Tianqi Tang (唐天琪)

Tianqi Tang received her B.S. degree in 2014 and her M.S. degree in 2017 from Department of Electronic Engineering in Tsinghua University, Beijing, China, and she is currently a Ph.D. student in UCSB under the supervision of Prof. Yuan Xie. Ms. Tang’s research mainly focuses on On-Chip Neural Network System , In Memory Processing, Emerging Non-Volatile-Memory Technology.


Address: 4-205, Rohm Building, Tsinghua University, Beijing, China
Email: ttq1008☺gmaNOSPAMMINGil·com

Selected Publications

Conference Papers

  • Tianqi Tang, Lixue Xia, Boxun Li, Yu Wang, Huazhong Yang, Binary Convolutional Neural Network on RRAM , in Proceedings of the 22nd Asia and South Pacific Design Automation Conference (ASP-DAC), 2017, pp.782-787. pdf slide
  • Lixue Xia, Tianqi Tang, Wenqin Huangfu, Ming Cheng, Xiling Yin, Boxun Li, Yu Wang, Huazhong Yang, Switched by Input: Power Efficient Structure for RRAM-based Convolutional Neural Network , in Design Automation Conference (DAC), 2016, pp.125:1-125:6. pdf slide
  • Yu Wang, Lixue Xia, Tianqi Tang, Boxun Li, Song Yao, Ming Cheng, Huazhong Yang, Low Power Convolutional Neural Networks on a Chip , in ISCAS, 2016, pp.129-132. pdf slide
  • Tianqi Tang, Lixue Xia, Boxun Li, Rong Luo, Yu Wang, Yiran Chen, Huangzhong Yang, Spiking Neural Network with RRAM : Can We Use it for Real-World Application? , in Proceedings of the Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015, pp.860-865. pdf
  • Yu Wang, Tianqi Tang, Lixue Xia, Boxun Li, Peng Gu, Hai Li, Yuan Xie, Huazhong Yang, Energy Efficient RRAM Spiking Neural Network for Real Time Classification , in Proceedings of the 25th Edition on Great Lakes Symposium on VLSI (GLSVLSI), 2015, pp.189-194. pdf
  • Yung-Hsiang Lu, Alan M. Kadin, Alexander C. Berg, Thomas M. Conte, Erik P. DeBenedictis, Rachit Garg, Ganesh Gingade, Bichlien Hoang, Yongzhen Huang, Boxun Li, Jingyu Liu, Wei Liu, Huizi Mao, Junran Peng, Tianqi Tang, Elie K. Track, Jingqiu Wang, Tao Wang, Yu Wang, Jun Yao, Rebooting Computing and Low-Power Image Recognition Challenge , in IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2015, pp.927-932. pdf
  • Tianqi Tang, Rong Luo, Boxun Li, Hai Li, Yu Wang, Huazhong Yang, Energy Efficient Spiking Neural Network Design with RRAM Devices , in Proceedings of the 14th International Symposium on Integrated Circuits (ISIC), 2014, pp.268 - 271. pdf

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