| 2025 | CVPR | Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training. | Lexington Allen Whalen, Zhenbang Du, Haoran You, Chaojian Li, Sixu Li, Yingyan Lin |
| 2024 | ECCV | Omni-Recon: Harnessing Image-Based Rendering for General-Purpose Neural Radiance Fields. | Yonggan Fu, Huaizhi Qu, Zhifan Ye, Chaojian Li, Kevin Zhao, Yingyan Lin |
| 2023 | HPCA | ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention. | Jyotikrishna Dass, Shang Wu, Huihong Shi, Chaojian Li, Zhifan Ye, Zhongfeng Wang, Yingyan Lin |
| 2023 | HPCA | ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design. | Haoran You, Zhanyi Sun, Huihong Shi, Zhongzhi Yu, Yang Zhao, Yongan Zhang, Chaojian Li, Baopu Li, Yingyan Lin |
| 2023 | ISCA | Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design. | Yonggan Fu, Zhifan Ye, Jiayi Yuan, Shunyao Zhang, Sixu Li, Haoran You, Yingyan Lin |
| 2022 | AAAI | Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets. | Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin |
| 2022 | AAAI | MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation. | Zhongzhi Yu, Yonggan Fu, Sicheng Li, Chaojian Li, Yingyan Lin |
| 2022 | DAC | Contrastive quant: quantization makes stronger contrastive learning. | Yonggan Fu, Qixuan Yu, Meng Li, Xu Ouyang, Vikas Chandra, Yingyan Lin |
| 2022 | ECCV | INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors. | Chaojian Li, Bichen Wu, Albert Pumarola, Peizhao Zhang, Yingyan Lin, Peter Vajda |
| 2022 | ECCV | SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning. | Haoran You, Baopu Li, Zhanyi Sun, Xu Ouyang, Yingyan Lin |
| 2022 | FCCM | FCsN: A FPGA-Centric SmartNIC Framework for Neural Networks. | Anqi Guo, Tong Geng, Yongan Zhang, Pouya Haghi, Chunshu Wu, Cheng Tan, Yingyan Lin, Ang Li, Martin C. Herbordt |
| 2022 | FPL | A Framework for Neural Network Inference on FPGA-Centric SmartNICs. | Anqi Guo, Tong Geng, Yongan Zhang, Pouya Haghi, Chunshu Wu, Cheng Tan, Yingyan Lin, Ang Li, Martin C. Herbordt |
| 2022 | HPCA | GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design. | Haoran You, Tong Geng, Yongan Zhang, Ang Li, Yingyan Lin |
| 2022 | ICCAD | RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering. | Chaojian Li, Sixu Li, Yang Zhao, Wenbo Zhu, Yingyan Lin |
| 2022 | ICCAD | NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks. | Huihong Shi, Haoran You, Yang Zhao, Zhongfeng Wang, Yingyan Lin |
| 2022 | ICLR | Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations? | Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin |
| 2022 | ICLR | PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. | Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin |
| 2022 | ICML | DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks. | Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin |
| 2022 | ICML | ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks. | Haoran You, Baopu Li, Huihong Shi, Yonggan Fu, Yingyan Lin |
| 2022 | ISCA | EyeCoD: eye tracking system acceleration via flatcam-based algorithm & accelerator co-design. | Haoran You, Cheng Wan, Yang Zhao, Zhongzhi Yu, Yonggan Fu, Jiayi Yuan, Shang Wu, Shunyao Zhang, Yongan Zhang, Chaojian Li, Vivek Boominathan, Ashok Veeraraghavan, Ziyun Li, Yingyan Lin |
| 2021 | DAC | InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks. | Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang, Chaojian Li, Yongyuan Liang, Mingchao Jiang, Zhangyang Wang, Yingyan Lin |
| 2021 | DAC | A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning. | Yonggan Fu, Yongan Zhang, Chaojian Li, Zhongzhi Yu, Yingyan Lin |
| 2021 | HotOS | Toward reconfigurable kernel datapaths with learned optimizations. | Yiming Qiu, Hongyi Liu, Thomas E. Anderson, Yingyan Lin, Ang Chen |
| 2021 | ICCAD | O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed. | Mengquan Li, Zhongzhi Yu, Yongan Zhang, Yonggan Fu, Yingyan Lin |
| 2021 | ICCAD | G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency. | Yongan Zhang, Haoran You, Yonggan Fu, Tong Geng, Ang Li, Yingyan Lin |
| 2021 | ICCV | SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam. | Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin |
| 2021 | ICLR | CPT: Efficient Deep Neural Network Training via Cyclic Precision. | Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin |
| 2021 | ICLR | HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. | Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin |
| 2021 | ICML | Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference. | Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin |
| 2021 | ICML | Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. | Yonggan Fu, Yongan Zhang, Yang Zhang, David D. Cox, Yingyan Lin |
| 2021 | ISLPED | DIAN: Differentiable Accelerator-Network Co-Search Towards Maximal DNN Efficiency. | Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, Meng Li, Vikas Chandra, Yingyan Lin |
| 2021 | MICRO | 2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency. | Yonggan Fu, Yang Zhao, Qixuan Yu, Chaojian Li, Yingyan Lin |
| 2021 | MICRO | I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization. | Tong Geng, Chunshu Wu, Yongan Zhang, Cheng Tan, Chenhao Xie, Haoran You, Martin C. Herbordt, Yingyan Lin, Ang Li |
| 2020 | AAAI | Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference. | Jianghao Shen, Yue Wang, Pengfei Xu, Yonggan Fu, Zhangyang Wang, Yingyan Lin |
| 2020 | ECCV | HALO: Hardware-Aware Learning to Optimize. | Chaojian Li, Tianlong Chen, Haoran You, Zhangyang Wang, Yingyan Lin |
| 2020 | FPGA | AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs. | Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, Yingyan Lin |
| 2020 | ICASSP | DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures. | Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, Yingyan Lin |
| 2020 | ICLR | Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. | Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin |
| 2020 | ICML | AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks. | Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang |
| 2020 | ISCA | Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain. | Weitao Li, Pengfei Xu, Yang Zhao, Haitong Li, Yuan Xie, Yingyan Lin |
| 2020 | ISCA | SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. | Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin |
| 2020 | ISCAS | A New MRAM-Based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision. | Hongjie Wang, Yang Zhao, Chaojian Li, Yue Wang, Yingyan Lin |
| 2019 | ISCAS | Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means. | Pengfei Xu, Yue Wang, Yang Zhao, Yingyan Lin |
| 2018 | ICML | Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions. | Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin |
| 2018 | ISCAS | Energy-efficient Convolutional Neural Networks via Statistical Error Compensated Near Threshold Computing. | Yingyan Lin, Joseph R. Cavallaro |
| 2018 | Mobisys | On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework. | Sicong Liu, Yingyan Lin, Zimu Zhou, Kaiming Nan, Hui Liu, Junzhao Du |
| 2018 | Mobisys | ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes. | Riccardo Petrolo, Yingyan Lin, Edward W. Knightly |
| 2017 | ISCAS | PredictiveNet: An energy-efficient convolutional neural network via zero prediction. | Yingyan Lin, Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag |
| 2012 | ICASSP | A fully automated technique for constructing FSM abstractions of non-ideal latches in communication systems. | Aadithya V. Karthik, Yingyan Lin, Chenjie Gu, Aolin Xu, Jaijeet S. Roychowdhury, Naresh R. Shanbhag |