Home Publications Awards & Activities Teaching Projects Team News

Publications

Selected Publications (To see full publications, please go to my Google Scholar page)

Conferences (* equal contribution)

  1. [24’NeurIPS] Bin Lei, Yi Zhang, Shan Zuo, Ali Payani, Caiwen Ding. MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems. 2024 Advances in Neural Information Processing Systems (NeurIPS).
  2. [24’ECCV] Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, and Dongkuan Xu. AdaDiff: Accelerating Diffusion Models through Step-Wise Adaptive Computation. The 18th European Conference on Computer Vision.
  3. [24’ICCAD] Tong Zhou*, Jiahui Zhao*, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding and Xiaolin Xu. AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing. In 2024 IEEE/ACM International Conference On Computer Aided Design (ICCAD).
  4. [24’ICS] 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. Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. In Proceedings of ACM International Conference on Supercomputing (ICS).
  5. [24’ICPE] Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin Barker, Ang Li. Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs (Vision Paper). In proceedings of ACM International Conference on Performance Engineering (ICPE).
  6. [24’ASPLOS] Hongwu Peng*, Xi Xie*, Kaustubh Shivdikar, MD Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David Kaeli, Caiwen Ding. MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. In Proceedings of ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2024. [codes]
  7. [24’HPCA] Deniz Gurevin, Mohsin Shan, Shaoyi Huang, MD Amit Hasan, Caiwen Ding, Omer Khan. PruneGNN: An Optimized Algorithm-Hardware Framework for Graph Neural Network Pruning, In Proc. of IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2024 [codes]
  8. [24’DATE] 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. A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. In Proc. of Design Automation & Test in Europe Conference & Exhibition (DATE), 2024.
  9. [23’NeurIPS] Hongwu Peng*, Ran Ran*, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding. LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. 2023 Advances in Neural Information Processing Systems (NeurIPS).
  10. [23’HPEC] Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao. Creating a Dataset Supporting Translation Between OpenMP Fortran and C++ Code. In 2023 IEEE High Performance Extreme Computing Conference (HPEC). (Outstanding Student Paper Award)
  11. [23’MICRO] Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu. AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. In 2023 IEEE/ACM International Symposium on Microarchitecture (MICRO).
  12. [23’ICCAD] Xi Xie*, Hongwu Peng*, MD Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding. Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. In 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD).
  13. [23’ICCV] 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. AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. In Proceedings of the 2023 International Conference on Computer Vision (ICCV).
  14. [23’SC] Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu. TANGO: Re-Thinking Quantization for Graph Neural Network Training on GPUs. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2023
  15. [23’ICML] Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen. SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference. In Proceedings of the 40th International Conference on Machine Learning (ICML 2023). Acceptance rate: 21.4%.
  16. [23’IJCAI] Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail Bragin, Ji Li, Caiwen Ding. Towards Lossless Head Pruning through Automatic Peer Distillation for Large Language Models. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2023. Acceptance rate: 15%.
  17. [23′Oakland] Ce Feng∗, Nuo Xu∗, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding, Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering, IEEE Symposium on Security and Privacy (IEEE S&P “Oakland”).
  18. [23’DAC] Hongwu Peng*, Shanglin Zhou*, Yukui Luo*, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding, PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
  19. [23’DAC] Shanglin Zhou*, Yingjie Li*, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding, Physics-aware Roughness Optimization for Diffractive Optical Neural Networks, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
  20. [23’CVPR] Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu, You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model, 2023 the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  21. [23’CVPR] Lei Zhang*, Jie Zhang*, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu, Accelerating Dataset Distillation via Model Augmentation, 2023 the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  22. [23’DAC] Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding, Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
  23. [23’DAC] Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen and Caiwen Ding, Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2023.
  24. [23’ISPASS] Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan, Workload Balancing to Unlock Extreme Parallelism for Graph Neural Network Acceleration, In Proceedings of the 2023 International Symposium on Performance Analysis of Systems and Software (ISPASS).
  25. [23’ICRA] Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao, Uncertainty Quantification of Collaborative Detection for Self-Driving, In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA).
