Michael Todinov | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Michael Todinov
Oxford Brookes University,United Kingdom

Michael Todinov
Affiliation Oxford Brookes University
Country United Kingdom
Scopus ID 7004595988
Documents 111
Citations 1,122
h-index 18
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-3957-7961

Michael Todinov is an engineering researcher associated with Oxford Brookes University whose scholarly work focuses on reliability, risk, engineering design, probabilistic methods, and structural efficiency. His recent publications address domain-independent reliability improvement, lightweight structures, algebraic approaches to reliability prediction, and probabilistic interpretations of engineering inequalities.[1][2]

Abstract

Michael Todinov’s research profile centers on engineering reliability, risk reduction, probabilistic analysis, and structural design. His recent work proposes methods for improving reliability by exploiting asymmetry, balancing system components, and interpreting algebraic relationships probabilistically. Other studies investigate lightweight structures subjected to bending and the use of reverse engineering of algebraic inequalities for reliability prediction and engineering-process improvement.[1][3]

Keywords

Engineering; Reliability Engineering; Risk Analysis; Probabilistic Methods; Structural Design; Lightweight Structures; Reliability Prediction; Engineering Optimization; Algebraic Inequalities; System Reliability.

Introduction

Reliability and risk are central concerns in engineering systems because failures can affect safety, performance, cost, and service continuity. Todinov’s research addresses these concerns through analytical approaches that seek to identify relationships between system configuration, reliability, and risk. His publications span reliability theory and engineering design, providing a connection between mathematical analysis and practical engineering problems.[3][4]

Research Profile

The supplied bibliometric profile records 111 documents, 1,122 citations, and an h-index of 18. These indicators describe a substantial body of indexed scholarly output. His publication portfolio demonstrates continuity in reliability and risk research while also extending into mechanical and structural engineering applications.[1][2]

Research Contributions

  • Development of a domain-independent approach to reliability improvement and risk reduction through exploitation of asymmetry.[1]
  • Investigation of lightweight multi-element structures subjected to bending loads, with emphasis on structural configuration and efficiency.[2]
  • Application of reverse engineering of algebraic inequalities to system reliability prediction and engineering-process enhancement.[3]
  • Probabilistic interpretation of algebraic inequalities associated with reliability and risk analysis.[4]

Publications

Among the recent publications is A new domain-independent method for improving reliability and reducing risk based on exploiting asymmetry, published in Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability in December 2025.[1] A related 2025 contribution examines lightweight structures composed of multiple elements loaded in bending.[2] Earlier work in IEEE Transactions on Reliability considers algebraic inequalities for system reliability prediction, while a 2023 study develops their probabilistic interpretation.[3][4]

Research Impact

The reported citation count and h-index indicate sustained scholarly visibility. The research is also notable for connecting reliability theory with engineering design problems, including structural loading and system configuration. The domain-independent orientation of recent reliability research may support application across different engineering contexts where risk and failure probabilities must be assessed systematically.[1][4]

Award Suitability

The documented publication record, citation indicators, and sustained focus on reliability and risk provide a substantive basis for consideration for an Innovative Research Award. His work combines analytical methods with engineering applications and addresses questions concerning system performance, structural efficiency, reliability prediction, and risk reduction. These characteristics align with recognition criteria emphasizing methodological innovation and meaningful engineering research contributions.

Conclusion

Michael Todinov’s research profile reflects sustained contributions to engineering reliability, risk analysis, probabilistic methods, and structural design. His recent publications demonstrate continued development of analytical approaches to reliability improvement alongside applications in mechanical engineering. The available bibliometric and publication information supports his consideration within an academic recognition framework focused on innovative engineering research.

References

  1. Todinov, M. (2025). A new domain-independent method for improving reliability and reducing risk based on exploiting asymmetry. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability.
    https://doi.org/10.1177/1748006X251324081
  2. Todinov, M. (2025). Designing light-weight structures consisting of multiple elements loaded in bending. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.
    https://doi.org/10.1177/09544062251365722
  3. Todinov, M. (2024). Reverse Engineering of Algebraic Inequalities for System Reliability Predictions and Enhancing Processes in Engineering. IEEE Transactions on Reliability.
    https://doi.org/10.1109/TR.2023.3315662
  4. Todinov, M. (2023). Probabilistic interpretation of algebraic inequalities related to reliability and risk. Quality and Reliability Engineering International.
    https://doi.org/10.1002/qre.3345
  5. Todinov, M. (2023). Improving reliability by increasing the level of balancing and by substitution. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.
    https://doi.org/10.1177/09544062221132419
  6. Elsevier. (n.d.). Scopus author details: Michael Todinov, Author ID 7004595988. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7004595988

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/

Sherief Hashima | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Sherief Hashima
RIKEN Center for Advanced Intelligence Project,Japan

Sherief Hashima, RIKEN-AIP, Japan, is recognized in the context of the International Academic Excellence Awards for research activity spanning engineering, wireless communications, intelligent networks, signal processing, and emerging communication technologies.

Sherief Hashima
Affiliation RIKEN Center for Advanced Intelligence Project
Country Japan
Scopus ID 55849342400
Documents 88
Citations 1,113
h-index 19
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-4443-7066

Abstract

Sherief Hashima’s documented publication record covers contemporary engineering problems involving wireless networks, intelligent communication systems, signal analysis, Internet of Things technologies, and next-generation mobile communications. Recent publications address neutron/gamma pulse-shape discrimination using scalogram imaging and pretrained convolutional neural networks, mobility management for unified 6G networks, integrated sensing and communications, reconfigurable intelligent surface-assisted wireless information and power transfer, and UAV-assisted vehicular communications. [1][2]

Keywords

Engineering; wireless communications; 6G; signal processing; artificial intelligence; Internet of Things; ISAC; RIS; UAV communications; beamforming; mobility management.

Introduction

Research in advanced communication engineering increasingly combines signal processing, machine learning, network optimization, and heterogeneous wireless infrastructure. The supplied publication record places Hashima’s recent work within this multidisciplinary engineering environment, with studies addressing both methodological developments and surveys of emerging communication architectures. [3]

Research Profile

The supplied profile records 88 documents, 1,113 citations, and an h-index of 19, associated with Scopus author ID 55849342400. These figures are bibliometric indicators and can change as databases update their indexing and citation records.

Research Contributions

  • Applied scalogram imaging and pretrained CNN methods to neutron/gamma pulse-shape discrimination. [1]
  • Examined mobility management challenges and future directions in three-dimensional unified 6G networks. [2]
  • Surveyed ISAC integration with emerging wireless network technologies and RIS-assisted SWIPT architectures. [3][4]

Publications

  • Neutron/Gamma Pulse Shape Discrimination via Scalogram Imaging and Pretrained CNN, Signals, 2026. DOI. [1]
  • Mobility management in 3D unified 6G networks: Challenges, opportunities and future directions, ICT Express, 2026. DOI. [2]
  • ISAC Integration With Emerging Wireless Network Technologies: A Comprehensive Survey, IEEE Open Journal of the Communications Society, 2026. DOI. [3]
  • RIS-Assisted SWIPT for IoT Networks: A Survey of Architectures, Optimization, and Future Directions, 2026. DOI. [4]
  • Delay-Doppler-Based Joint mmWave Beamforming and UAV Selection in Multi-UAV-Assisted Vehicular Communications, Aerospace, 2025. DOI. [5]

Research Impact

The reported citation count and h-index provide quantitative indicators of scholarly visibility in the supplied Scopus profile. The publication set also demonstrates engagement with several active engineering themes, including 6G networks, ISAC, RIS-enabled IoT systems, machine-learning-based signal analysis, and UAV communications.

Award Suitability

The documented research themes correspond to the engineering scope of the Innovative Research Award. In particular, the combination of signal-processing methods, intelligent communication technologies, network architectures, and emerging wireless systems provides a substantive basis for consideration within an academic recognition program. This description concerns alignment between the supplied research record and the stated award category.

Conclusion

Sherief Hashima’s supplied academic profile reflects research activity across multiple areas of contemporary engineering and wireless communication. The listed publications demonstrate work on both applied signal analysis and emerging network technologies, while the reported bibliometric indicators provide additional context for the research profile.

