Papers

4

Total Citations

14

H-Index

3

About

Muhammad Haris Khan is a pioneering researcher at the intersection of human-robot interaction, generative AI, and autonomous manufacturing. His work focuses on making robotics more accessible and intelligent, with key contributions in assistive manipulation, swarm robotics, and next-generation industrial systems. Khan’s most cited paper, “GazeGrasp” (6 citations), introduces a DNN-driven system that enables individuals with motor impairments to control collaborative robots using eye-gaze—a breakthrough in assistive technology that integrates ESP32 CAM, MediaPipe, and YOLOv8 for seamless, hands-free operation. He is also the visionary behind “Industry 6.0” (3 citations each in 2024 and 2025), which proposes the first fully automated production system that designs and manufactures products from natural language descriptions using generative AI and heterogeneous robot swarms. Additionally, his work “ImpedanceGPT” (2 citations) advances swarm drone navigation in dynamic environments by combining vision-language models with impedance control. With a growing citation impact and a focus on real-world applications, Khan is shaping the future of inclusive robotics and autonomous industry.

Research Focus

Key Achievements

3
H-Index
4
Papers
14
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
GazeGrasp: DNN-Driven Robotic Grasping with Wearable Eye-Gaze Interface
6 citations · 2025
📈 Most Prolific Year: 2025 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Skolkovo Institute of Science and Technology, Russian Space Systems

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago