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刘双龙 特聘教授

作者:时间:2020-10-09 08:30浏览次数:

 

 

个人简介

刘双龙,男,1988年8月出生,博士,“潇湘学者”特聘教授。湖南省“百人计划”青年项目入选者。2010年7月毕业于清华大学微纳电子系获得学士学位,2013年7月毕业于清华大学微电子所获得硕士学位,2017年9月获得英国帝国理工学院电子工程专业博士学位。2017年4月至2020年8月在帝国理工学院计算机系从事博士后研究工作(导师:Wayne Luk院士)。现主要从事高性能计算和大规模数字电路设计,研究领域包括基于可编程器件(FPGA)的神经网络加速、粒子滤波加速、贝叶斯算法加速和超光谱图像分割等。迄今已在IEEE Trans. On Computers,ACM Trans. on Reconfigurable Technology and Systems (TRETS),FPGA,FCCM等刊物上发表高水平学术论文22篇。申请国际发明专利两项,获得HiPEAC Paper Award。现承担国家自然科学基金青年科学基金项目。

办公室:理学院221

Email: s.liu13@imperial.ac.uk

学术贡献

1. 基于FPGA的高性能卷积神经网络加速器

2. 基于贝叶斯重采样的粒子滤波加速器

3. 自定制精度下的MCMC加速算法与系统

教学情况

更新中

承担课题

 1. 体育外围投注平台“潇湘学者”特聘教授启动经费 (2020/09-, 150万)

 2. 国家自然科学基金青年科学基金项目 (62001165, 2021/01-2023/12,24万)

代表性论文

1. H. Fan, M. Ferianc, S. Liu, and W. Luk, “RNAS: Reconfigurable CNN Accelerator with Differentiable Neural Architecture Search,” in IEEE International Conference on Computer Design (ICCD), 2020. (accepted)

2. Liu, Shuanglong, and Wayne Luk. "Towards an Efficient Accelerator for DNN-Based Remote Sensing Image Segmentation on FPGAs." In 2019 29th International Conference on Field Programmable Logic and Applications (FPL), pp. 187-193. IEEE, 2019.

3. Liu, S., Fan, H., Niu, X., Ng, H. C., Chu, Y., & Luk, W. (2018). Optimizing cnn-based segmentation with deeply customized convolutional and deconvolutional architectures on fpga. ACM Transactions on Reconfigurable Technology and Systems (TRETS), 11(3), 1-222018.

4. S. Liu, R. Chu, X. Wang, and W. Luk, “Optimizing CNN-based Hyperspectral Image Classification on FPGAs," in 15th International Symposium on Applied Reconfigurable Computing (ARC), 2018.

5. S. Liu, C. Zeng, H. Fan, H.-C. Ng, J. Meng, and W. Luk, “Memory-Efficient Architecture for Accelerating Generative Networks on FPGAs," in IEEE International Conference on Field Programmable Technology (FPT), 2018.

6. H. Fan, S. Liu, M. Ferianc, and W. Luk, “A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA," in IEEE International Conference on Field Programmable Technology (FPT), 2018.

7. S. Liu, G. Mingas, and C.-S. Bouganis, “An unbiased mcmc fpga-based accelerator in the land of custom precision arithmetic," IEEE Transactions on Computers, vol. 66, no. 5, pp. 745-758, 2017.

8. R. Zhao, S. Liu, H. Ng, E. Wang, J. Davis, X. Niu, X. Wang, H. Shi, G. Constantinides, P. Cheung, and W. Luk, “Hardware compilation of deep neural networks: An overview," in IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2018.

9. S. Liu, X. Niu, and W. Luk, “A low-power deconvolutional accelerator for convolutional neural network based segmentation on fpga," in ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2018, pp. 293-293.

10. S. Liu and C.-S. Bouganis, “Communication-aware mcmc method for big data applications on fpgas," in IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2017, pp. 9-16.

11. S. Liu, G. Mingas, and C.-S. Bouganis, “An exact mcmc accelerator under custom precision regimes," in IEEE International Conference on Field Programmable Technology (FPT), 2015, pp. 120-127.

12. S. Liu, G. Mingas, and C.-S. Bouganis, “Parallel resampling for particle filters on fpgas," in IEEE International Conference on Field-Programmable Technology (FPT), 2014, pp. 191-198.

13. 刘双龙 张春, 黄钰, 王志华, “一种基于内插采样的时差测量与基站同步技术," 电路与系统学报, vol. 18, no. 2, pp. 173-177, 2013.

获奖情况

1.  湖南省“青年百人计划”(2020年)

2.  Imperial College President's PhD Scholarships 2013年)

3. Marie Currie Research Fellowship 2012年)

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