References

  1. MDPI. (2026). Neutron/Gamma Pulse Shape Discrimination via Scalogram Imaging and Pretrained CNN. Signals.
    https://doi.org/10.3390/signals7050091
  2. Elsevier. (2026). Mobility management in 3D unified 6G networks: Challenges, opportunities and future directions. ICT Express.
    https://doi.org/10.1016/j.icte.2025.11.011
  3. IEEE. (2026). ISAC Integration With Emerging Wireless Network Technologies: A Comprehensive Survey. IEEE Open Journal of the Communications Society.
    https://doi.org/10.1109/OJCOMS.2026.3690251
  4. IEEE. (2026). RIS-Assisted SWIPT for IoT Networks: A Survey of Architectures, Optimization, and Future Directions. IEEE Open Journal of the Communications Society.
    https://doi.org/10.1109/OJCOMS.2026.3724584
  5. MDPI. (2025). Delay-Doppler-Based Joint mmWave Beamforming and UAV Selection in Multi-UAV-Assisted Vehicular Communications. Aerospace.
    https://doi.org/10.3390/aerospace12090757
  6. Elsevier. (n.d.). Scopus author details: Sherief Hashima, Author ID 55849342400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55849342400

Vidya Nandikolla | Engineering | Best Researcher Award

Published on by Academic Excellence

Best Researcher Award

Dr Vidya Nandikolla
Affiliation California State University Northridge
Country United States
Scopus ID 8339231200
Documents 25
Citations 136
h-index 5
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-4151-4783

Dr Vidya Nandikolla
California State University Northridge,United States

Dr Vidya Nandikolla is an engineering researcher affiliated with California State University Northridge in the United States. Her documented research output includes work in autonomous vehicles, robotics, brain-computer interfaces, and simultaneous localization and mapping (SLAM), reflecting an interdisciplinary interest in intelligent robotic and autonomous systems. Available bibliographic indicators record 25 documents, 136 citations, and an h-index of 5.

Abstract

Dr Vidya Nandikolla’s research profile is situated within engineering applications involving robotics, autonomous systems, human-machine interaction, and computational sensing. Her publication record includes research on a hybrid EEG-based brain-computer interface (BCI) arm manipulator controlled through ROS and work concerning autonomous vehicles and LiDAR-based localization. These topics connect sensing, control, perception, and intelligent automation, all of which are central areas of contemporary engineering research.

Keywords

Robotics; autonomous vehicles; LiDAR; SLAM; brain-computer interface; ROS; robotic control; engineering; localization; intelligent systems.

Introduction

Modern autonomous and robotic platforms depend on reliable perception, localization, control, and human-machine communication. SLAM methods allow robotic systems to estimate their position while constructing representations of an environment, while BCI technologies investigate alternative mechanisms for controlling assistive robotic devices. Nandikolla’s documented work intersects these engineering challenges, providing a research profile that combines robotics with emerging sensing and control technologies. [2]

Research Profile

The available record identifies Engineering as the principal subject area. Her research themes include ROS-enabled robotic control, EEG-based BCI systems, autonomous vehicle technologies, and LiDAR SLAM. ROS is widely used as a framework for developing modular robotic applications, making its use relevant to experimental robotics and autonomous-system research. [3]

Research Contributions

  • Research involving a hybrid EEG-based BCI arm manipulator and ROS-based robotic control.
  • Investigation of autonomous vehicle technologies, including custom battery-pack design using solar energy.
  • Evaluation of Extended Kalman Filter odometry for improving the performance of 2D LiDAR SLAM algorithms. [1]

Publications

Evaluating the Impact of Extended Kalman Filter Odometry on the Performance of 2D LiDAR SLAM Algorithms is listed as a working paper and carries. Another documented publication is Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS, published in the Journal of Robotics in 2022 and reported with five citations in the supplied record. A conference paper, Design and Analysis of an Custom Battery Pack Using Solar Energy for an Autonomous Vehicle, further demonstrates an application-oriented engineering focus.

Research Impact

The reported bibliometric record of 136 citations across 25 documents indicates measurable scholarly visibility. An h-index of 5 provides an additional bibliometric indicator of citation distribution. These metrics should be interpreted alongside publication quality, research relevance, technical contribution, and broader application potential rather than as standalone measures of research excellence. [4]

Award Suitability

Dr Vidya Nandikolla demonstrates characteristics relevant to consideration for a Best Researcher Award in Engineering, particularly through a research portfolio connecting robotics, autonomous mobility, BCI systems, and localization. The combination of published research, interdisciplinary engineering applications, and documented citation activity provides a reasonable academic basis for recognition. Final award assessment should consider the complete submitted evidence and the evaluation criteria established by the International Academic Excellence Awards.

