Papers

11

Total Citations

1,066

H-Index

7

About

Jianjun Meng is a prominent researcher specializing in brain-computer interfaces (BCIs), neurorobotics, and neuroprosthetics, with a particular focus on enabling intuitive, noninvasive neural control of robotic and assistive devices. His work has fundamentally advanced the field of EEG-based robotic control, most notably through his landmark 2016 study demonstrating noninvasive BCI-driven reach-and-grasp tasks with a robotic arm — a paper that has since accumulated over 475 citations and remains a touchstone in the field. Building on this, his 2019 work on continuous neural tracking for robotic device control (378 citations) established critical groundwork for practical, high-dimensional neuroprosthetic systems that sidestep the risks of surgical implantation. Meng has also made sustained contributions to SSVEP- and motor imagery-based BCI paradigms, hybrid BCI architectures, and myoelectric prosthetic control, including a comprehensive decade-in-review of upper-limb prosthesis research published in 2023. His investigations into spatial-temporal EEG dynamics and the effects of gaze fixation on BCI performance reflect a rigorous, clinically motivated research philosophy. Collectively, his body of work — spanning over 1,000 cumulative citations — meaningfully bridges laboratory neuroscience and real-world assistive technology for individuals with motor impairments.

Research Focus

Key Achievements

7
H-Index
11
Papers
1,066
Total Citations
97
Avg Citations/Paper
🏆 Most Cited Paper
Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks
475 citations · 2016
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 29
🏛 Institutions: University of Minnesota, Carnegie Mellon University, Shanghai Jiao Tong University, University of Minnesota System

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago