唐建石，长聘副教授，博士生导师。2008年本科毕业于清华大学微纳电子系，2014年博士毕业于美国UCLA电子工程系，2015-2019年在美国IBM T. J. Watson Research Center工作，2019年回清华大学工作，现任清华大学集成电路学院长聘副教授、副院长，入选国家级高层次人才计划和国家级青年人才计划、《麻省理工科技评论》“35岁以下科技创新35人”中国区榜单，先后获清华大学“学术新人奖”、清华大学优秀博士/硕士学位论文指导教师、中国电子学会自然科学一等奖、中国半导体十大研究进展、中国新锐科技人物卓越影响奖、IEEE Brain Best Paper Award、NT18“Best Young Scientist Award”等奖项。主要研究方向包括新型存储器与类脑计算、单片三维异质集成等，先后主持科技部青年科学家项目、基金委重点项目等10余项。以第一/通讯作者在Nature Electronics、Nature Nanotechnology、IEDM、VLSI等重要期刊和国际会议上发表论文60余篇，论文被引16000余次，授权专利60余项。担任IEEE Transactions on Electron Devices编辑、Journal of Semiconductors编委，IEDM、IEEE-NANO、EDTM、CSTIC等国际会议的技术委员会成员，IEEE高级会员。

招生/招聘信息：本课题组每年招收3-5名博士/硕士研究生，常年招聘器件、工艺、电路、算法等方向的博士后，同时也非常欢迎感兴趣的本科生参与科研。详情请附上简历咨询jtang@tsinghua.edu.cn.

Prof. Jianshi Tang is currently a tenured Associate Professor and Vice Dean of the School of Integrated Circuits at Tsinghua University. Prof. Tang received his BS degree from the Department of Microelectronics and Nanoelectronics at Tsinghua University in 2008, and his PhD degree in Electrical Engineering from University of California, Los Angeles (UCLA) in 2014. From 2015 to 2019, he worked at IBM T. J. Watson Research Center, after which he joined Tsinghua University in 2019. He received many awards including Top 10 Semiconductor Research Progress of China, Tsinghua University Outstanding Young Faculty Award, Tsinghua University Outstanding Ph.D./M.S Thesis Advisor, MIT TR35 China, CIE Natural Science Award, IEEE Brain Best Paper Award, NT18 “Best Young Scientist Award”. His main research areas include emerging memory and neuromorphic computing, and monolithic 3D heterogeneous integration, etc. He is the PI of over 10 research projects funded by NSFC, MOST, etc. As the first/corresponding author, Prof. Tang has published more than 60 articles and proceedings in top journals and international conferences, such as Nature Electronics, Nature Nanotechnology, IEDM, VLSI, etc. His work has been cited over 16000 times and he is granted over 60 patents. Prof. Tang is an Editor for IEEE Transactions on Electron Devices and serves on the Editorial Board of Journal of Semiconductors. He is an IEEE senior member, and served as Technical/Executive Committee Member for several international conference, including IEDM, IEEE-NANO, EDTM, CSTIC, etc.

Group Openings: Our group has openings for 3-5 PhD/Master students every year and regularly recruit postdocs with related background in emerging devices, nanofabrication and circuit design. Undergraduate students are also encouraged to participate in our research. For more information, please email jtang@tsinghua.edu.cn with your CV.

近期代表性工作（通讯/一作）Representative Publications (as correspondence/first author):

Journal Papers:

[1] Z. Liu^#, J. Mei^#, J. Tang^*, M. Xu^*, B. Gao, K. Wang^., S. Ding, Q. Liu, Q. Qin, W. Chen, Y. Xi, Y. Li, P. Yao, H. Zhao, N. Wong, H. Qian, B. Hong, T.-P. Jung, D. Ming^*, H. Wu^*, “A Memristor-based adaptive neuromorphic decoder for brain-computer interfaces”, Nature Electronics, published online (2025).

[2] H. Huang, X. Liang, Y. Wang^*, J. Tang^*, Y. Li, Y. Du, W. Sun, J. Zhang, P. Yao, X. Mou, F. Xu, J. Zhang, Y. Lu, Z. Liu, J. Wang, Z. Jiang, R. Hu, Z. Wang, Q. Zhang, B. Gao, X. Bai, L. Fang, Q. Dai, H. Yin, H. Qian, H. Wu^*, “Fully integrated multimodal optoelectronic memristor array for diversified in-sensor computing applications”, Nature Nanotechnology, 20, 93 (2025). (Cover Image)

[3] X. Li^#, B. Qin^#, Y. Wang^#, Y. Xi, Z. Huang, M. Zhao, Y. Peng, Z. Chen, Z. Pan, J. Zhu, C. Cui, R. Yang, W. Yang, S. Meng, D. Shi, X. Bai, C. Liu, N. Li, J. Tang^*, K. Liu^*, L. Du^*, G. Zhang^*, “2D Sliding ferroelectric memories and synapses”, Nature Communications, 15, 10921 (2024).