Conclusion

Dr Vidya Nandikolla’s documented research reflects an engineering-oriented approach to robotics, autonomous systems, human-machine interfaces, and intelligent localization. Her publication activity and bibliometric indicators support recognition of sustained research engagement, while her work addresses practical challenges in emerging robotic technologies.

References

  1. Nandikolla, Vidya K. et al. (2026). Evaluating the Impact of Extended Kalman Filter Odometry on the Performance of 2D LiDAR SLAM Algorithms. Preprints.
    https://doi.org/10.20944/preprints202607.1435.v1
  2. Cadena, C. et al. (2016). Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age. IEEE Transactions on Robotics, 32(6), 1309–1332.
    https://doi.org/10.1109/TRO.2016.2624754
  3. Quigley, M. et al. (2009). ROS: an open-source Robot Operating System. ICRA Workshop on Open Source Software.
  4. Elsevier. (n.d.). Scopus author details: Vidya Nandikolla, Author ID 8339231200. Scopus.
    https://www.scopus.com/pages/authors/8339231200
  5. Nandikolla, Vidya K., and Medina Portilla, Daniel A. (2022). Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS. Journal of Robotics.
  6. Nandikolla, Vidya K. et al. Design and Analysis of an Custom Battery Pack Using Solar Energy for an Autonomous Vehicle. Conference paper.

Sumaraj S | Engineering | Academic Excellence Award

Published on by Academic Excellence

Dr. Sumaraj S | Engineering | Academic Excellence Award

Dr. Sumaraj is a Civil and Environmental Engineer with over a decade of academic and research experience, specializing in water and environmental sustainability. He holds a Ph.D. in Civil and Environmental Engineering from the University of Auckland, New Zealand, where his doctoral research contributed to advancing sustainable approaches in water and wastewater treatment systems. His strong academic foundation also includes a Master of Technology in Environmental Engineering and Management from the Indian Institute of Technology Kharagpur, where he graduated with distinction, and a Bachelor of Engineering in Civil Engineering from the National Institute of Engineering, Mysore. Dr. Sumaraj’s research interests span water and wastewater treatment engineering, sustainable technologies, nutrient contaminant remediation, carbon-based materials such as biochar and activated carbon, adsorption mechanisms, surface chemistry, analytical chemistry, and air pollution monitoring. His work reflects an interdisciplinary approach that integrates environmental science, engineering solutions, and sustainability-driven innovation, leading to peer-reviewed publications, conference presentations, and award-winning student research projects. Currently serving as an Assistant Professor in the Department of Civil Engineering at Nitte Meenakshi Institute of Technology, Bengaluru, Dr. Sumaraj is actively involved in teaching, mentoring, and academic leadership. He has designed and delivered courses in green technology, environmental sustainability, wastewater treatment, water supply engineering, and research methodology. Beyond the classroom, he plays a key role in industry–academia collaboration, skill development initiatives, and sustainability-focused training programs. A recipient of multiple scholarships and honors, including the University of Auckland Doctoral Scholarship and recognition under national and international sustainability programs, Dr. Sumaraj is also a certified Green-Belt Career and Higher Education Counsellor. His professional journey reflects a strong commitment to research excellence, environmental stewardship, and the development of future-ready engineers.

Citation Metrics (Google Scholar)

160

80

40

10

0

Citations
154

Documents
9

h-index
4

 

 

Citations                Documents

h-index



View Google Scholar Profile

 

