基本信息

     

 

             李宝婷 博士

    人工智能学院 助理教授

 

        baotingli@xjtu.edu.cn

教育和工作经历

2024-至今，西安交通大学，人工智能学院，助理教授

2018-2023年，西安交通大学，电信学部微电子学院，博士研究生

2015-2018年，西安交通大学，软件学院(集成电路班)，硕士研究生

2011-2015年，哈尔滨工业大学，电子科学与技术，工学学士

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个人简介

李宝婷，工学博士，西安交通大学人工智能学院助理教授。研究兴趣包括轻量级神经网络、智能计算架构、数字集成电路等。

  1. Baoting Li, Danqing Zhang, Pengfei Zhao, et al., DQ-STP: An Efficient Sparse On-device Training Processor based on Low-rank Decomposition and Quantization for DNN[J]. IEEE Transactions on Circuits and Systems - I Regular Papers (TCAS-I), 2024. Accepted. 

  2. Danqing Zhang, Baoting Li, Hang Wang, et al., An Efficient Sparse-Aware Summation Optimization Strategy for DNN Accelerator[C]. IEEE International Symposium on Circuits and Systems (ISCAS), 2024. Accepted. 

  3. 汪航, 李宝婷, 张旭翀等, 深度神经网络在线训练硬件加速器的数据量化综述[J]. 微电子学与计算机. 2023.04.

  4. Baoting Li, Hang Wang, Fujie Luo, et al. ACBN: Approximate Calculated Batch Normalization for Efficient DNN On-device Training Processor[J]. IEEE Transactions on Very Large Scale Integration Systems (TVLSI), vol. 31, no. 6, pp. 738-748, June 2023.

  5. Baoting Li, Hang Wang, Xuchong Zhang, et al. Dynamic Dataflow Scheduling and Computation Mapping Techniques for Efficient Depthwise Separable Convolution Acceleration [J]. IEEE Transactions on Circuits and Systems - I Regular Papers (TCAS-I), vol. 68, no. 8, pp. 3279-3292, Aug. 2021.

  6. Shaofei Yang, Longjun Liu, Baoting Li, et al. Exploiting Variable Precision Computation Array for Scalable Neural Network Accelerators[C]. 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020, pp. 315-319.

  7. Baoting Li, Longjun Liu, Yanming Jin, et al. Designing Efficient Shortcut Architecture for Improving the Accuracy of Fully Quantized Neural Networks Accelerator[C]. 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 2020, pp. 289-294.

  8. Baoting Li, Longjun Liu, Jiahua Liang, et al. Exploring Resource-Aware Deep Neural Network Accelerator and Architecture Design[C]. 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), 2018, pp. 1-5.