The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Zhongfeng Wang sits on this spectrum.
This scientist: 327 publications — 63rd percentile
63% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 1,065 publications or more.
The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Zhongfeng Wang sits on this spectrum.
This scientist: 35 D-Index — 21st percentile
21% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 111 D-Index or more.
Zhongfeng Wang is affiliated with Nanjing University in China and has a significant body of research primarily in the fields of Computer Science and Engineering. Their work encompasses a broad range of subfields including Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, and Hardware and Architecture.
The scientist's main topics of research focus on advanced neural network applications, error correcting code techniques, advanced wireless communication techniques, advanced memory and neural computing, CCD and CMOS imaging sensors, image processing techniques and applications, and advanced vision and imaging.
Wang's recent published papers illustrate a strong engagement with emerging technologies and hardware-oriented innovations in neural computing and integrated systems. Notable papers include:
Frequent coauthors in Wang's publications include Jun Lin, Wendong Mao, Suwen Song, Meiqi Wang, and Jing Tian. These collaborations highlight ongoing research partnerships and joint contributions in related technical areas.
The scientist has contributed extensively to several reputable publication venues, with notable numbers of publications in the following:
Wang's research spans over 308 publications in Computer Science and 168 in Engineering, reflecting consistent academic productivity over diverse yet interconnected areas of study. The focus on hardware-accelerated neural networks, wireless communication techniques, and image processing underlines expertise in both theoretical and applied domains.
Zhongfeng Wang;Zhiqiang Cui
Kai Zhang;Xinming Huang;Zhongfeng Wang
Meiqi Wang;Siyuan Lu;Danyang Zhu;Jun Lin
T. Zhang;Z. Wang;K.K. Parhi
Zhongfeng Wang;H. Suzuki;K.K. Parhi
Jun Lin;Jin Sha;Zhongfeng Wang;Li Li
Jichen Wang;Jun Lin;Zhongfeng Wang
Bainan Chen;Xinmiao Zhang;Zhongfeng Wang
Siyuan Lu;Meiqi Wang;Shuang Liang;Jun Lin
Zhiqiang Cui;Zhongfeng Wang;Youjian Liu
Peiyi Zhao;J McNeely;Weidong Kuang;Nan Wang
Zhongfeng Wang;Zhipei Chi;K.K. Parhi
Danyang Zhu;Siyuan Lu;Meiqi Wang;Jun Lin
Zhisheng Wang;Jun Lin;Zhongfeng Wang
Yizhi Wang;Jun Lin;Zhongfeng Wang
Jun Lin;Jin Sha;Zhongfeng Wang;Li Li
Qingwei Li;Zhongfeng Wang
Jinjin He;Huaping Liu;Zhongfeng Wang;Xinming Huang
Chuan Zhang;Zhongfeng Wang;Jin Sha;Li Li
Zhongfeng Wang;Zhiqiang Cui
Jin Sha;Zhongfeng Wang;Minglun Gao;Li Li
Meiqi Wang;Zhisheng Wang;Jinming Lu;Jun Lin
Zhongfeng Wang;K.K. Parhi
Jinming Lu;Chao Fang;Mingyang Xu;Jun Lin
Xiaoru Xie;Jun Lin;Zhongfeng Wang;Jinghe Wei
Chunhua Deng;Fangxuan Sun;Xuehai Qian;Jun Lin
Jing Zeng;Jun Lin;Zhongfeng Wang
Yi Xie;Siyu Liao;Bo Yuan;Yanzhi Wang
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For students interested in Electronics and Electrical Engineering, exploring related fields can open up diverse career opportunities. A bachelor's degree in project management is an excellent complement, equipping graduates with skills to lead complex technical projects within engineering environments.
Many working professionals pursue education through degree programs for working adults, which offer flexible schedules and accelerated coursework. This approach is ideal for those balancing careers with education, enabling faster advancement in fields related to electronics and engineering.
For those interested in educational roles or corporate training within technology sectors, a master's in instructional design provides expertise to develop impactful learning materials that integrate technical knowledge with instructional strategies.
Additionally, competency based programs offer a practical path by focusing on demonstrated skills rather than traditional credit hours. This format benefits learners who already have industry experience and want to validate their competencies quickly and effectively.
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