Featured Publications

Eddy Chevallier | Engineering | Best Researcher Award

Published on by Academic Excellence

Dr. Eddy Chevallier | Engineering | Best Researcher Award

LAMIH – UPHF/CNRS 8201 | France

Dr. Eddy Chevallier is a distinguished researcher in Engineering Sciences, specializing in electromechanical systems that utilize static or dynamic electrical contact as a channel for information or power transmission. Currently serving as an Ingénieur de Recherche at the LAMIH Laboratory (UMR CNRS 8201, UPHF) in Famars, France, he focuses on understanding how surface topography influences multi-physical phenomena occurring at interfaces. His work spans electrical, thermal, and mechanical properties, integrating experimental measurement, numerical programming, and theoretical modeling to advance industrial applications that rely on surface-dependent interactions. His research aims to identify and quantify the relationships between topographic parameters and functional surface behavior, enabling the development of hybrid methodologies for optimizing surface designs based on precise performance requirements. Dr. Chevallier is qualified in the French national academic sections 28 (Physics of Materials), 60 (Mechanics), and 63 (Electrical Engineering), reflecting the interdisciplinary breadth of his expertise. He earned his Doctorate in 2014 from the Université de Picardie Jules Verne, where his thesis, supervised by Jérôme Fartin and co-advised by Robert Rouzereau and Valéry Bourny, focused on defining quality indices for metallic sliding contact using electrical signatures of surface condition. His doctoral work received the distinction of “Très Honorable.” He also holds a Master’s degree in physical characterization and modeling of complex materials from the same institution. Dr. Chevallier has contributed to leading scientific journals such as Tribology International, Journal of Tribology, Journal of Applied Physics, and has presented his work at numerous international and national conferences, reinforcing his role as a key contributor to tribology and electromechanical interface research.

Profile: Google Scholar

Featured Publications

Chevallier, E., Bourny, V., Bouzerar, R., Fortin, J., Durand-Drouhin, O., & others. (2014). Voltage noise across a metal/metal sliding contact as a probe of the surface state. Journal of Applied Physics, 115(15).

Chevallier, E. (2014). Définition d’indices de qualité du contact glissant métallique: Signatures électriques de l’état de surface (Doctoral dissertation, Université de Picardie Jules Verne). Université de Picardie Jules Verne.

Chevallier, E. (2020). Mechanical model of the electrical response from a ring–wire sliding contact. Tribology Transactions, 63(2), 215–221.

Jonckheere, B., Bouzerar, R., Bourny, V., Bausseron, T., Foy, N., & Chevallier, E. (2017). Assessment of the real contact area of a multi-contact interface from electrical measurements. In 23ème Congrès Français de Mécanique (CFM), France.

Guessasma, M., Bourny, V., Haddad, H., Machado, C., Chevallier, E., Tekaya, A., & others. (2018). Multi-scale and multi-physics modeling of the contact interface using DEM and coupled DEM-FEM approach. In Advances in Multi-Physics and Multi-Scale Couplings in Geo-Environmental Engineering.

Shagufta Riaz | Engineering | Women Researcher Award

Published on by Academic Excellence

Dr. Shagufta Riaz | Engineering | Women Researcher Award

Dr. Shagufta Riaz, National Textile University, Pakistan 

Dr. Shagufta Riaz is an Assistant Professor in the Department of Textile Engineering at National Textile University, Faisalabad, Pakistan. With a Ph.D. in Textile Engineering, she specializes in functional textiles, focusing on the use of nanomaterials for textile development. Dr. Riaz has authored several influential publications and has completed various high-impact research projects. She has worked as a researcher at the Wilson School of Textiles in the USA and is actively involved in advancing textile innovations. A member of prestigious international organizations like the Textile Institute and the Pakistan Engineering Council, Dr. Riaz is committed to sustainable textile solutions.

Professional Profile

Scopus

Google Scholar

Suitability of Dr. Shagufta Riaz for the Research for Women Researcher Award

Dr. Shagufta Riaz is a highly accomplished researcher in textile engineering, specializing in functional textiles and nanotechnology applications. Her extensive academic background, including a Ph.D. in Textile Engineering and international research experience at the Wilson School of Textiles, NCSU, USA, demonstrates her expertise in the field. She has significantly contributed to the advancement of sustainable textile innovations, textile finishing, and the development of nanomaterials for multifunctional textile applications. As an HEC Ph.D. Approved Supervisor and a Fellow of the Textile Institute, UK, she has played a crucial role in mentoring young researchers and advancing academic excellence in textile engineering.

Her research portfolio includes several high-impact projects funded at both national and international levels, focusing on crucial areas such as RF-shielding maternity garments, recycling of cellulosic waste for graphene quantum dots, and sustainable bio-processing in textile manufacturing. Additionally, her collaborations with industry highlight her ability to bridge the gap between academic research and practical industrial applications. Notable projects include the development of antibacterial medical gauze, pesticide-resistant clothing, and UV-shielding protective garments, which showcase her commitment to improving textile functionality for real-world challenges.

