling Resilience in Virtualized RANs with Atlas” International Conference on Mobile Computing and Networking (Mobicom 2023)
T. Keller, J. R. Cavallaro, “On the Design of Reconfigurable Transformer Model Accelerators for IoT Wireless Systems,” 2023 IEEE 57th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, (October-November 2023), (Invited from abstract July 14, 2023).
S. Sharan, W. Zheng*, K. Hsu, J. Xiong, A. Chen, and Z. Wang, “Symbolic Distillation for Learned TCP Congestion Control”, Advances in Neural Information Processing Systems (NeurIPS), 2022.
Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye, Zhongzhi Yu, Cheng-I Lai, Yingyan Lin, "Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing", Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022).
Chaojian Li, Sixu Li, Yang Zhao, Wenbo Zhu, Yingyan Lin, “RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering”, The IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2022).
Rahman Doost-Mohammady, Mehdi Zafari, and Ashutosh Sabharwal. "Robustness of Distributed Multi-User Beamforming: An Experimental Evaluation." In 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2022.
Chance Tarver, Alexios Balatsoukas-Stimming, Christoph Studer, and Joseph R. Cavallaro. "OFDM-based beam-oriented digital predistortion for massive MIMO." In 2021 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2021.
Chance Tarver, Alexios Balalsoukas-Slimining, Christoph Studer, and Joseph R. Cavallaro. "Virtual DPD Neural Network Predistortion for OFDM-based MU-Massive MIMO." In 2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2021.
Nadya Mohamed, Joseph R. Cavallaro, "Design and Implementation of Autoencoder-LSTM Accelerator for Edge Outlier Detection," In IEEE International Workshop on Signal Processing Systems (SiPS), October 2021, pp. 134-139, doi: https://doi.org/10.1109/SiPS52927.2021.00032
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Yingyan Lin, “HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark”, The 9th International Conference on Learning Representations 2021 (ICLR 2021).
Yonggan Fu, Yongan Zhang, Chaojian Li, Zhongzhi Yu, Yingyan Lin, “A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning”, The 58th Design Automation Conference 2021 (DAC 2021).
Mengquan Li, Zhongzhi Yu, Yongan Zhang, Yonggan Fu, Yingyan Lin, “O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed”, The 40th IEEE/ACM International Conference on Computer Aided Design 2021 (ICCAD 2021).
Yiming Qiu, Hongyi Liu, Thomas Anderson, Yingyan Lin, Ang Chen, “Toward Reconfigurable Kernel Datapaths with Learned Optimizations”, The 18th Workshop on Hot Topics in Operating Systems (HotOS 2021)