ASME

Journal of Computing and Information Science in Engineering

Krishnanand 
Kaipa, Ph.D.
Krishnanand Kaipa

Areas of Interest

AUTONOMOUS SYSTEMS
BIO-INSPIRED COMPUTING
COLLABORATIVE ROBOTICS
MACHINE LEARNING FOR ENGINEERING APPLICATIONS
ROBOTICS FOR ADVANCED MANUFACTURING
SWARM INTELLIGENCE
Old Dominion University
Dr. Krishnanand Kaipa is a tenured Associate Professor in the Department of Mechanical and Aerospace Engineering at the Old Dominion University. Dr. Kaipa directs the Collaborative Robotics & Adaptive Machines (CRAM) Laboratory where his group actively conducts research in diverse fields including swarm intelligence, autonomous systems, human-robot collaboration, bio-inspired robotics, surgical robotics, and robotics in education. His research has received federal funding from National Science Foundation and Office of Naval Research. Dr. Kaipa received his BE (Hons.) in Electrical Engineering from the Birla Institute of Technology and Science, Pilani and his master’s and PhD degrees from the Indian Institute of Science, Bangalore. He pursued postdoctoral studies at the University of Vermont and University of Maryland, where he was also a research assistant professor. Dr. Kaipa and his PhD advisor co-developed glowworm swarm optimization (GSO), a novel swarm intelligence algorithm that is recently gaining traction in the research community, with diverse applications ranging from multimodal optimization and clustering to mobile sensor networks and swarm robotics. He has published one book on GSO and more than eighty papers in journals, book chapters, and refereed conference proceedings and has been awarded one US patent. He received best master thesis and best PhD thesis awards, best paper awards in international conferences, outstanding book chapter award, and outstanding teaching award for a graduate course at University of Maryland. Dr. Kaipa is a member of American Society of Mechanical Engineers (ASME), Institute of Electrical and Electronics Engineers (IEEE), and American Society of Engineering Education (ASEE). He currently serves as the Associate Editor for ASME Journal of Computing and Information Science in Engineering, IEEE Robotics and Automation Letters, and IEEE International Conference on Robotics and Automation.

Return to the Editorial Board

More To Explore

Announcements

Special Issue on Geometric Data Processing and Analysis for Advanced Manufacturing

Geometric information, such as three-dimensional (3D) shapes and network topologies, has been increasingly explored in manufacturing research. For example, characterizing geometric information in 3D-printed parts, in-situ or ex-situ, opens opportunities for defect detection, quality improvement, and product customization. However, geometric data mining remains critically challenging. Geometric information is embedded in complex data structures, such as 3D point clouds, graphs, meshes, voxels, high-dimensional images, and tensors, which possess challenges for analysis due to their high-dimensionality, high-volume, unstructured, multimodality characteristics. Additional challenges stem from compromised data quality (e.g., noisy and incomplete data), the need for registration, etc.

Announcements

2023 Reviewer’s Recognition

The Editor and Editorial Board of the Journal of Computing and Information Science in Engineering would like to thank all of the reviewers for volunteering their expertise and time reviewing manuscripts in 2023. Serving as reviewers for the journal is a critical service necessary to maintain the quality of our publication and to provide the authors with a valuable peer review of their work.

LATEST PAPERS

Latest Papers from ASME's Digital Collection