Science Explorer Back to mapMap
Discussion
Researcher · Bristol Robotics Laboratory · United Kingdom

Ning Wang

Ning Wang publishes mostly in Control and Systems Engineering, Biomedical Engineering and Mechanical Engineering, on topics such as Robot Manipulation and Learning, Teleoperation and Haptic Systems and Soft Robotics and Applications.

ORCID 0000-0002-3264-1852 OpenAlex
World rank
#1,122,815
of 7,710,434 ranked researchers
Rank in United Kingdom
#89,740
of 367,258
Works
100
Citations
1.5k
Citations per work
15.4
h-index
21
i10-index 30Top 11% in Control and Systems Engineering
Ning Wang

What does Ning Wang research?

Ning Wang's work is mostly in Engineering (59%), Computer Science (11%), Neuroscience (7%).

Physical Sciences: 70 works · 70.0% of their workEngineering: 59 works · 58.8% of their workControl and Systems Engineering: 31 works · 31.1% of their workBiomedical Engineering: 18 works · 18.0% of their workMechanical Engineering: 10 works · 9.7% of their workComputer Science: 11 works · 11.2% of their workArtificial Intelligence: 7 works · 7.1% of their workComputer Vision and Pattern Recognition: 4 works · 4.1% of their workEverything else: 23 works · 23.3% of their workLife Sciences: 7 works · 6.7% of their workNeuroscience: 7 works · 6.7% of their workCognitive Neuroscience: 7 works · 6.7% of their workTHEIR WORKNing Wang100works
Life Sciences7%Physical Sciences70%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Engineering5958.8%
    2. Computer Science1111.2%
  2. Everything else2323.3%
    1. Neuroscience76.7%
  1. 1Control and Systems Engineering31% of their works
  2. 2Biomedical Engineering18% of their works
  3. 3Mechanical Engineering10% of their works
  4. 4Artificial Intelligence7% of their works
  5. 5Cognitive Neuroscience7% of their works
  6. 6Computer Vision and Pattern Recognition4% of their works

Research topics

Which keywords describe Ning Wang's research?

The keywords of their largest research topics: Deep Learning, Grasping, Robot Learning, Robotic Manipulators, Haptic Interfaces, Teleoperation, Neural Networks and Bioinspired Robotics.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 20 words, with their numbers
  1. Deep Learning582 topics
  2. Grasping491 topic
  3. Robot Learning491 topic
  4. Robotic Manipulators422 topics
  5. Haptic Interfaces251 topic
  6. Teleoperation251 topic
  7. Neural Networks212 topics
  8. Bioinspired Robotics171 topic
  9. Soft Robotics171 topic
  10. Electromyography161 topic
  11. Muscle Fatigue161 topic
  12. Robotics162 topics
  13. Kinematic Analysis121 topic
  14. Robot Manipulators121 topic
  15. Autonomous Control91 topic
  16. Brain-Computer Interfaces91 topic
  17. EEG Analysis91 topic
  18. Reinforcement Learning91 topic
  19. Exoskeletons71 topic
  20. Lower Limb71 topic

Where does Ning Wang work?

Ning Wang's main affiliation in the publication record is Bristol Robotics Laboratory, United Kingdom.

How many publications and citations does Ning Wang have?

OpenAlex counts 100 works and 1,542 citations for Ning Wang, an h-index of 21, ranking #1,122,815 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Other researchers named Ning Wang

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

Ask a question or share a note about Ning Wang. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.