V.G. Saranya | Engineering | Best Researcher Award

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Mrs. V.G. Saranya | Engineering | Best Researcher Award

Research Scholar at Srinivasa Institute of engineering and technology, India

V.G. Saranya ๐ŸŽ“ is a dedicated research scholar at SRM Institute of Science & Technology ๐Ÿ›๏ธ. She earned her B.E. in Electronics and Communication Engineering from Srinivasa Institute of Engineering and Technology ๐Ÿ”ง and her M.E. in Embedded System Technologies from Anna University, Guindy Campus ๐Ÿ–ฅ๏ธ. Currently pursuing her Ph.D. ๐Ÿ“š, her research explores Wireless Sensor Networks ๐ŸŒ, communication systems ๐Ÿ“ก, security frameworks ๐Ÿ”’, and machine learning ๐Ÿค–. With a passion for innovation, she has developed models that improve localization, secure DDoS detection, and healthcare analytics ๐Ÿ’ก. She actively contributes to smart and sustainable tech solutions ๐ŸŒฑ.

Professional Profile:

Scopus

๐Ÿ”น Education & Experience

  • ๐ŸŽ“ B.E. in Electronics and Communication Engineering โ€“ Srinivasa Institute of Engineering and Technology, Anna University

  • ๐ŸŽ“ M.E. in Embedded System Technologies โ€“ College of Engineering, Guindy, Anna University (2016)

  • ๐Ÿงช Ph.D. in Progress โ€“ SRM Institute of Science & Technology

  • ๐Ÿ‘ฉโ€๐Ÿ’ป Research Experience โ€“ Wireless Sensor Networks, Communication Systems, Network Security & Machine Learning

  • ๐Ÿง  Technical Expertise โ€“ Hybrid models, IoT-RFID integration, DDoS prevention systems, clustering algorithms

๐Ÿ”น Professional Development

V.G. Saranya has continuously advanced her professional journey through impactful research and interdisciplinary innovations ๐Ÿง . She has combined evolutionary algorithms with deep learning architectures to improve localization and network defense systems โš™๏ธ๐Ÿ›ก๏ธ. Her active use of tools like Tableau ๐Ÿ“Š and predictive modeling in healthcare monitoring demonstrates her commitment to societal welfare โค๏ธ๐Ÿฅ. Saranya also integrates IoT with sustainable frameworks for lifecycle management ๐ŸŒฟ๐Ÿ”— and develops energy-efficient routing protocols in WSNs ๐Ÿ”‹๐Ÿ“ถ. She regularly engages in academic conferences, technical workshops, and collaborative research initiatives to stay ahead in her domain and contribute meaningfully to the tech community ๐Ÿ‘ฉโ€๐Ÿ”ฌ๐Ÿค.

๐Ÿ”น Research Focus Categoryย 

V.G. Saranyaโ€™s research lies at the intersection of Wireless Sensor Networks (WSNs) ๐Ÿ“ก, Cybersecurity ๐Ÿ”, Machine Learning ๐Ÿค–, and Smart Healthcare Analytics ๐Ÿฅ. Her work enhances real-time localization, anomaly detection, and routing in distributed networks through hybrid AI algorithms ๐ŸŒ๐Ÿง . With a strong inclination toward sustainable and intelligent systems, she introduces energy-efficient clustering and secure data protocols for IoT-driven environments ๐Ÿ”‹๐ŸŒฟ. Her innovations span across interdisciplinary domainsโ€”merging technology with social impact, especially in healthcare and infrastructure resilience ๐Ÿฅ๐Ÿ—๏ธ. Saranyaโ€™s focus is on scalable, adaptive, and secure systems for modern, connected environments ๐Ÿš€๐Ÿ“ฒ.

