Zhengde Zhang <br> 张正德

Zhengde Zhang
张正德

B.S. from BUAA
Ph.D from CAS
Postdoctor of SJTU
associate researcher at IHEP, CAS now

Biography / 自传

Zhengde Zhang is currently an associate researcher of the computing center of the Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences (CAS), Beijing, China.

张正德目前是中国科学院(CAS)高能物理研究所(IHEP)的副研究员，北京，中国。

His interests include deep learning, computer vision, first principles, application of artificial intelligence in the field of high energy physics and quantum-inspired third generation artificial intelligence algorithm.

研究领域包含深度学习、计算机视觉、第一原理、人工智能在高能物理领域的应用和量子启发的第三代人工智能算法。

Github Open Source Homepage/开源主页: https://github.com/zhangzhengde0225

Experience / 教育和工作经历

From Sept. 2011 to Jun. 2015, he received the B.S. degree in applied physics from the School of Physics, Beihang University (BUAA), Beijing, China.

2011.09-2015.06，在北京航空航天大学(BUAA) 取得应用物理学理学学士学位。

From Sept. 2015 to June 2020, he received the Ph.D. degree in particle physics and nuclear physics from the Shanghai Institute of Applied Physics (SINAP), Chinese Academy of Sciences, Shanghai, China.

2015.09-2020.06，在中国科学院(CAS)上海应用物理研究所(SINAP) 取得粒子物理与原子核物理博士学位。

From Jul. 2020 to Jun. 2022, he completed post doctoral research at the School of Electronic Information and Electrical Engineering (SEIEE) of Shanghai Jiaotong University (SJTU), Shanghai, China. The research topic is “The Application and Frontier of Deep Learning Algorithms in the Field of Target Detection – From Data Augmentation, Network Improvement to Quantum-inspired Knowledge Element Fusion”.

2020.07-2022.06，在上海交通大学(SJTU)电子信息与电气工程学院(SEIEE) 信息与通信工程流动站完成博士后研究，研究课题为：深度学习在目标检测领域的应用研究与前沿探索——从数据增强、网络改进到量子启发的知识要素融合。

Achievements / 成果

Open Source Project / 开源项目

  • [1] damei: Artificial Intelligence and Quantum Mechanics Intersection Library.

    一个人工智能和量子力学交叉研究的开源项目，常用函数、控制台、解算器。

    开源地址：https://github.com/zhangzhengde0225/damei

  • [2] CDNet: The Crosswalk Detection Network based on YOLOv5.

    一个实时、鲁棒的超越原生YOLOv5的斑马线检测网络.

    开源地址：https://github.com/zhangzhengde0225/CDNet

  • [3] FINet: A Transmission Line Insulator Dataset Based on Synthetic fog (~13000 images) and a detection benchmark.

    一个基于合成雾的输电导线绝缘子数据集(~13000张图像)和一个检测基准.

    开源地址：https://github.com/zhangzhengde0225/FINet

  • [4] VaspCZ: An Efficient VASP Computation Assistant Program.

    一个提高效率高效的VASP辅助计算程序.

    开源地址：https://github.com/zhangzhengde0225/VaspCZ

Publications / 学术论文

一作或通讯论文

  • [1] 2022. Zhang ZD*, Tan ML, Lan ZC, Liu HC, Pei L and Yu WX*. CDNet: A Real-Time and Robust Crosswalk Detection Network on Jetson Nano Based on YOLOv5 [J].

    CDNet: 一个基于YOLOv5的在Jetson Nano上实时、鲁棒的斑马线检测网络 [J].

    Neural Computing and Applications, 2022, 1(1): 1-1.

    DOI: 10.1007/s00521-022-07007-9

    CODE: CDNet

  • [2] 2022. Zhang ZD*, Zhang Bo*, Lan ZC, Liu HC, Li DY, Pei L and Yu WX. FINet: An Insulator Dataset and Detection Benchmark Based on Synthetic Fog and improved YOLOv5 [J].

    FINet: 一个基于合成雾和改进YOLOv5的绝缘子数据集和检测基准 [J].

    IEEE Transactions on Instrumentation and Measurement, TIM, 2022, Accepted.

    CODE: FINet

  • [3] 2022. Xu C, Pei L*, Zhang ZD*. MWNet: A Tracking Method for Frequently Occluded Scenes Based on Matter Waves [C].

    MWNet：一种基于物质波的频繁遮挡场景跟踪方法 [C].

    The 29th IEEE International Conference on Image Processing, ICIP, 2022, Accepted.

  • [4] 2022. Zhou FR, Ma Y, Wen G, Ma YT, Lan ZC, Zhang ZD*. AIDNet: Detecting Insulators and Defects from Satellite Remote Sensing Images An Exploration [C].

    AIDNet: 基于自适应增强算法的从卫星遥感图像中检测绝缘子及其缺陷的探索研究 [C].