  26. [22’IEEE BigData] Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran, Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification, 2022 IEEE International Conference on Big Data (IEEE Big Data).
  27. [22’CCS] Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding and Yuan Hong. Poster: Cryptographic Inferences for Video Deep Neural Networks. In Proceedings of the 29th ACM Conference on Computer and Communications Security (CCS), Los Angles, CA, November 7-11, 2022.
  28. [22’ICCD] Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang. On the Design of Quantum Graph Convolutional Neural Network in the NISQ era and beyond. In the 40th IEEE International Conference on Computer Design (ICCD), 2022. (Special Session)
  29. [22’ICCD] Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan. Towards Real-time Temporal Graph Learning. In the 40th IEEE International Conference on Computer Design (ICCD), 2022. (Special Session)
  30. [22’ICCD] Yixuan Luo*, Payman Behnam*, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng. CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. In the 40th IEEE International Conference on Computer Design (ICCD), 2022. (Special Session)
  31. [22’ICCD] Hongwu Peng*, Deniz Gurevin*, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding. Towards Sparsification of Graph Neural Networks. In the 40th IEEE International Conference on Computer Design (ICCD), 2022. (Special Session)
  32. [22’ICCAD] Sahidul Islam*, Shanglin Zhou*, Ran Ran, Yu-Fang Jin, Wujie Wen, Caiwen Ding, Mimi Xie. EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System. In the 41st International Conference On Computer-Aided Design (ICCAD), 2022.
  33. [22’ICCAD] Yifan Gong, Zheng zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang. All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. In the 41st International Conference On Computer-Aided Design (ICCAD), 2022.
  34. [22’ACL] 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. “Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.” in Proceeding of 60th Annual Meeting of the Association for Computational Linguistics (ACL), main conference, 2022.
  35. [22’DAC] Hongwu Peng*, Shaoyi Huang*, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu and Caiwen Ding, A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2022. (Publicity Paper)
  36. [22’MLSys] Samuel A. Stein, Betis Baheri, Daniel Chen, Ying Mao, Qiang Guan, Ang Li, Shuai Xu, Caiwen Ding, QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity, in Proc. of the Fifth Conference on Machine Learning and Systems (MLSys), 2022. Acceptance rate: 20.6% (51/247).
  37. [22’DATE] Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, and Mimi Xie, Enabling Super-Fast Deep Learning on Tiny Energy-Harvesting IoT Devices, In Proc. of Design Automation & Test in Europe Conference & Exhibition (DATE), 2022.
  38. [21’EMNLP] Jieren Deng*, Yijue Wang*, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, and Caiwen Ding, TAG: Transformer Attack from Gradient, In Findings of ACL Empirical Methods in Natural Language Processing (EMNLP), 2021.
  39. [21’EMNLP] Jieren Deng*, Chenghong Wang*, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran and Caiwen Ding, A Secure and Efficient Federated Learning Framework for NLP, In Proceedings of ACL Empirical Methods in Natural Language Processing (EMNLP), 2021. (Oral)
  40. [21’SC] Shiyang Chen*, Shaoyi Huang*, Santosh Pandey, Bingbing Li, Guang Gao, Long Zheng, Caiwen Ding, Hang Liu, E.T.: Re-Thinking Self-Attention for Transformer Models on GPUs, In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2021.
  41. [21’SC] Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S Li, Hang Liu, Dr.Top-k: Delegate-Centric Top-k Computation on GPUs, In Proceedings of the International Conference for High-Performance Computing, Networking, Storage and Analysis (SC), 2021.
  42. [21’ICCAD] Daniel Manu, Yi Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang, BFL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery, 2021 the 40th International Conference On Computer-Aided Design (ICCAD), 2021. (Special Session)
  43. [21’ICCAD] Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, and Caiwen Ding, Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search, 2021 the 40th International Conference On Computer-Aided Design (ICCAD), 2021. (Special Session)
  44. [21’ICCAD] Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Jinjun Xiong, Yiyu Shi, WeiwenJiang, Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs, 2021 the 40th Inter-national Conference On Computer-Aided Design (ICCAD), 2021. (Invited Paper)
  45. [21’IJCAI] Deniz Gurevin*, Mikhail Bragin*, Caiwen Ding*, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao, Enabling Retrain-free Deep Neural Network Pruning using Surrogate Lagrangian Relaxation. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. Acceptance rate: 13.9% (587/4204)
  46. [21’IJCAI] Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran. Against Membership Inference Attack: Pruning is All You Need. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. Acceptance rate: 13.9% (587/4204)
  47. [21’IJCAI] Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang, “A compression-compilation framework for on-mobile real-time BERT applications”, in Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. (Demonstration Track)
  48. [21’ISCA] Geng Yuan*, Payman Behnam*, Ali Shafiee, Zhengang Li, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Bojnordi, Yanzhi Wang, Caiwen Ding, FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator, In Proceedings of the 46th International Symposium on Computer Architecture (ISCA), 2021.
  49. [21’DAC] Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding, Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
  50. [21’DAC] Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang, A unified DNN weight compression framework using reweighted optimization methods, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2021.
  51. [21’DATE] Geng Yuan*, Payman Behnam*, Yuxuan Cai, Ali Shafiee, Jingyan Fu, Zhiheng Liao, Zhengang Li, Xiaolong Ma, Jieren Deng, Jinhui Wang, Mahdi Bojnordi, Yanzhi Wang, Caiwen Ding, TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators, In Proc. of Design Automation & Test in Europe Conference & Exhibition (DATE), 2021. (Best Paper Award Nomination)
  52. [20’EMNLP]Bingbing Li*, Zhenglun Kong*, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, and Caiwen Ding, Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning, In Findings of ACL Empirical Methods in Natural Language Processing (EMNLP), 2020.
  53. [20’ISLPED] Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu and Caiwen Ding. FTRANS: Energy-Efficient Acceleration of Transformers using FPGA. In Proceedings of ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED),
  54. [20’DAC] Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden So, Caiwen Ding. Ftdl: A tailored FPGA-overlay for deep learning with high scalability. In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2020. (full paper)
  55. [19’ISCA] Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Yoshikawa Nobuyuki, Yanzhi Wang, A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology, In Proceedings of the 46th International Symposium on Computer Architecture (ISCA), 2019. (Acceptance Rate: 17%)
  56. [19’FPGA] Caiwen Ding*, Shuo Wang*, Ning Liu, Kaidi Xu, Yanzhi Wang and Yun Liang, REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs, In Proceedings of the ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2019 (Full paper)
  57. [19’HPCA] Zhe Li*, Caiwen Ding*, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Yanzhi Wang. E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs, In Proc. of IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2019
  58. [18’AAAI] Yanzhi Wang, Caiwen Ding, Gen Yuan, Siyu Liao, Zhe Li, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, and Xue Lin. Towards ultra-high performance and energy efficiency of deep learning systems: an algorithm-hardware co-optimization framework. In Proc. of the 32nd AAAI Conference on Artificial Intelligence (AAAI), Feb. 2018.
  59. [18’ASPLOS] Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang. VIBNN: Hardware Acceleration of Bayesian Neural Networks. In Proceedings of ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2018. (Acceptance Rate: 17.4%)
  60. [18’DATE] Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, and Massoud Pedram. FFT-Based Deep Learning Deployment in Embedded Systems. In Proc. of Design Automation & Testing Europe Conference & Exhibition (DATE), Mar. 2018. (Best Paper Award Nomination)
  61. [17’MICRO] Caiwen Ding, Yanzhi Wang, Siyu Liao, Zhe Li, Yu Bai, et al., “CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices”, in IEEE/ACM International Symposium on Microarchitecture (MICRO), 2017. (Acceptance Rate: 18.6%)
  62. [17’ASPLOS] Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, and Bo Yuan. 2017. SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. In Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS ’17). (acceptance rate: 17.4%)

Journals

  1. [24’IEEE RA-L] Sanbao Su, Songyang Han, YimingLI, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao, Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation, in the IEEE Robotics and Automation Letters (RA-L).
