R
Rohan Basu Roy
Researcher at Northeastern University
Publications - 18
Citations - 316
Rohan Basu Roy is an academic researcher from Northeastern University. The author has contributed to research in topics: Computer science & Wavelet. The author has an hindex of 5, co-authored 14 publications receiving 123 citations. Previous affiliations of Rohan Basu Roy include National Institute of Fashion Technology & University of Calcutta.
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Journal ArticleDOI
A review on sensor based monitoring and control of friction stir welding process and a roadmap to Industry 4.0
TL;DR: In this article, a case study has also been presented to introduce the readers with the behavior of some of the signals, and semantic utilization of the processing techniques in FSW has been proposed.
Journal ArticleDOI
Digital twin: current scenario and a case study on a manufacturing process
Rohan Basu Roy,Debasish Mishra,Surjya K. Pal,Tapas Chakravarty,Satanik Panda,M. Girish Chandra,Arpan Pal,Prateep Misra,Debashish Chakravarty,Sudip Misra +9 more
TL;DR: A model for implementing DT in a factory has been proposed and a state-of-the-art review on various DTs with their application areas is created.
Journal ArticleDOI
Weld defect identification in friction stir welding through optimized wavelet transformation of signals and validation through X-ray micro-CT scan
Rohan Basu Roy,Alekhya Ghosh,Soham Bhattacharyya,Raju Prasad Mahto,Kanchan Kumari,Surjya K. Pal,Srikanta Pal +6 more
TL;DR: In this paper, a discrete wavelet transform (DWT) was applied for detection of the defects in the weld sample for real-time Internet of Things (IoT)-based remote welding process.
Proceedings ArticleDOI
Bliss: auto-tuning complex applications using a pool of diverse lightweight learning models
TL;DR: Bliss as discussed by the authors is a solution for auto-tuning parallel applications without requiring apriori information about applications, domain-specific knowledge, or instrumentation, and demonstrates how to leverage a pool of Bayesian Optimization models to find the near-optimal parameter setting.
Proceedings ArticleDOI
IceBreaker: warming serverless functions better with heterogeneity
TL;DR: IceBreaker is the first technique to employ and leverage the idea of mixing expensive and cheaper nodes to improve both service time and keep-alive cost for serverless functions -- opening up a new research avenue of serverless computing on heterogeneous servers for researchers and practitioners.