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 Mark Yim sits on this spectrum.
This scientist: 232 publications — 39th percentile
39% 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 Mark Yim sits on this spectrum.
This scientist: 49 D-Index — 58th percentile
58% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 111 D-Index or more.
Mark Yim is affiliated with the University of Pennsylvania in the United States and specializes in Engineering, with a primary focus on Mechanical Engineering and Biomedical Engineering. Their research also covers Computer Vision and Pattern Recognition, Control and Systems Engineering, and Computer Networks and Communications.
The scientist's main areas of study include Modular Robots and Swarm Intelligence, Soft Robotics and Applications, Robotic Path Planning Algorithms, Micro and Nano Robotics, Advanced Materials and Mechanics, Robot Manipulation and Learning, and Robotic Locomotion and Control.
Mark Yim has published extensively in several prominent venues. Frequent publication venues include:
Mark Yim's recent papers exemplify a focus on modular robotics and variable topology structures. Key publications are:
Collaborative work is a significant part of Mark Yim's research efforts. Frequent co-authors include:
The research topics and their wide scope indicate an interdisciplinary approach, combining aspects of engineering design, materials science, and autonomous systems. The work involving modular robots and swarm intelligence integrates hardware innovation with algorithmic development, notably in path planning and control. The engagement with micro and nano robotics further diversifies the scale at which this scientist operates, bridging from macroscale robot structures to microscale device applications.
Mark Yim has contributed to both experimental and computational aspects of robotics. This includes the study of variable topology truss systems, which involves reconfigurable mechanical structures, as well as methods for multi-robot coordination using advanced neural network techniques. The combination of contributions in physical robot systems and robotic learning methods reflects a hybrid research strategy spanning mechanical and software systems engineering.
M. Yim;Wei-Min Shen;B. Salemi;D. Rus
M. Yim;D.G. Duff;K.D. Roufas
Mark R. Tremblay;Mark H. Yim
Mark Yim;Kimon Roufas;David Duff;Ying Zhang
M. Yim;Ying Zhang;D. Duff
M. Yim;Ying Zhang;K. Roufas;D. Duff
J.W. Suh;S.B. Homans;M. Yim
Mark Yim;Wei-Min Shen;Behnam Salemi;Daniela Rus
Mark H. Yim;Wei-min Shen;Benham Salemi;Daniela Rus
Mark Yim
Mark Yim;Ying Zhang;John Lamping;Eric Mao
P. Caloud;Wonyun Choi;J.-C. Latombe;C. Le Pape
James F. Kramer;Mark H. Yim;Marc R. Tremblay;Daniel H. Gomez
M. Yim
Mark Yim;Ying Zhang;David Duff
Jay Davey;Ngai Kwok;Mark Yim
Jimmy Sastra;Sachin Chitta;Mark Yim
Markus Fromherz;David Biegelsen;Mark Yim;Kimon Roufas
S. Vassilvitskii;M. Yim;J. Suh
Jungwon Seo;Jamie Paik;Mark Yim
David G. Duff;Mark Yim
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