๐Ÿ”น Awards & Honorsย 

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  • ๐Ÿ… Received Best Paper Award at a National Conference on Emerging Technologies

  • ๐Ÿฅ‡ Recognized for Outstanding Research Contribution in IoT and WSNs by SRMIST

  • ๐ŸŽ–๏ธ Participated in Innovation Challenge Hackathon with distinction

  • ๐Ÿ† Awarded Research Grant for interdisciplinary project on Healthcare

Publication Top Notes

  • Title: TDOA-based WSN localization with hybrid covariance matrix adaptive evolutionary strategy and gradient descent distance techniques

  • Authors: V.G. Saranya, K. Sekhar, Karthik

  • Journal: Alexandria Engineering Journal (AEJ)

  • Year: 2025

  • DOI: 10.1016/j.aej.2024.12.091

Conclusion

V.G. Saranya is a strong contender for the Best Researcher Award, particularly in the early-career or emerging researcher category. Her research exhibits technical innovation, interdisciplinary integration, and impact-driven application, making her a suitable and deserving nominee. Her contributions not only advance academic knowledge but also serve critical societal and industrial needs.

Shirko Faroughi | Engineering | Best Researcher Award

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Prof. Shirko Faroughi | Engineering | Best Researcher Award

Academic at Urmia University of Technoloy, Iran

Dr. Shirko Faroughi, an esteemed Professor of Mechanical Engineering at Urmia University of Technology, Iran, specializes in Computational Mechanics, Isogeometric Analysis, and Finite Element Methods. With a Ph.D. from Iran University of Science and Technology, he has held research positions at KTH University (Sweden), Swansea University (UK), and Bauhaus University Weimar (Germany). His work spans fracture mechanics, machine learning, and 3D printing simulations. As a CICOPS Scholar at the University of Pavia, Italy, Dr. Faroughi actively collaborates on international research projects, contributing significantly to advanced numerical methods. ๐Ÿ“š๐ŸŒ

Professional Profile:

Scopus

Google Scholar

Education & Experience ๐ŸŽ“๐Ÿ“œ

  • Ph.D. in Mechanical Engineering (2010) โ€“ Iran University of Science and Technology ๐Ÿ›๏ธ

  • M.S. in Mechanical Engineering (2005) โ€“ Iran University of Science and Technology ๐Ÿ—๏ธ

  • B.S. in Mechanical Engineering (2003) โ€“ Tabriz University ๐Ÿš—

๐Ÿ”น Academic Roles

  • Professor (2020 โ€“ Present) โ€“ Urmia University of Technology ๐Ÿ‘จโ€๐Ÿซ

  • Associate Professor (2015 โ€“ 2020) โ€“ Urmia University of Technology ๐Ÿ”ฌ

  • Assistant Professor (2011 โ€“ 2015) โ€“ Urmia University of Technology ๐Ÿ“–

  • Visiting Researcher (2008 โ€“ 2009) โ€“ KTH University, Sweden ๐Ÿ‡ธ๐Ÿ‡ช

๐Ÿ”น Administrative & International Positions

  • Dean of Mechanical Engineering Department (2022 โ€“ Present) ๐Ÿข

  • CICOPS Scholar โ€“ University of Pavia, Italy (2022) ๐Ÿ‡ฎ๐Ÿ‡น

  • Research Collaborator โ€“ Swansea University, UK (2015 โ€“ Present) ๐Ÿ‡ฌ๐Ÿ‡ง

  • Research Collaborator โ€“ New Mexico State University, USA (2016 โ€“ Present) ๐Ÿ‡บ๐Ÿ‡ธ

  • Research Collaborator โ€“ Bauhaus University Weimar, Germany (2017 โ€“ Present) ๐Ÿ‡ฉ๐Ÿ‡ช

Professional Development ๐ŸŒ๐Ÿ“š

Dr. Shirko Faroughi has made remarkable contributions to mechanical engineering through computational mechanics, finite element analysis, and machine learning. His research advances superconvergent mass and stiffness matrices, isogeometric methods, phase-field methods, and energy harvesting. He also integrates AI-driven techniques to enhance engineering simulations. His collaborations span Europe and the U.S., working with top researchers on thin structures, 3D printing, and structural dynamics. As a department dean and international collaborator, he plays a pivotal role in engineering education and research innovations, fostering global academic partnerships. ๐ŸŒŽ๐Ÿ’ก