[4] H. Xu, D. Shang^*, J. Tang^*, Q. Luo, X. Xu, R. Liang, L. Pan, B. Gao, Q. Wang, D. He, Q. Liu^*, M. Liu, H. Qian, H. Wu^*, “A biomimetic nociceptor based on a vertical multi-gate, multi-channel neuromorphic transistor”, ACS Nano, 18, 30668 (2024).

[5] X. Liang, J. Tang^*, Y. Zhong, B. Gao, H. Qian, H. Wu, “Physical reservoir computing with emerging electronics”, Nature Electronics, 7, 193 (2024).

[6] Y. Du, J. Tang^*, Y. Li, Y. Xi, Y. Li, J. Li, H. Huang, Q. Qin, Q. Zhang, B. Gao, N. Deng, H. Qian, H. Wu, “Monolithic 3D Integration of Analog RRAM-Based Computing-in-Memory and Sensor for Energy-Efficient Near-Sensor Computing” Advanced Materials, 36, 202302658 (2024).

[7] Y. Fan, R. An, J. Tang^*, Y. Li, T. Liu, B. Gao, H. Qian, H. Wu, “Monolithic 3D integration as a pathway to energy-efficient computing and beyond: From materials and devices to architectures and chips”. Current Opinion in Solid State and Materials Science, 33, 101199 (2024).

[8] Y. Li, J. Tang^*, J. Yao, A. Fan, B. Yan, Y. Yang, Y. Xi, Y. Li, J. Li, W. Sun, Y. Du, Z. Liu, Q. Zhang, S. Qiu, Q. Li, H. Qian, H. Wu^*, “Monolithic three-dimensional integration of RRAM-based hybrid memory architecture for one-shot learning”, Nature Communications, 14, 7140 (2023).

[9] H. Zhao^#, Z. Liu^#, J. Tang^*, B. Gao, Q. Qin, J. Li, Y. Zhou, P. Yao, Y. Xi, Y. Lin, H. Qian, H. Wu, “Energy-Efficient High-Fidelity Image Reconstruction with Memristor Arrays for Medical Diagnosis”, Nature Communications, 14, 2276 (2023).

[10] H. Xu, D. Shang^*, Q. Luo, J. An, Y. Li, S. Wu, Z. Yao, X. Xu, P. Zhang, C. Dou, H. Jiang, L. Pan, X. Zhang, M. Wang, Z. Wang, J. Tang^*, Q. Liu^*, M. Liu, “A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing”, Nature Communications, 14, 6385 (2023).

[11] X. Li, Y. Zhong, H. Chen, J. Tang^*, X. Zheng, W. Sun, Y. Li, D. Wu, B. Gao, X. Hu^*, H. Qian, H. Wu^*, “A Memristors-based Dendritic Neuron for High-Efficiency Spatial-Temporal Information Processing”, Advanced Materials, 35, 2203684 (2023).

[12] Y. Zhong, J. Tang^*, X. Li, X. Liang, Z. Liu, Y. Li, Y. Xi., P. Yao, Z. Hao, B. Gao, H. Qian, H. Wu^*, “A Memristor-based Analogue Reservoir Computing System for Real-Time and Power-Efficient Signal Processing”, Nature Electronics, 5, 672-681 (2022). (Selected as Editorials)

[13] X. Liang^#, Y. Zhong^#, J. Tang^*, Z. Liu, P. Yao, K. Sun, Q. Zhang, B. Gao, H. Heidari^*, H. Qian, H. Wu^*, “Rotating Neurons for All-Analog Implementation of Cyclic Reservoir Computing”, Nature Communications, 13, 1549 (2022). (Featured in Nature Communications Editors’ Highlights)

[14] Z. Zhao, J. Tang^*, J. Yuan, Y. Li, Y. Dai^*, J. Yao, Q. Zhang, S. Ding, T. Li, R. Zhang, Y. Zheng, Z. Zhang, S. Qiu, Q. Li, B. Gao, N. Deng, H. Qian, F. Xing, Z. You, H. Wu^*, “Large-Scale Integrated Flexible Tactile Sensor Array for Sensitive Smart Robotic Touch”, ACS Nano 16, 16784-16795 (2022).