🎓 Education

Dr. Shagufta Riaz holds a Ph.D. in Textile Engineering from National Textile University, Faisalabad, Pakistan, where she also completed her M.Sc. in Textile Advanced Materials Engineering and B.Sc. in Textile Engineering with distinctions. She further honed her skills as a researcher at the Wilson School of Textiles, North Carolina State University, USA. This educational foundation, coupled with her hands-on research experience, forms the backbone of her expertise in nanotechnology, textile finishing, and sustainable textile innovations.

💼 Professional Experience

Dr. Shagufta Riaz is an Assistant Professor at National Textile University, Faisalabad. She has led and collaborated on multiple research projects, including those in partnership with international institutions and the textile industry. Her professional experience spans research in textile engineering, focusing on nanomaterials and sustainable solutions. Dr. Riaz has consulted on industry projects to optimize processes in textile production, such as designing protective garments and improving fabric properties. Her role as a Ph.D. supervisor and her recognition as a Fellow of the Textile Institute, UK, highlight her significant contribution to academia and industry.

🏅 Awards and Recognition

Dr. Shagufta Riaz’s academic excellence is evidenced by her recognition as a Fellow of the Textile Institute, UK, and a Lifetime Member of the Pakistan Engineering Council. She has received multiple accolades for her contributions to textile engineering, including a significant number of awards for her research in nanotechnology and textile innovations. Her work, recognized internationally, is reflected in numerous high-impact publications and the completion of major research and consultancy projects in collaboration with the textile industry.

🌍 Research Skills On Engineering

Dr. Riaz is an expert in nanotechnology applications in textile engineering, particularly for the development of multifunctional textiles. Her research focuses on the integration of nanomaterials to enhance textile properties such as antimicrobial, UV resistance, and electrical shielding. She has completed several research projects under government and industry funding, contributing valuable advancements in sustainable textiles, functional finishes, and eco-friendly processes. Dr. Riaz’s skills extend to guiding doctoral research and publishing in prestigious journals, marking her as a leading researcher in textile engineering.

📖 Publication Top Notes

  • Fabrication of robust multifaceted textiles by application of functionalized TiO₂ nanoparticles

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus
    • Citations: 95
    • Year: 2019

  • Functional finishing and coloration of textiles with nanomaterials

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Rehman, A. Javid, K. Iqbal, …
    • Citations: 77
    • Year: 2018

  • Modification of silica nanoparticles to develop highly durable superhydrophobic and antibacterial cotton fabrics

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain
    • Citations: 58
    • Year: 2019

  • Electrospun nanofiber-based viroblock/ZnO/PAN hybrid antiviral nanocomposite for personal protective applications

    • Authors: A. Salam, T. Hassan, T. Jabri, S. Riaz, A. Khan, K.M. Iqbal, S. Khan, M. Wasim, …
    • Citations: 41
    • Year: 2021

  • Cationization of TiO₂ nanoparticles to develop highly durable multifunctional cotton fabric

    • Authors: S. Riaz, M. Ashraf, H. Aziz, A. Younus, M. Umair, A. Salam, K. Iqbal, …
    • Citations: 31
    • Year: 2022

  • Layer by layer deposition of PEDOT, silver and copper to develop durable, flexible, and EMI shielding and antibacterial textiles

    • Authors: S. Riaz, S. Naz, A. Younus, A. Javid, S. Akram, A. Nosheen, M. Ashraf
    • Citations: 26
    • Year: 2022

  • Multifunctional formaldehyde-free finishing of cotton by using metal oxide nanoparticles and eco-friendly cross-linkers

    • Authors: N. Sarwar, M. Ashraf, M. Mohsin, A. Rehman, A. Younus, A. Javid, K. Iqbal, …
    • Citations: 24
    • Year: 2019

  • In situ development and application of natural coatings on non-absorbable sutures to reduce incision site infections

    • Authors: R. Masood, T. Hussain, M. Umar, Azeemullah, T. Areeb, S. Riaz
    • Citations: 21
    • Year: 2017

  • Selection and Optimization of Silane Coupling Agents to Develop Durable Functional Cotton Fabrics Using TiO₂ Nanoparticles

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus, M. Raza, A. Nosheen
    • Citations: 20
    • Year: 2021

  • Simultaneous fixation of wrinkle-free finish and reactive dye on cotton using response surface methodology

    • Authors: S. Abid, T. Hussain, A. Nazir, Z.A. Raza, A. Siddique, A. Azeem, S. Riaz
    • Citations: 16
    • Year: 2018