Yogesh Shankar | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Yogesh shankar
Infineon Technologies Asia Pacific, Singapore

Yogesh shankar
Affiliation Infineon Technologies Asia Pacific
Country Singapore
Scopus ID 57215433281
Documents 2
Citations 21
h-index 2
Subject Area Engineering
Event International Academic Excellence Awards

Yogesh shankar is an engineering researcher associated with Infineon Technologies Asia Pacific in Singapore. The supplied indexed record identifies research involving radar-based sensing, non-intrusive motion recognition, and deformable convolutional neural networks. The available bibliometric information reports two documents, 21 citations, and an h-index of 2. The documented publication record provides a focused example of applying deep-learning methods to sensing and recognition problems. [1]

Abstract

The supplied research profile concerns engineering applications of intelligent sensing and machine learning. Its identified publication, presented at the 18th IEEE International Conference on Machine Learning and Applications in 2019, investigates radar-based non-intrusive fall motion recognition using a deformable convolutional neural network. Such work combines radar sensing with deep-learning-based recognition, addressing the computational interpretation of motion without relying on direct physical contact. [2]

Keywords

Engineering; radar sensing; fall recognition; motion recognition; deep learning; convolutional neural networks; deformable convolution; non-intrusive sensing; machine learning; intelligent systems.

Introduction

Radar-based sensing provides a means of observing movement without requiring conventional wearable or contact-based instrumentation. Within this context, machine learning can be used to extract patterns from radar-derived information and classify specific human activities. The documented work by yogesh shankar and collaborators applies a deformable convolutional neural network to fall-motion recognition, placing the research at the intersection of radar sensing, signal interpretation, and artificial intelligence. [2]

Research Profile

The stated subject area is Engineering, with the available publication evidence specifically connected to machine learning and sensing applications. The supplied profile reports two documents, 21 citations, and an h-index of 2. These bibliometric indicators represent the supplied database snapshot and may change as additional publications and citations are indexed. [1]

Research Contributions

  • Investigation of radar-based non-intrusive sensing for human fall-motion recognition. [2]
  • Application of deformable convolutional neural networks to motion-recognition tasks. [2]
  • Integration of radar sensing and deep-learning-based computational recognition within an engineering research context.

Publications

Radar-based non-intrusive fall motion recognition using deformable convolutional neural network was published as a conference paper in the Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). The listed authors are Y. Shankar, Yogesh Shankar, Souvik Hazra, and Avik Santra. The supplied record reports 12 citations for this publication. [2]

Research Impact

The supplied Scopus information reports 21 citations across two documents and an h-index of 2. The identified conference paper accounts for 12 citations in the supplied results. Citation counts are dynamic bibliometric measures and can differ between indexing services; therefore, they are best interpreted as indicators of documented scholarly visibility rather than as a complete measure of research significance. [1] [2]

Award Suitability

The documented publication provides evidence of research activity relevant to an Innovative Research Award within the Engineering subject area. Its focus on radar-based non-intrusive sensing and deformable convolutional neural networks represents an application of contemporary computational methods to human-motion recognition. Consideration for an award should be made alongside the complete research record and the applicable criteria of the International Academic Excellence Awards.

Conclusion

yogesh shankar’s supplied academic record demonstrates focused research at the intersection of engineering, radar sensing, and machine learning. The documented work on non-intrusive fall-motion recognition illustrates the use of deformable convolutional neural networks in an applied sensing context. The available bibliometric indicators and publication evidence provide a concise basis for academic recognition within the International Academic Excellence Awards framework.

References

  1. Elsevier. (n.d.). Scopus author details: Yogesh Shankar, Author ID 57215433281. Scopus. The supplied Scopus record reports two documents, 21 citations, and an h-index of 2.
  2. Shankar, Y., Shankar, Y., Hazra, S., & Santra, A. (2019). Radar-based non-intrusive fall motion recognition using deformable convolutional neural network. Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). The supplied record reports 12 citations.
  3. IEEE. (2019). 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). Conference publication record associated with the documented research.
  4. International Academic Excellence Awards. (n.d.). Academic Excellence Awards.
    https://academicexcellenceawards.com/

Qinnan Chen | Engineering | Best Researcher Award

Published on by Academic Excellence

Assoc. Prof. Dr. Qinnan Chen | Engineering | Best Researcher Award

Assoc. Prof. Dr. Qinnan Chen, Xiamen University, China

Dr. Qinnan Chen is an Associate Professor at the Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, China. With a Ph.D. in Optical Engineering from Tianjin University, Dr. Chen specializes in cutting-edge research in light-matter interactions, micro/nano-structure evolution, and multi-physical perception technologies. His work is at the forefront of extreme-environment photoelectric sensing and micro-nano manufacturing for aerospace and renewable energy sectors. Over his academic career, Dr. Chen has led prestigious national and provincial research projects and published prolifically in top-tier journals. His innovations in sensor design and microfabrication have garnered significant citations, demonstrating a high impact on the field. As a senior member of multiple scientific societies and an active editor, he contributes broadly to the scientific community. Dr. Chen’s commitment to interdisciplinary excellence continues to inspire emerging scholars and drive technological breakthroughs in advanced engineering systems.

Profile

Scopus

Google Scholar

🌟 Assessment of Dr. Qinnan Chen, Ph.D. – Suitability for the Research for Best Researcher Award

Dr. Qinnan Chen, currently serving as an Associate Professor at the Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, exemplifies the caliber of an ideal candidate for the Research for Best Researcher Award. His career reflects sustained excellence in micro/nano-scale science and technology, particularly in the areas of photoelectric sensing, micro-nano manufacturing, and extreme-environment sensor applications. With over 1,500 citations and an impressive H-index of 26, his scientific influence and research productivity are significant.

Dr. Chen’s academic trajectory—from Ph.D. in Optical Engineering to postdoctoral and faculty appointments—demonstrates a commitment to innovation and interdisciplinary application. His work under China’s National Natural Science Foundation and Major Provincial Science and Technology Projects speaks to both the national and regional significance of his research. Furthermore, his active role in courses related to electrical engineering, optics, and nano-manufacturing shows a commendable dedication to cultivating future researchers.

🎓 Education 

Dr. Qinnan Chen received his Ph.D. in Optical Engineering from Tianjin University in 2015. His doctoral research laid a robust foundation in photonics, fiber sensing, and optical instrumentation, equipping him with advanced theoretical and practical skills in nano-optics and sensor systems. He previously earned his bachelor’s degree in Optoelectronic Information Science and Engineering through a joint program between Tianjin University and Nankai University in 2010. This program emphasized photonics, electronics, and material sciences, shaping his early interest in micro/nano systems and their applications. The multidisciplinary training Dr. Chen acquired has been instrumental in his ability to bridge engineering with materials science, enabling him to pursue high-impact research in extreme-environment sensing and manufacturing. His academic pathway reflects a strong emphasis on precision instrumentation, smart materials, and advanced fabrication technologies, forming the backbone of his current innovative work in high-temperature sensors and aerospace micro-devices.

💼 Professional Experience 

Dr. Qinnan Chen currently serves as Associate Professor at Xiamen University (2023–Present), where he continues his groundbreaking research on extreme-environment sensors and micro-nano devices. Prior to this role, he was an Assistant Professor (2018–2023) and earlier, a Postdoctoral Fellow (2015–2018) at the same university. His academic journey is rooted in advancing microfabrication methods and multi-functional sensors for aerospace and energy applications. Dr. Chen has been the principal investigator on major national grants including projects from the National Natural Science Foundation of China and the National Key R&D Program. He also holds various part-time academic roles, such as Editor for Nanotechnology and Precision Engineering and Technical Observer in national standardization committees. Alongside teaching core engineering courses, he actively mentors undergraduate and postgraduate students. Dr. Chen’s leadership in research and education is helping shape the next generation of micro-nano engineers and driving the future of intelligent sensing technology.

