Caiwen Ding
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
88
Venues
33
Active years
2016–2026
Best venue rank
A*
Where they publish
- A*DAC10 papers
- AICCAD9 papers
- CICCD6 papers
- ADATE5 papers
- BASPDAC4 papers
- AFPGA4 papers
- A*IJCAI4 papers
- A*CVPR3 papers
- BIJCNN3 papers
- AICS3 papers
- A*ASPLOS3 papers
- ASC3 papers
- A*EMNLP3 papers
- AISLPED3 papers
- A*ACL2 papers
- A*ICLR2 papers
- A*HPCA2 papers
- A*MICRO2 papers
- CISCAS2 papers
- A*ISCA2 papers
- A*WWW1 paper
- A*ECCV1 paper
- CHPCC1 paper
- A*ICCV1 paper
- A*ICML1 paper
- A*ICRA1 paper
- BISPASS1 paper
- A*SP1 paper
- A*CCS1 paper
- MulticonferenceICASSP1 paper
- AMICCAI1 paper
- A*AAAI1 paper
- BICPR1 paper
Papers
88 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation. | Le Chen, Nuo Xu, Winson Chen, Bin Lei, Pei-Hung Lin, Dunzhi Zhou, Rajeev Thakur, Caiwen Ding, Ali Jannesari, Chunhua Liao |
| 2026 | ASPDAC | HDLxGraph: Bridging Large Language Models and HDL Repositories via HDL Graph Databases. | Pingqing Zheng, Jiayin Qin, Fuqi Zhang, Niraj Chitla, Zishen Wan, Shang Wu, Yu Kevin Cao, Caiwen Ding, Yang Katie Zhao |
| 2025 | CVPR | Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack. | Nicole Meng, Caleb Manicke, Ronak Sahu, Caiwen Ding, Yingjie Lao |
| 2025 | FPGA | HEDWIG: Homomorphic Encryption Accelerator Design Using BFV-HPS With HiGh-Speed Fixed-Point Approximation. | Antian Wang, Weihang Tan, Zhenyu Xu, Tao Wei, Caiwen Ding, Keshab K. Parhi, Yingjie Lao |
| 2025 | ICCAD | MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging. | Jinwei Tang, Jiayin Qin, Nuo Xu, Pragnya Sudershan Nalla, Yu Cao, Yang Katie Zhao, Caiwen Ding |
| 2025 | ICCAD | GROOT: Graph Edge Re-growth and Partitioning for the Verification of Large Designs in Logic Synthesis. | Kiran Thorat, Hongwu Peng, Yuebo Luo, Xi Xie, Shaoyi Huang, Amit Hasan, Jiahui Zhao, Yingjie Li, Zhijie Shi, Cunxi Yu, Caiwen Ding |
| 2025 | ICLR | RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs. | Xi Xie, Yuebo Luo, Hongwu Peng, Caiwen Ding |
| 2025 | IJCNN | TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs. | Kiran Thorat, Amit Hasan, Caiwen Ding, Zhijie Shi |
| 2025 | ICS | Graph Convolutional Network Acceleration Using Adiabatic Superconductor Josephson Devices. | Zhengang Li, Hongwu Peng, Xuan Shen, Masoud Zabihi, Xi Xie, Geng Yuan, Yanzhi Wang, Olivia Chen, Caiwen Ding |
| 2025 | ICS | DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs. | Yuebo Luo, Shiyang Li, Junran Tao, Kiran Gautam Thorat, Xi Xie, Hongwu Peng, Nuo Xu, Caiwen Ding, Shaoyi Huang |
| 2025 | WWW | RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models. | Can Jin, Hongwu Peng, Anxiang Zhang, Nuo Chen, Jiahui Zhao, Xi Xie, Kuangzheng Li, Shuya Feng, Kai Zhong, Caiwen Ding, Dimitris N. Metaxas |
| 2024 | ASPLOS | MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. | Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding |
| 2024 | DATE | SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits. | Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang |
| 2024 | ECCV | AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation. | Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu |
| 2024 | HPCA | PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration. | Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan |
| 2024 | ICCAD | AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing. | Tong Zhou, Jiahui Zhao, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding, Xiaolin Xu |
| 2024 | ICS | Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. | Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang |
| 2023 | CVPR | You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. | Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu |
| 2023 | CVPR | Accelerating Dataset Distillation via Model Augmentation. | Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu |
| 2023 | DAC | Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. | Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang |
| 2023 | DAC | Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. | Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding |
| 2023 | DAC | Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. | Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding |
| 2023 | DAC | Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning. | Zhuo Liu, Yunan Yang, Zhenyu Pan, Anshujit Sharma, Amit Hasan, Caiwen Ding, Ang Li, Michael C. Huang, Tong Geng |
| 2023 | DAC | PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. | Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding |
| 2023 | DAC | Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. | Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding |
| 2023 | HPCC | Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. | Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan |
| 2023 | ICCAD | Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. | Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding |
| 2023 | ICCV | AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. | Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding |
| 2023 | ICML | SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference. | Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen |
| 2023 | IJCAI | Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models. | Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding |
| 2023 | ICRA | Uncertainty Quantification of Collaborative Detection for Self-Driving. | Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao |
| 2023 | ISPASS | MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration. | Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan |
| 2023 | MICRO | AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. | Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu |
| 2023 | SC | TANGO: re-thinking quantization for graph neural network training on GPUs. | Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu |
| 2023 | SP | Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. | Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding |
| 2022 | ACL | Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. | Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding |
| 2022 | CCS | Poster: Cryptographic Inferences for Video Deep Neural Networks. | Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong |
| 2022 | DAC | A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. | Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding |
| 2022 | DATE | Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. | Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie |
| 2022 | ICCAD | All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. | Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang |
| 2022 | ICCAD | EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System. | Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie |
| 2022 | ICCD | Towards Real-Time Temporal Graph Learning. | Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan |
| 2022 | ICCD | On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond. | Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang |
| 2022 | ICCD | CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. | Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng |
| 2022 | ICCD | Towards Sparsification of Graph Neural Networks. | Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding |
| 2022 | IJCNN | Variance of the Gradient Also Matters: Privacy Leakage from Gradients. | Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran |
| 2022 | ISCAS | Reliability Improvement in RRAM-based DNN for Edge Computing. | Md. Oli-Uz-Zaman, Saleh Ahmad Khan, Geng Yuan, Yanzhi Wang, Zhiheng Liao, Jingyan Fu, Caiwen Ding, Jinhui Wang |
| 2021 | DAC | Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. | Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding |
| 2021 | DAC | A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. | Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang |
| 2021 | DATE | TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators. | Geng Yuan, Payman Behnam, Yuxuan Cai, Ali Shafiee, Jingyan Fu, Zhiheng Liao, Zhengang Li, Xiaolong Ma, Jieren Deng, Jinhui Wang, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding |
| 2021 | EMNLP | TAG: Gradient Attack on Transformer-based Language Models. | Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding |
| 2021 | EMNLP | A Secure and Efficient Federated Learning Framework for NLP. | Chenghong Wang, Jieren Deng, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding |
| 2021 | ICCAD | 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, Caiwen Ding, Weiwen Jiang, Lei Yang |
| 2021 | ICCAD | Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). | Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding |
| 2021 | ICCAD | Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper). | Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang |
| 2021 | IJCAI | Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation. | Deniz Gurevin, Mikhail A. Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao |
| 2021 | IJCAI | A Compression-Compilation Framework for On-mobile Real-time BERT Applications. | Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang |
| 2021 | IJCAI | Against Membership Inference Attack: Pruning is All You Need. | Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran |
| 2021 | ISCA | FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. | Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding |
| 2021 | SC | E.T.: re-thinking self-attention for transformer models on GPUs. | Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu |
| 2021 | SC | Dr. Top-k: delegate-centric Top-k on GPUs. | Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu |
| 2020 | ASPDAC | Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation. | Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang |
| 2020 | DAC | FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. | Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding |
| 2020 | EMNLP | Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. | Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding |
| 2020 | FPGA | FTDL: An FPGA-tailored Architecture for Deep Learning Systems. | Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding |
| 2020 | ICASSP | Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. | Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin |
| 2020 | ISLPED | FTRANS: energy-efficient acceleration of transformers using FPGA. | Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding |
| 2019 | FPGA | REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs. | Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang |
| 2019 | HPCA | E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs. | Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang |
| 2019 | ISCA | A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology. | Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang |
| 2019 | ISLPED | An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM. | Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang |
| 2019 | MICCAI | Deep Compressed Pneumonia Detection for Low-Power Embedded Devices. | Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang |
| 2018 | AAAI | Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework. | Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin |
| 2018 | ASPLOS | VIBNN: Hardware Acceleration of Bayesian Neural Networks. | Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang |
| 2018 | DATE | FFT-based deep learning deployment in embedded systems. | Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram |
| 2018 | DATE | Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators. | Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang |
| 2018 | FPGA | C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs. | Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang, Yun Liang |
| 2018 | ICLR | Efficient Recurrent Neural Networks using Structured Matrices in FPGAs. | Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang |
| 2018 | ICPR | Learning Topics Using Semantic Locality. | Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu |
| 2017 | ASPDAC | Algorithm accelerations for luminescent solar concentrator-enhanced reconfigurable onboard photovoltaic system. | Caiwen Ding, Ji Li, Weiwei Zheng, Naehyuck Chang, Xue Lin, Yanzhi Wang |
| 2017 | ASPDAC | Towards acceleration of deep convolutional neural networks using stochastic computing. | Ji Li, Ao Ren, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang |
| 2017 | ASPLOS | SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. | Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, Bo Yuan |
| 2017 | IJCNN | Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks. | Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang |
| 2017 | ISLPED | Reconfigurable thermoelectric generators for vehicle radiators energy harvesting. | Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Jaemin Kim, Xue Lin, Yanzhi Wang, Naehyuck Chang |
| 2017 | MICRO | CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices. | Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan |
| 2016 | ICCD | Dynamic converter reconfiguration for near-threshold non-volatile processors using in-door energy harvesting. | Caiwen Ding, Hongjia Li, Jingtong Hu, Yongpan Liu, Yanzhi Wang |
| 2016 | ICCD | Luminescent solar concentrator-based photovoltaic reconfiguration for hybrid and plug-in electric vehicles. | Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Naehyuck Chang, Xue Lin |
| 2016 | ISCAS | Multi-source in-door energy harvesting for non-volatile processors. | Caiwen Ding, Soroush Heidari, Yanzhi Wang, Yongpan Liu, Jingtong Hu |