[15] X. Mou, J. Tang^*, Y. Lyu, Q. Zhang, S. Yang, F. Xu, W. Liu, M. Xu, Y. Zhou, W. Sun, Y. Zhong, B. Gao, P. Yu^*, H. Qian, H. Wu, “Analog Memristive Synapse based on Topotactic Phase Transition for High-Performance Neuromorphic Computing and Neural Network Pruning”, Science Advances, 7, abh0648 (2021).

[16] Y. Zhong, J. Tang^*, X. Li, B. Gao, H. Qian, H. Wu^*, “Dynamic Memristor-based Reservoir Computing for High-Efficiency Temporal Signal Processing”, Nature Communications, 12, 408 (2021).

[17] X. Li^#, J. Tang^#, Q. Zhang^#, B. Gao, J. Joshua Yang, S. Song, W. Wu, W. Zhang, P. Yao, N. Deng, L. Deng, Y. Xie, H. Qian, H. Wu^*, “Power-Efficient Neural Network with Artificial Dendrites”, Nature Nanotechnology, 15, 776 (2020).

[18] Z. Liu, J. Tang^*, B. Gao, X. Li, P. Yao, Y. Lin, D. Liu, B. Hong, H. Qian, H. Wu^*, “Multi-Channel Parallel Processing of Neural Signals in Memristor Arrays”, Science Advances, 6, eabc4797 (2020).

[19] Z. Liu, J. Tang^*, B. Gao, P. Yao, X. Li, D. Liu, Y. Zhou, H. Qian, B. Hong^*, H. Wu^*, “Neural Signal Analysis with Memristor Arrays Towards High-Efficiency Brain-Machine Interfaces”, Nature Communications, 11, 4234 (2020).

[20] Y. Li, J. Tang^*, B. Gao, W. Sun, Q. Hua, W. Zhang, X. Li, W. Zhang, H. Qian, H. Wu^*, “High-Uniformity Threshold Switching HfO₂-based Selectors with Patterned Ag Nanodots”, Advanced Science, 7, 2002251 (2020).

[21] J. Tang^#, F. Yuan^#, X. Shen^#, Z. Wang, M. Rao, Y. He, Y. Sun, X. Li, W. Zhang, Y. Li, B. Gao, H. Qian, G. Bi, S. Song, J. Joshua Yang*, H. Wu*, “Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges”, Adv. Mater., 31, 1902761 (2019).

Conference Proceedings:

[22] T. Liu, J. Tang^*, Y. Du, H. Yang, Y. Zhang, Z. Liu, Z. Jiang, R. An, Y. Xi, Y. Li, D. Wu, B. Gao, H. Qian, H. Wu^*, “IGZO/TeO_x Complementary Oxide Semiconductor-based CFET for BEOL-Compatible Memory-Immersed Logic”, IEDM Tech. Dig., 5.3.1-5.3.4 (2024). (IEDM Highlight Paper)

[23] Y. Su^#, T. Liu^#, J. Tang^*, Y. Li, R. An, Y. Du, Z. Tang, Y. Zhang, Y. Fan, Y. He, M. Shi, H. Yang, T. Huang, J. Zhang, Z. Zhu, G. Wang, C. Zhao, C. Wang, L. Pan, P. Yao, D. Wu, B. Gao, H. Qian, and H. Wu, “Complementary Oxide Semiconductor-based 2T0C DRAM Macro with CFET peripherals using TeO_x-PFET/IGZO-NFET for 3D Memory Integration”, IEDM Tech. Dig., 6.5.1-6.5.4 (2024).

[24] J. Zhang^#, X. Ma^#, Y. Xi, Y. Lu, K. Wang, H. Ren, J. Tang^*, L. Pan^*, L. Chen, D. Wu, B. Gao, H. Qian, H. Wu^*, “A 28nm 4Mb Embedded RRAM IP with Record-High Endurance of 10⁷ Cycles and 10years@125°C Retention through Reliability-Enhanced Design-Technology Co-Optimization”, IEDM Tech. Dig., 11.6.1-11.6.4 (2024).

[25] Y. Zhang, J. Tang^*, Y. Li, N. Gao, L. Gao, H. Xu^*, R. An, H. Yang, Z. Liu, C. Guo, W. Bu, D. Wu, B. Gao, H. Qian, H. Wu, “Monolithic 3D Integration of Multi-layer CNT-CMOS/RRAM Macros for Mixed-Precision Analog-Digital Computing-in-Memory Architecture”, IEDM Tech. Dig., 5.7.1-5.7.4 (2024).