🏅 Awards and Recognition 

Dr. Qinnan Chen has received multiple prestigious awards recognizing his contributions to engineering innovation and education. Notably, he was honored with the First Prize for Science and Technology Progress of Fujian Province (2022) and Second Prize for Science and Technology Progress of Xiamen City (2020). He earned the Second Prize for Outstanding Academic Papers in Natural Sciences in Fujian Province (2020), acknowledging his research excellence. Dr. Chen was nominated for the 2022 MINE Outstanding Young Scientist Award and won Second Prize in Fujian Province’s Young Teachers’ Electrical Engineering Competition (2023). As a high-level talent recognized by both Fujian Province and Xiamen City, he is deeply engaged in national and provincial research initiatives. He is a senior member of the Chinese Micro-Nano Technology Society, the Chinese Optical Society, and more. His accolades reflect both scholarly distinction and leadership in China’s evolving engineering landscape.

🌍 Research Skills On Engineering

Dr. Qinnan Chen’s research expertise lies in light-matter interaction, property-structure evolution, multi-physical perception, and conformal microfabrication. He has developed state-of-the-art polymer-derived ceramic sensors for high-temperature applications, with successful implementations in aerospace and new energy systems. His skillset spans 3D printing of ceramic thermistors, thin-film strain and heat flux sensors, and direct ink writing of nanomaterials. He exhibits mastery in extreme-environment testing, plasma-based devices, and micro-nano manufacturing. As a corresponding author of numerous high-impact publications, he merges theory and application, consistently pushing boundaries in sensing technologies. Dr. Chen is adept at managing interdisciplinary projects across materials science, optics, mechanical engineering, and thermal systems. His research continues to advance China’s strategic capabilities in smart sensing and microscale device innovation. With over 1500 citations and an h-index of 26, he exemplifies excellence in high-impact engineering research.

📖   Publication Top Notes

  • A high-efficiency multiple events discrimination method in optical fiber perimeter security system
    Authors: K Liu, M Tian, T Liu, J Jiang, Z Ding, Q Chen, C Ma, C He, H Hu, X Zhang
    Journal of Lightwave Technology, 33 (23), 4885-4890
    Citations: 84 | Year: 2015

  • An elimination method of polarization-induced phase shift and fading in dual Mach–Zehnder interferometry disturbance sensing system
    Authors: Q Chen, T Liu, K Liu, J Jiang, Z Ding, L Zhang, Y Li, L Pan, C Ma
    Journal of Lightwave Technology, 31 (19), 3135-3141
    Citations: 73 | Year: 2013

  • 3D printed microfluidic chip for multiple anticancer drug combinations
    Authors: X Chen, H Chen, D Wu, Q Chen, Z Zhou, R Zhang, X Peng, YC Su, D Sun
    Sensors and Actuators B: Chemical, 276, 507-516
    Citations: 63 | Year: 2018

  • An improved positioning algorithm with high precision for dual Mach–Zehnder interferometry disturbance sensing system
    Authors: Q Chen, T Liu, K Liu, J Jiang, Z Shen, Z Ding, H Hu, X Huang, L Pan, …
    Journal of Lightwave Technology, 33 (10), 1954-1960
    Citations: 60 | Year: 2015

  • Note: Improving spatial resolution of optical frequency-domain reflectometry against frequency tuning nonlinearity using non-uniform fast Fourier transform
    Authors: Z Ding, T Liu, Z Meng, K Liu, Q Chen, Y Du, D Li, XS Yao
    Review of Scientific Instruments, 83 (6)
    Citations: 56 | Year: 2012

  • Cryogenic temperature measurement using Rayleigh backscattering spectra shift by OFDR
    Authors: Y Du, T Liu, Z Ding, Q Han, K Liu, J Jiang, Q Chen, B Feng
    IEEE Photonics Technology Letters, 26 (11), 1150-1153
    Citations: 55 | Year: 2014

  • High-temperature electrical properties of polymer-derived ceramic SiBCN thin films fabricated by direct writing
    Authors: C Wu, X Pan, F Lin, Z Cui, X Li, G Chen, X Liu, Y He, G He, Z Hai, Q Chen, …
    Ceramics International, 48 (11), 15293-15302
    Citations: 49 | Year: 2022

  • TiB₂/SiCN thin-film strain gauges fabricated by direct writing for high-temperature application
    Authors: C Wu, X Pan, F Lin, Z Cui, Y He, G Chen, Y Zeng, X Liu, Q Chen, D Sun, …
    IEEE Sensors Journal, 22 (12), 11517-11525
    Citations: 46 | Year: 2022