Research Focus ๐Ÿ”๐Ÿง 

Dr. Faroughi’s research primarily revolves around Computational Mechanics and Advanced Numerical Methods, integrating Artificial Intelligence and Machine Learning for engineering applications. His work focuses on:

  • Superconvergent mass and stiffness matrices ๐Ÿ“๐Ÿ”ฌ

  • Isogeometric and finite element methods ๐Ÿ—๏ธ๐Ÿ“Š

  • Fracture mechanics and phase-field modeling ๐Ÿš๏ธ๐Ÿ’ฅ

  • Tensegrity structures and energy harvesting โšก๐Ÿ”ฉ

  • Machine learning and transfer learning in mechanical simulations ๐Ÿค–๐Ÿ“ˆ

  • 3D printing simulations and advanced material modeling ๐Ÿ–จ๏ธ๐Ÿงฉ

His research bridges traditional mechanical engineering with AI and computational techniques, pushing engineering boundaries through innovative numerical simulations. ๐Ÿš€๐Ÿ”ข

Awards & Honors ๐Ÿ†๐ŸŽ–๏ธ

  • CICOPS Scholarship โ€“ University of Pavia, Italy (2022) ๐Ÿ‡ฎ๐Ÿ‡น

  • Visiting Researcher โ€“ KTH University, Sweden (2008-2009) ๐Ÿ‡ธ๐Ÿ‡ช

  • Research Collaborator โ€“ Swansea University, UK (2015-Present) ๐Ÿ‡ฌ๐Ÿ‡ง

  • Research Collaborator โ€“ Bauhaus University Weimar, Germany (2017-Present) ๐Ÿ‡ฉ๐Ÿ‡ช

  • Research Collaborator โ€“ New Mexico State University, USA (2016-Present) ๐Ÿ‡บ๐Ÿ‡ธ

  • Dean of Mechanical Engineering Department โ€“ Urmia University of Technology (2022-Present) ๐Ÿ›๏ธ

  • Multiple Grants for Advanced Computational Mechanics Research ๐ŸŽ“๐Ÿ”

Publication Top Notes

  1. Wave Propagation in 2D Functionally Graded Porous Rotating Nano-Beams

    • Authors: S. Faroughi, A. Rahmani, M.I. Friswell

    • Published in Applied Mathematical Modelling (2020)

    • Citations: 71

    • Focus: Investigates wave propagation in porous nano-beams using a general nonlocal higher-order beam theory, considering functionally graded materials and rotation effects.

  2. Vibration of 2D Imperfect Functionally Graded Porous Rotating Nanobeams

    • Authors: A. Rahmani, S. Faroughi, M.I. Friswell

    • Published in Mechanical Systems and Signal Processing (2020)

    • Citations: 54

    • Focus: Examines vibration behavior of imperfect functionally graded porous rotating nanobeams based on a generalized nonlocal theory.

  3. Non-linear Dynamic Analysis of Tensegrity Structures Using a Co-Rotational Method

    • Authors: S. Faroughi, H.H. Khodaparast, M.I. Friswell

    • Published in International Journal of Non-Linear Mechanics (2015)

    • Citations: 47

    • Focus: Develops a co-rotational method for analyzing nonlinear dynamics of tensegrity structures.

  4. Physics-Informed Neural Networks for Solute Transport in Heterogeneous Porous Media

    • Authors: S.A. Faroughi, R. Soltanmohammadi, P. Datta, S.K. Mahjour, S. Faroughi

    • Published in Mathematics (2023)

    • Citations: 40

    • Focus: Uses physics-informed neural networks (PINNs) with periodic activation functions to model solute transport in heterogeneous porous media.

  5. Nonlinear Transient Vibration of Viscoelastic Plates Using a NURBS-Based Isogeometric HSDT Approach

    • Authors: E. Shafei, S. Faroughi, T. Rabczuk

    • Published in Computers & Mathematics with Applications (2021)

    • Citations: 30

    • Focus: Investigates nonlinear transient vibrations of viscoelastic plates using an isogeometric high-order shear deformation theory (HSDT) approach.