  2. [23’IEEE T-ITS] Songyang Han, Shanglin Zhou, Jiangwei Wang, Lynn Pepin, Caiwen Ding, Jie Fu, Fei Miao. A Multi-Agent Reinforcement Learning Approach For Safe and Efficient Behavior Planning Of Connected Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems (T-ITS 2023). [Impact factor: 9.551]
  3. [23’ACM TODAES] Shanglin Zhou, Mikhail A Bragin, Deniz Gurevin, Lynn Pepin, Fei Miao, Caiwen Ding. Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning. In ACM Transactions on Design Automation of Electronic Systems (TODAES 2023).
  4. [23’IEEE CAL] Deniz Gurevin, Caiwen Ding, Omer Khan. Exploiting Intrinsic Redundancies in Dynamic Graph Neural Networks For Processing Efficiency. In IEEE Computer Architecture Letters (CAL 2023).
  5. [23’MM] Rajat Sainju, Graham Roberts, Wei-Ying Chen, Brian Hutchinson, Qian Yang, Caiwen Ding, Danny J Edwards, Meimei Li, Yuanyuan Zhu. ”Deep Learning for Automated Quantification of Irradiation Defects in TEM Data: Relating Pixel-level Errors to Defect Properties.” Microscopy and Microanalysis, 2023, page: 1559-15
  6. [22’ Nature Scientific Reports] Yuanyuan Zhu, Rajat Sainju, Wei-Ying Chen, Samuel Schaefer, Qian Yang, Caiwen Ding, Meimei Li. DefectTrack: A Deep learning-based Multi-Object Tracking Algorithm for Quantitative Defect Analysis of In-situ TEM Videos in Real-time. Nature Scientific Reports. [Impact factor: 5]
  7. [22’IEEE TC] Zeinab S. Jalali, Chenghong Wang, Griffin Kearney, Geng Yuan, Caiwen Ding, Yinan Zhou, Yanzhi Wang, Sucheta Soundarajan. Memristor-Based Spectral Decomposition of Matrices and Applications. In EEE Transactions on Computer (TC), 2022. ). [Impact factor: 3.131]
  8. [22’JLPEA] Oli-Uz-Zaman, Md, Saleh Ahmad Khan, Geng Yuan, Zhiheng Liao, Jingyan Fu, Caiwen Ding, Yanzhi Wang, and Jinhui Wang, Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs, Journal of Low Power Electronics and Applications, J. Low Power Electron. Appl. 2022, 12(1), 10; (The only Feature Paper in the entire issue)
  9. [22’MM] Rajat Sainju, Wei-Ying Chen, Samuel Schaefer, Qian Yang, Caiwen Ding, Meimei Li, Yuanyuan Zhu. ”Real-time Multi-Object Tracking of Ion-irradiation Induced Defects in in situ TEM Videos.” Microscopy and Microanalysis 28, no. S1 (2022): 2058-2059.
  10. [21’MM] Rajat Sainju, Steven Suib, Caiwen Ding, and Yuanyuan Zhu. ”Tracking and Understanding Nanocatalyst Sintering and Regeneration using Deep Learning-assisted In Situ Environmental TEM.” Microscopy and Microanalysis 28, no. S1 (2022): 2058-2059.
  11. [21’CADJ] Jiangce Chen, Horea T. Ilies, Caiwen Ding (2021). Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching, Computer-Aided Design.
  12. [21’TCCPS-LETTER] Caiwu Ding, Hongwu Peng, Lu Lu, and Caiwen Ding, Aerial Manipulation Using a Novel Unmanned AerialVehicle Cyber-Physical System, IEEE Technical Committee on Cyber-Physical Systems letter (TCCPSletter),
  13. [21’TPDS] Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu. TRUST: Triangle Counting Reloaded on GPUs. IEEE Transactions on Parallel and Distributed Systems. IEEE Transactions on Parallel and Distributed Systems (TPDS) (2021).
  14. [21’IEEE RA-L] Caiwu Ding, Lu Lu, Cong Wang, Caiwen Ding. Design, Sensing, and Control of a Novel UAV Platform for Aerial Drilling. In Robotics and Automation Letters (RA-L) (2021).