  • Direct write of a flexible high-sensitivity pressure sensor with fast response for electronic skins
    Authors: Y Luo, D Wu, Y Zhao, Q Chen, Y Xie, M Wang, L Lin, L Wang, D Sun
    Organic Electronics, 67, 10-18
    Citations: 44 | Year: 2019

  • Polymer-derived ceramic thin-film temperature sensor
    Authors: Z Cui, X Li, X Pan, G Chen, Y Li, J Lin, C Wu, X Liu, T Yang, Z Hai, G He, …
    Sensors and Actuators A: Physical, 332, 113038
    Citations: 43 | Year: 2021

Farzad Pashmforoush | Engineering | Best Researcher Award

Published on by Academic Excellence

Assoc. Prof. Dr. Farzad Pashmforoush | Engineering | Best Researcher Award

Assoc. Prof. Dr. Farzad Pashmforoush, University of Maragheh, Iran

Farzad Pashmforoush is a distinguished Associate Professor at the University of Maragheh, specializing in Mechanical Engineering. Born on July 31, 1987, he has dedicated his career to advancing research in composite materials, artificial intelligence, finite element methods, and non-destructive testing. His academic journey began at the University of Tabriz, where he ranked first in his Bachelor’s program. He continued his education at Amirkabir University of Technology, earning both his Master’s and PhD with exceptional grades. Dr. Pashmforoush’s contributions to the field are reflected in his extensive research on damage identification in composite structures, optimization techniques, and material characterization. With numerous high-impact publications, citations, and an h-index of 9, his work has influenced academia and industry alike. His passion for innovation and excellence has earned him significant recognition, making him a leading figure in mechanical engineering research.

Professional Profile

Google Scholar

Suitability for the Research for Best Researcher Award – Farzad Pashmforoush

Dr. Farzad Pashmforoush is a distinguished researcher and academic with a strong background in mechanical engineering, particularly in areas such as composite materials, finite element method (FEM), artificial intelligence, fracture mechanics, and non-destructive testing (NDT). His academic journey reflects excellence at every level, securing top ranks during his Bachelor’s and Master’s degrees, followed by a high distinction PhD from Amirkabir University of Technology. His doctoral work on the numerical-experimental study of magnetic abrasive finishing of optical glass showcases innovative problem-solving abilities and a commitment to advancing material science and manufacturing techniques.

His research contributions are extensive and impactful, as evidenced by 26 high-quality journal publications in esteemed journals, over 400 citations, and an h-index of 9 on Google Scholar. His works span damage characterization in composite materials, deep learning for autonomous damage recognition, optimization techniques, and multiphysics simulations, demonstrating a multidisciplinary approach to mechanical engineering. Additionally, his application of artificial intelligence in non-destructive evaluation and advanced material testing methods showcases his ability to integrate cutting-edge technology into engineering research.

🎓 Education

Farzad Pashmforoush’s academic journey began at the University of Tabriz, where he completed his Bachelor of Science in Mechanical Engineering in 2009, ranking first with a grade of 18.86. He continued his education at Amirkabir University of Technology, earning a Master of Science in 2011, with a thesis on damage modes in composite materials, also achieving first rank. He further advanced his studies, obtaining a Ph.D. in Mechanical Engineering from the same university in 2015. His doctoral thesis focused on numerical-experimental studies of magnetic abrasive finishing of optical glass. Throughout his academic career, Farzad maintained an outstanding academic performance, receiving top grades and contributing to innovative research. His advanced training and in-depth knowledge of mechanical engineering have set the foundation for a successful academic and research career.

💼 Professional Experience

Farzad Pashmforoush has had a distinguished academic career, with extensive experience as an Associate Professor in Mechanical Engineering at the University of Maragheh. He has taught and mentored students in advanced topics such as composite materials, non-destructive testing, and fracture mechanics. His research focuses on finite element methods, artificial intelligence applications in engineering, and composite material behavior. Farzad has also collaborated with international institutions on projects involving acoustic emission techniques for damage detection in composites and the optimization of manufacturing processes. His expertise in experimental mechanics, data analysis, and numerical modeling has resulted in numerous high-impact publications. As an educator and researcher, he is dedicated to advancing engineering technology while fostering the next generation of engineers through innovative teaching and research initiatives.

