ASME

Journal of Computing and Information Science in Engineering

Atul 
Thakur, Ph.D.
Atul Thakur

Areas of Interest

ADDITIVE MANUFACTURING
COMPUTER-AIDED DESIGN
COMPUTER-AIDED MANUFACTURING
DATA-DRIVEN ENGINEERING APPLICATIONS
GPU COMPUTING FOR DESIGN AND MANUFACTURING
MACHINE LEARNING FOR ENGINEERING APPLICATIONS
VIRTUAL AND AUGMENTED REALITY
Indian Institute of Technology Patna, India
Atul Thakur is an Associate Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Patna. His research interest is broadly in the area of robotics, automation, and additive manufacturing. He has been actively engaged in the research involving the design, motion planning, and control of bio-inspired robots, application of robotics in the area of solid waste management, and selective micromanipulation of biological cells using magnetic microrobots. He received a Ph.D. degree in mechanical engineering from the University of Maryland, College Park, Master of Technology (M.Tech.) degree in manufacturing engineering from the Indian Institute of Technology Bombay, and Bachelor of Engineering (B.E.) degree in production engineering from the University of Mumbai. Atul is a recipient of the 2013 Best Dissertation Award from ASME – CIE Division. He received the Elsevier Journal of Computer-Aided Design 2012 most cited paper award. He is also a member of the American Society of Mechanical Engineers (ASME) since 2009 and Institute of Electrical and Electronics Engineers (IEEE) since 2011.

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