  15. [21′Nutrients] Xiang Chen, Evelyn Johnson, Aditya Kulkarni, Caiwen Ding, Natalie Ranelli, Yanyan Chen, and Ran Xu. (2021). An exploratory approach to deriving nutrition information of restaurant food from crowdsourced food images: Case of Hartford. Nutrients.
  16. [19’INTEGRATION] Ji Li, Zihao Yuan, Zhe Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Shahin Nazarian, Qinru Qiu, Bo Yuan, and Yanzhi Wang. Normalization and dropout for stochastic computing-based deep convolutional neural networks. In Integration, the VLSI Journal, 2019.
  17. [18’TVLSI] Jaemin Kim, Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Xue Lin, et al. Dynamic reconfiguration of thermoelectric generators for vehicle radiators energy harvesting under location-dependent temperature. In IEEETransactions on Very Large Scale Integration (VLSI) Systems (TVLSI).
  18. [18’TCAD] Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan, Jian Tang, Qinru Qiu, Yanzhi Wang. HEIF: Highly Efficient Stochastic Computing based Inference Framework for Deep Neural Networks. In IEEE Transactions computer Aided Design of Integrated Circuits & Systems (TCAD).
  19. [18’D&T] Caiwen Ding, Hongjia Li, Weiwei Zheng, Xue Lin, and Yanzhi Wang. Reconfigurable Photovoltaic Systems for Electric Vehicles. In IEEE Design & Test, 2018, IEEE.
  20. [17’D&T] Caiwen Ding, Ning Liu, Yanzhi Wang, Ji Li, Soroush Heidari, Jingtong Hu, and Yongpan Liu. Multisource indoor energy harvesting for nonvolatile In IEEE Design & Test, 34(3):42–49, 2017.
  21. [16’TCCPS-LETTER] Yanzhi Wang, Caiwen Ding, Luminescent Solar Concentrator-Based Reconfigurable Photovoltaic System for EV/HEV, IEEE Technical Committee on Cyber-Physical Systems letter (TCCPS- letter), 2016.

Workshop and Posters (* equal contribution)

    1. [24’ARC-LG (workshop paper)] Kiran Gautam Thorat, Amit Hasan, Jiahui Zhao, Yaotian Liu, Xi Xie, Hongwu Peng, Bin Lei, Jeff Zhang, and Caiwen Ding. “LLM-VeriPPA: Power, Performance, and Area-aware Verilog Code Generation and Refinement with Large Language Models.” ARC-LG workshop @ ISCA (2024).
    2. [23’AAAI DCAA (best paper award)] Songyang Han, Shanglin Zhou, Lynn Pepin, Jiangwei Wang, Caiwen Ding, and Fei Miao. “Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles.” AAAI DCAA workshop (2023).
    3. [20’NeurIPS workshop] Sheng Lin, Chenghong Wang, Hongjia Li, Jieren Deng, Yanzhi Wang, Caiwen Ding, ESMFL: Efficient and Secure Models for Federated Learning, In NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning, 2020.
    4. [20’FPGA] Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, So Hayden, Caiwen Ding. Ftdl: An FPGA-tailored architecture for deep learning applications. In Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. ACM, 2020. (Poster)
    5. [20’BARC] Zheng Zhan, Yifan Gong, Zhengang Li, Wei Niu, Xiaolong Ma, Bin Ren, Caiwen Ding, Xue Lin and Yanzhi Wang, A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework, Boston area ARChitecture Annual Workshop (BARC).
    6. [20’BARC] Shanglin Zhou, Bingbing Li, and Caiwen Ding. Accelerating Transformers-based Large-Scale Language Representation using FPGA, Boston area ARChitecture Annual Workshop (BARC).
    7. [19’MICCAI Workshop] Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, and Yanzhi Wang, Deep Compressed Pneumonia Detection for Low-Power Embedded Device. In the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshop, 2019.
    8. [18’ICLR Workshop] Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang. EfficientRecurrent Neural Networks using Structured Matrices in FPGAs. International Conference on Learning Representations (ICLR) Workshop, 2018.