    2022 International Conference on Computer Networks and Communications, ICCNC. 2022. Accepted.

  • [5] 2022. Zhou FR, Zhang H, Zhe ML, Wen G, Pan H, Lan ZC, Zhang ZD*. TLDNet: A transmission line and its defect detection method based on data enhancement, augmentation and neural network [J].

    TLDNet: 一种基于数据增强增广和神经网络的输电导线及其缺陷检测方法 [J].

    Southern Power System Technology, 2022, Accepted.

  • [6] 2020. Zhang ZD, Tan ML, Ren CL and Huai P*. VaspCZ: an efficient VASP computation assistant program [J].

    VaspCZ: 一个提高效率的VASP计算辅助程序[J].

    Nuclear Techniques, 2020, 32(3): 30501.

    DOI: 10.11889/j.0253-3219.2020.hjs.43.030501

    CODE: VaspCZ

  • [7] 2020. Zhang ZD, Ren CL, Tan ML, Yang YQ, Yin YR, Wang CY, Han H and Huai P. Migration Behavior of Tellurium in Bcc Iron Against Typical Alloying Elements: A First-principles Study [J].

    Te与典型合金元素在bcc-Fe中的扩散行为的第一性原理研究 [J].

    Computational Materials Science, 2020, 181(1): 109571.

    DOI: 10.1016/j.commatsci.2020.109571

合作论文

  • [1] 2022. Tan ML, Zhu GF, Zhang ZD, Zou Y, Yu XH, Yu CG, Dai Y and Yan R.

    Burnup optimization of once-through molten salt reactors using enriched uranium and thorium [J].

    使用富集铀和钍的一次通过熔盐堆的燃耗优化 [J].

    Nuclear Science and Techniques, 2022, 33(1): 1-1.

    DOI: 10.1007/s41365-022-00995-2

  • [2] 2021. Ji ZH, Zhang LL, Tang DM, Chem CM, Nordling TEM, Zhang ZD, Ren CL, Da B, Li X, Guo SY, Liu C and Cheng HM.

    High-throughput screening and machine learning for the efficient growth of high-quality single-wall carbon nanotubes [J].

    高效生长高质量单壁碳纳米管的高通量筛选和机器学习 [J].

    Nano Research, 2021, 14(12): 4610-4615.

    DOI: 10.1007/s12274-021-3387-y

  • [3] 2020. Hu JB, Hu JP, Zhang ZD, Shen KC, Liang ZF, Zhang H, Tian QW, Wang P, Jiang Z, Huang H, Wells JW, Song F*.

    Ullmann coupling of 2,7-dibromopyrene on Au(1 1 1) assisted by surface adatoms [J].

    表面吸附原子辅助下2,7-二溴芘在Au(1 1 1)上的Ullmann耦合 [J].

    Applied Surface Science, 2020, 513(1): 145797.

    DOI: 10.1016/j.apsusc.2020.145797

  • [4] 2020. Hu JB, Strand FS, Chellappan RK, Zhang ZD, Shen KC, Hu JP, Ji GW, Huai P, Huang H, Wang P, Li ZS, Jiang Z, Weels JW and Song F*.

    Direct Synthesis of Semimetal Phthalocyanines on a Surface with Insights into Interfacial Properties [J].

    基于洞察界面性质在表面上直接合成半金属酞菁 [J].

    Journal of Physical Chemistry C, 2020, 124(15): 8247-8256.

    DOI: 10.1021/acs.jpcc.0c00895

  • [5] 2020. Liao LX, Zhang X, Ren CL, Zhang ZD, Huang HF, Ma GH, Huai P*.

    First-principles study of helium behavior in nickel with noble gas incorporation.

    镍中掺杂惰性气体的氦行为第一性原理研究 [J].

    Journal of Applied Physics, 2020*, 127(17): 1-1.

    DOI: 10.1063/1.5145016

Patent & Software copyright / 专利和软著

  • [1] 2022. 专利. 《基于深度学习的可见光、红外和雷达融合目标检测方法》
  • [2] 2021. 专利. 《一种基于深度学习的输电线路绝缘子缺陷检测方法》
  • [3] 2021. 专利. 《一种基于神经网络的自然灾害后建筑损伤评估方法》
  • [4] 2021. 技术成果转移. 《基于深度学习的目标自动检测、跟踪和半自动状态标注软件》2021SR0416473 165万 1/3
  • [5] 2020. 软著. 《AILabelImage: 目标自动检测、跟踪和半自动标注软件》

Infos / 联系信息

E-mail : drivener@163.com
Github开源地址: https://github.com/zhangzhengde0225
ResearchGate主页：https://www.researchgate.net/profile/De-Zhang-12
ORCID主页: https://orcid.org/my-orcid?orcid=0000-0002-6542-052X