Dr. Shonak Bansal
Also known as: Dr. Bansal
Chandigarh University, Punjab Engineering College
0000-0002-6551-6011
About
Shonak Bansal received a Doctor of Philosophy (Ph.D.) degree from the Punjab Engineering College (Deemed to be University), Chandigarh, India, in Graphene- based Photodetectors. He is an Associate Professor with the Electronics and Communication Engineering Department at Chandigarh University, Mohali, India. His areas of research interest are Nanophotonics, Modeling of photodetectors, Graphene-based photodetectors, Mercury Cadmium telluride based infrared photodetectors, ZnO nanowires, Solar Cells, Optical communication, Soft-computing algorithms, and Nature-inspired optimization algorithms. He has published more than 90 publications in various reputed Journals and National/International Conferences. He has published 11 book chapters and 03 books. He has contributed as a Peer Reviewer for prestigious publishers. He is serving as an Academic Editor for Wiley, Scientific Reports, and PLOS One Journals. He is also a Topical Advisory Panel Member for the Micromachines (MDPI) Journal. He was awarded the Coursera Faculty Excellence Award for exceptional performance and outstanding progress in 2022 and the Best Researcher Award for International Research Awards on Quantum Physics and Quantum Technologies for his contribution and honourable achievement in innovative research in 2023. He has received the IoP (Institute of Physics) trusted Reviewer and Outstanding Reviewer award in recognition of an exceptionally high level of peer review competency in 2020, 2022, and 2024. He has achieved the India Top Cited Award 2022 in Materials as an author of the top 1% most-cited papers in IoP Publishing’s portfolio of journals from 2019-2021. He has also awarded as a Top 2% 2022 and 2025 Scientists List by Elsevier & Stanford University.
Employment
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Chandigarh University Associate Professor2020 - Present
Education
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Punjab Engineering College PhD2015 - 2021
Projects & Funding
Projects & funding information is unavailable.
Publications (69)
- Graphene-based InSb/AlSb/GaAs heterostructure infrared photodetector with machine learning-assisted TCAD analysis Save
- Advancing waste management through explainable artificial intelligence for real-time detection and classification of bio-medical waste using faster mask recurrent convolutional neural networks Save
- Gas Sensing Technologies for Rare Earth-Doped Metal Oxide Nanostructures: Advances in Energy Harvesting and Environmental Sensing Save
- Integrated quantum-classical hybrid architectures for robust lung lesion segmentation in volumetric CT video data samples Save
- Machine learning driven design and optimization of broadband metamaterial absorber for terahertz applications Save
- High-isolation coradiator-based UWB MIMO antenna for on-body IoT applications Save
- Enhancing environmental sustainability through real-time bio-waste detection using YOLOv6-CSP and relevance vector machine for improved waste management Save
- Design and TCAD analysis of few-layer graphene/ZnO nanowires heterojunction-based photodetector in UV spectral region Save
- Optimized Ensemble Model to Predict the Compatibility of Automobiles With Hybrid Electric Vehicles Save
- Author Correction: Design and TCAD analysis of few-layer graphene/ZnO nanowires heterojunction-based photodetector in UV spectral region Save