[26] H. Yang^#, Y. Li^#, J. Tang^*, R. An, Y. Zhang, L. Gao, N. Gao, H. Xu, Y. Du, Z. Liu, X. Ma, G. Wang, C. Zhao, J. Xiang, J. Zhao, W. Bu, K. Zheng, J. Kang, B. Gao, H. Qian, H. Wu, “Monolithic 3D Integration of Analog RRAM-based Fully Weight Stationary and Novel CFET 2T0C-based Partially Weight Stationary for Accelerating Transformer”, VLSI, JFS6.5 (2024).

[27] Y. Zhang^#, Y. Li^#, J. Tang^*, N. Gao, L. Gao, H. Xu^*, R. An, Q. Qin, Z. Liu, D. Wu, B. Gao, H. Qian, H. Wu, “3D Stackable CNTFET/RRAM 1T1R Array with CNT CMOS Peripheral Circuits as BEOL Buffer Macro for Monolithic 3D Integration with Analog RRAM-based Computing-In-Memory”, IEDM Tech. Dig., 23.2.1-23.2.4 (2023). (IEDM Highlight Paper)

[28] M. Shi^#, Y. Su^#, J. Tang^*, Y. Li, Y. Du, R. An, J. Li, Y. Li, J. Yao, R. Hu, Y. He, Y. Xi, Q. Li, S. Qiu, Q. Zhang, L. Pan, B. Gao, H. Qian, H. Wu, “Counteractive Coupling IGZO/CNT Hybrid 2T0C DRAM Accelerating RRAM-based Computing-In-Memory via Monolithic 3D Integration for Edge AI”, IEDM Tech. Dig., 14.2.1-14.2.4 (2023).

[29] Z. Jiang, Y. Xi, J. Tang^*, Y. Lu, R. Yu, R. Hu, Q. Hu, B. Gao, H. Qian, H. Wu^*, “COPS: An Efficient and Reliability-Enhanced Programming Scheme for Analog RRAM and On-Chip Implementation of Denoising Diffusion Probabilistic Model”, IEDM Tech. Dig., 21.1.1-21.1.4 (2023).

[30] Y. Du, J. Tang^*, Y. Li, Y. Xi, B. Gao, H. Qian, H. Wu, “Monolithic 3D Integration of FeFET, Hybrid CMOS Logic and Analog RRAM Array for Energy-Efficient Reconfigurable Computing-In-Memory Architecture”, VLSI, T15-4 (2023).

[31] R. An^#, Y. Li^#, J. Tang^*, B. Gao, Y. Du, J. Yao, Y. Li, S. Wen, H. Zhao, J. Li, Q. Qin, Q. Zhang, S. Qiu, Q. Li, Z. Li^*, H. Qian, H. Wu^*, “A Hybrid Computing-In-Memory Architecture by Monolithic 3D Integration of BEOL CNT/IGZO-based CFET Logic and Analog RRAM”, IEDM Tech. Dig., 18.1.1-18.1.4 (2022). (IEDM Brain Best Paper Award)

[32] Y. Li, J. Tang^*, B. Gao, J. Yao, Y. Xi, Y. Li, T. Li, Y. Zhou, Z. Liu, Q. Zhang, S. Qiu, Q. Li, H. Qian, H. Wu^*, “Monolithic 3D Integration of Logic, Memory and Computing-In-Memory for One-Shot Learning”, IEDM Tech. Dig., 21.5.1-21.5.4 (2021). (IEDM Highlight Paper)

[33] H. Zhao, Z. Liu, J. Tang^*, B. Gao, Y. Zhou, P. Yao, Y. Xi, H. Qian, H. Wu^*, “Implementation of Discrete Fourier Transform using RRAM Arrays with Quasi-Analog Mapping for High-Fidelity Medical Image Reconstruction”, IEDM Tech. Dig., 12.4.1-12.4.4 (2021).

[34] Y. Lin, Q. Zhang, J. Tang^*, B. Gao, C. Li, P. Yao, Z. Liu, J. Zhu, J. Lu, S. X. Hu, H. Qian, H. Wu^*, “Bayesian Neural Network Realization by Exploiting Inherent Stochastic Behavior of Analog RRAM”, IEDM Tech. Dig., 14.6.1-14.6.4 (2019).