🏅 Awards and Recognition

Farzad Pashmforoush has received numerous accolades throughout his career for his outstanding contributions to mechanical engineering. He was recognized as a top graduate in both his undergraduate and graduate studies, receiving the first-rank distinction at both the University of Tabriz and Amirkabir University of Technology. His research on composite materials, non-destructive testing, and fracture mechanics has earned him high citation counts and recognition from peers in the academic community. Additionally, Farzad has been acknowledged for his role in advancing mechanical engineering research and education, earning grants and research funding for innovative projects. His excellence in teaching and research, along with his impactful publications, continues to shape the future of engineering education and practice.

🌍 Research Skills On Engineering

Farzad Pashmforoush possesses a broad range of research skills, making him a leading expert in his field. His proficiency in finite element methods (FEM) allows him to model and analyze complex engineering problems, particularly in the areas of composite materials and structural analysis. Farzad’s research integrates artificial intelligence techniques, such as deep learning, to enhance the evaluation and optimization of engineering processes. His extensive use of non-destructive testing (NDT) methods, particularly acoustic emission, enables him to study material behavior and detect damage in real-time. In addition, his expertise in fracture mechanics and damage detection provides valuable insights into the durability and performance of materials. Farzad’s approach combines theoretical analysis with experimental validation, ensuring the practical application of his research in industry. His innovative use of advanced technologies and methodologies has garnered widespread recognition in the engineering community.

📖 Publication Top Notes 

  • “Autonomous damage recognition in visual inspection of laminated composite structures using deep learning”

    • Authors: S. Fotouhi, F. Pashmforoush, M. Bodaghi, M. Fotouhi
    • Journal: Composite Structures
    • Citation: 87
    • Year: 2021

  • “Characterization of composite materials damage under quasi-static three-point bending test using wavelet and fuzzy C-means clustering”

    • Authors: M. Fotouhi, H. Heidary, M. Ahmadi, F. Pashmforoush
    • Journal: Journal of Composite Materials
    • Citation: 86
    • Year: 2012

  • “Damage classification of sandwich composites using acoustic emission technique and k-means genetic algorithm”

    • Authors: F. Pashmforoush, R. Khamedi, M. Fotouhi, M. Hajikhani, M. Ahmadi
    • Journal: Journal of Nondestructive Evaluation
    • Citation: 83
    • Year: 2014

  • “Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithm”

    • Authors: F. Pashmforoush, M. Fotouhi, M. Ahmadi
    • Journal: Journal of Reinforced Plastics and Composites
    • Citation: 72
    • Year: 2012

  • “Damage characterization of glass/epoxy composite under three-point bending test using acoustic emission technique”

    • Authors: F. Pashmforoush, M. Fotouhi, M. Ahmadi
    • Journal: Journal of Materials Engineering and Performance
    • Citation: 66
    • Year: 2012

  • “Influence of water-based copper nanofluid on wheel loading and surface roughness during grinding of Inconel 738 superalloy”

    • Authors: F. Pashmforoush, R. D. Bagherinia
    • Journal: Journal of Cleaner Production
    • Citation: 64
    • Year: 2018

  • “Monitoring the initiation and growth of delamination in composite materials using acoustic emission under quasi-static three-point bending test”

    • Authors: M. Fotouhi, F. Pashmforoush, M. Ahmadi, A. Refahi Oskouei
    • Journal: Journal of Reinforced Plastics and Composites
    • Citation: 64
    • Year: 2011

  • “Statistical analysis on free vibration behavior of functionally graded nanocomposite plates reinforced by graphene platelets”

    • Authors: F. Pashmforoush
    • Journal: Composite Structures
    • Citation: 48
    • Year: 2019

  • “Nano-finishing of BK7 optical glass using magnetic abrasive finishing process”

    • Authors: F. Pashmforoush, A. Rahimi
    • Journal: Applied Optics
    • Citation: 42
    • Year: 2015

  • “Interfacial characteristics and thermo-mechanical properties of calcium carbonate/polystyrene nanocomposite”

    • Authors: F. Pashmforoush, S. Ajori, H. R. Azimi
    • Journal: Materials Chemistry and Physics
    • Citation: 27
    • Year: 2020