潘红兵：男，工学博士。曾任Globalfoundries研究顾问，金沙威尼斯欢乐娱人城教授，博导生导师，国家重点项目首席专家。

1990年至1994年在金沙威尼斯欢乐娱人城物理学系获理学学士学位；2000年至2005年在金沙威尼斯欢乐娱人城物理学系微电子专业获工学博士学位。
主要研究领域为：类脑计算、感存算一体方法及芯片、存算一体方法及芯片、人工智能算法及硬件优化、可重构计算、嵌入式智能系统、数字信号处理算法硬件优化、CMOS传感器、模拟集成电路等方向的研究。

主要研究成果：2018年，提出了基于超大规模超小像素成像器件的光电存算一体方法。近年来发表学术论文50余篇；主持20余项科研项目，包括多项国家重点项目，国家自然科学基金面上项目，江苏省重点研发项目等，参与10余项科研项目，包括科技部重点专项等；申请发明专利60余项（其中获授权发明专利30余项，PCT等国际专利多项）；7项科研成果通过江苏省科技厅科技成果鉴定；“多核芯片设计关键技术及应用”项目获江苏省科技进步三等奖。

1.数字集成电路，存算一体芯片研究方向联系人：王宇宣老师，邮箱：wangyuxuan@nju.edu.cn

2.CMOS半导体器件、CMOS图像传感器芯片设计研究方向联系人：李张南老师，邮箱：mg1723014@smail.nju.edu.cn

3.模拟集成电路设计，认知成像芯片等研究方向联系人：王博士,邮箱：DG20230041@smail.nju.edu.cn

4.嵌入式智能系统，存算一体软硬件协同研究方向联系人：彭成磊老师，邮箱：pcl@nju.edu.cn

5.SPAD成像芯片设计方向联系人：毛成老师，cmao@nju.edu.cn

6.全定制芯片设计方向及系统开发方向联系人：孔祥顺老师，kxs@nju.edu.cn

1. 类脑计算方法及芯片

2. 存算一体方法及芯片

3. 人工智能算法及硬件优化

4. 嵌入式智能系统

5. 可重构计算

6. 数字信号处理算法硬件优化

7. CMOS传感器

8. 超大规模集成电路设计

本科生：数字系统I,并行计算
研究生：并行计算，数字集成电路设计

1. Xuan Chen, Xiaopeng Yuan,  Gaoming Fu, Yuanyong Luo,  Tao Yue,  Feng Yan,  Yuxuan Wang and Hongbing Pan*,Frontiers in Computational Neuroscience, Effective Plug-Ins for Reducing Inference-Latency of Spiking Convolutional Neural Networks During Inference Phase, 18 October 2021.pp.1-18| https://doi.org/10.3389/fncom.2021.697469

2.Hongxi Dong , Manzhen Wang, Yuanyong Luo , Muhan Zheng, Mengyu An, Yajun Ha , Hongbing Pan，PLAC: Piecewise Linear Approximation Computation for All Nonlinear Unary Functions，IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, VOL. 28, NO. 9, pp. 2014-2026, SEPTEMBER 2020

3.Zheng, Muhan , Luo, Yuanyong; Pan, Hongbing; Wang, Zhongfeng; Xue, Yuan , CLA Formula and its Acceleration of Architecture Design for Clustered Look-Ahead Pipelined Recursive Digital Filter, Journal of Signal Processing Systems, v 93, n 6, p 617-629, June 2021

4.Yuxuan Wang,Yuanyong Luo,Zhongfeng Wang and Hongbing Pan, A Hidden DCT-Based Invisible Watermarking Method for Low-Cost Hardware implementations，Electronics 2021, 10(12), 1465，18 Jun 2021

5.    Yuanyong Luo, Yuxuan Wang, Huaqing Sun, Yi Zha, Zhongeng Wang and Hongbing Pan, “CORDIC-Based Architecture for Computing Nth Root and Its Implementation,” in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 12, pp. 4183-4195, Dec. 2018.

6.    Yuanyong Luo, Yuxuan Wang, Yajun Ha, Zhongfeng Wang, Siyuan Chen and Hongbing Pan, “Generalized Hyperbolic CORDIC and Its Logarithmic and Exponential Computation with Arbitrary Fixed Base,” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 27, no. 9, pp. 2156-2169, Sept. 2019.

7.     Huaqing Sun, Yuanyong Luo, Yajun Ha, Yang Gao, Yinghuan Shi, Qinghong Shen, Hongbing Pan, “A Universal Method of Linear Approximation with Controllable Error for the Efficient Implementation of Transcendental Functions,” in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 67, no. 1, pp. 177-188, Jan. 2020.

8.     Yuxuan Wang, Yuanyong Luo, Zhongfeng Wang, Qinghong Shen and Hongbing Pan, “GH CORDIC-Based Architecture for Computing Nth Root of Single Precision Floating-point Number,” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 28, no. 4, pp. 864-875, April 2020.

9.     Zidi Qin, Yuou Qiu, Huaqing Sun, Zhonghai Lu, Zhongfeng Wang, Qinghong Shen and Hongbing Pan, A Novel Approximation Methodology and Its Efficient VLSI Implementation for the Sigmoid Function, in IEEE Transactions on Circuits and Systems II: Express Briefs, doi: 10.1109/TCSII.2020.2999458.

10.     Zidi Qin, Yuou Qiu, Muhan Zheng, Hongxi Dong, Zhonghai Lu, Zhongfeng Wang, and Hongbing Pan, A Universal Approximation Method and Optimized Hardware Architectures for Arithmetic Functions Based on Stochastic Computing, in IEEE Access, vol. 8, pp. 46229-46241, 2020, doi: 10.1109/ACCESS.2020.2978399.

11. Zidi Qin,Di Zhu,Xingwei Zhu,Xuan Chen,Yinghuan Shi,Yang Gao,Zhonghai Lu,Qinghong Shen,Li Li andHongbing Pan,Accelerating Deep Neural Networks by Combining Block-Circulant Matrices and Low-Precision Weights,Electronics,2019,8(1), 78

12. Wei Tang, Fei Lyu , Dunhui Wang, Hongbing Pan, A New Design of a Single-Device 3D Hall Sensor: Cross-Shaped 3D Hall Sensor, sensors, 2018, 18(4), 1065

13. Fei Lyu, Xinfu Liu, Yinjie Ding, Eng-Huat Toh, Zhenyan Zhang, Yifan Pan, Zhen Wang, Chengjie Li, Li Li, Jin Sha and Hongbing Pan*, Influences of an Aluminum Covering Layer on the Performance of Cross-Like Hall Devices, Sensors 2016, 16(1), 106

14. Fei Lyu, Zhenyan Zhang, Eng-Huat Toh, Xinfu Liu, Yinjie Ding, Yifan Pan,Chengjie Li, Li Li, Jin Sha and Hongbing Pan*，Performance Comparison of Cross-Like Hall Plates with Different Covering Layers,Sensors,2015,15,672-686

15. Yue Xu, Hong-Bin Pan*, Shu-Zhuan He, Li Li，Monolithic H-bridge brushless DC vibration motor driver with a highly sensitive hall sensor in 0.18 μm complementary metal-oxide semiconductor technology，IET Circuits, Devices & Systems，VOL7,I4,2013,P204-210

16 . Yue Xu, Hong-Bing Pan*, Shu-Zhuan He and Li Li, A Highly Sensitive CMOS Digital Hall Sensor for Low Magnetic Field Applications, Sensors 2012.12, pp.2162-P2174