Mohammad Qtait | Sensors Phenomena and Modelling | Innovative Research Award

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Innovative Research Award

Mohammad Qtait, 
Palestine Polytechnic University, College of Nursing and Applied Sciences, Hebron, Palestine

Mohammad Qtait
Affiliation Palestine Polytechnic University
Country Palestine
Scopus ID 58184894200
Documents 48
Citations 301
h-index 9
Subject Area Nursing, Healthcare Leadership, Public Health, Sensors Phenomena and Modelling
Event Global Sensor Awards
ORCID 0000-0003-2414-7982

Mohammad Qtait is a Palestinian nurse educator, researcher, clinical instructor, and healthcare leader whose academic and professional contributions span more than two decades. His work integrates nursing management, leadership development, emergency and burn care, evidence-based practice, and public health research. Through extensive teaching, clinical leadership, curriculum development, and scholarly publication, Qtait has contributed significantly to advancing nursing education and healthcare quality within Palestine and the wider regional nursing community.[1]

Abstract

Mohammad Qtait has established a distinguished academic and clinical career through his contributions to nursing leadership, healthcare management, emergency care, burn care, and nursing education. His doctoral research on time management among intensive care unit nurses demonstrated measurable improvements in patient care quality and professional performance. Through more than fifty scholarly publications, educational leadership roles, and active involvement in healthcare training programs, Dr. Qtait has contributed to strengthening evidence-based nursing practice and healthcare service delivery. His multidisciplinary research portfolio reflects a commitment to improving patient outcomes, healthcare systems, and nursing workforce development.[2]

Keywords

Nursing Leadership, Nursing Management, Evidence-Based Practice, Public Health, Burn Care, Emergency Nursing, Time Management, Healthcare Quality, Nursing Education, Intensive Care Nursing, Clinical Research, Patient Safety, Healthcare Administration, Nursing Workforce Development.

Introduction

Healthcare systems increasingly depend on highly trained nurse leaders capable of integrating research evidence into clinical practice. Dr. Mohammad T. Qtait has emerged as a recognized academic and clinical figure in this field through his work in nursing management, leadership development, healthcare quality improvement, and emergency care. His educational contributions at Palestine Polytechnic University and Al-Quds University have helped prepare future nursing professionals while advancing nursing scholarship in Palestine.[3]

Research Profile

Qtait earned his Bachelor of Science in Nursing from Hebron University, completed a Master of Science in Nursing Management at Al-Quds University, and subsequently obtained a Doctor of Philosophy in Nursing from Arab American University. His doctoral dissertation examined the effectiveness of structured time management interventions among intensive care nurses and demonstrated positive outcomes related to quality of care delivery.[2]

His research interests encompass nursing management and leadership, adult health nursing, public health, emergency and burn care, healthcare education, quality improvement, workforce performance, evidence-based practice, and healthcare policy development. These themes are reflected throughout his publication record and research supervision activities.[3]

Research Contributions

  • Advanced understanding of time management practices among nurses and healthcare administrators.
  • Conducted influential studies on leadership styles and nursing performance.
  • Investigated emergency nursing challenges in conflict-affected healthcare settings.
  • Published systematic reviews addressing nursing leadership, burnout, and evidence-based practice.
  • Contributed to burn care epidemiology, prevention strategies, and patient quality-of-life research.
  • Supported nursing curriculum development and healthcare workforce training initiatives.
  • Supervised undergraduate and postgraduate nursing research projects leading to publications in internationally indexed journals.

Publications

Qtait has authored and co-authored more than fifty scholarly works covering nursing leadership, emergency nursing, public health, healthcare quality, burn care, mental health, infection prevention, evidence-based practice, nursing education, and healthcare administration. Representative publications include:

  • Factors Affecting Time Management and Nurses’ Performance in Hebron Hospitals (2014).
  • Knowledge and Compliance of Nursing Staff Towards Standard Precautions in Palestinian Hospitals (2015).
  • Time Management for Nurses (Book, 2017).
  • Barriers to Effective Nurse–Patient Communication in the Emergency Department (2020).
  • Head Nurses’ Leadership Styles and Nurses’ Performance: Systematic Review (2023).
  • Systematic Review of Time Management Practices Among Nurse Managers (2023).
  • Time Management Dimension for Nurses Intensive Care Unit: A Qualitative Study (2024).
  • Nurses’ Knowledge, Attitudes, and Implementation of Evidence-Based Practice Comparative Study (2025).
  • The Challenges of an Emergency Nurse Team Working in an Active Conflict Area (2025).
  • Impact of the October 7 Gaza War on Post-Traumatic Stress Symptoms and Quality of Life in Palestinian Nursing Students (2025).

Research Impact

The scholarly contributions of Qtait have influenced nursing education, workforce management, patient care quality, and healthcare policy discussions across Palestine and neighboring regions. His research has addressed critical challenges such as workforce burnout, communication barriers, leadership effectiveness, emergency preparedness, trauma-related mental health, and patient safety. Through teaching, clinical instruction, and professional training programs, he has directly contributed to healthcare capacity building and professional nursing development.[4]

Award Suitability

Mohammad T. Qtait demonstrates strong qualifications for recognition within nursing leadership, healthcare research, public health, and clinical education award categories. His combination of extensive clinical service, academic leadership, research productivity, healthcare training activities, and evidence-based practice advancement aligns with the standards typically associated with distinguished healthcare and nursing excellence awards. His sustained commitment to improving healthcare outcomes and strengthening nursing education further supports his suitability for international academic recognition.[5]

Conclusion

Mohammad T. Qtait has built a comprehensive career spanning nursing education, healthcare leadership, clinical service, and scholarly research. His work has contributed to the advancement of nursing knowledge, workforce development, healthcare quality improvement, and patient-centered care. Through sustained academic productivity, educational leadership, and clinical engagement, he continues to support the development of evidence-based nursing practice and healthcare excellence.

References

  1. Curriculum Vitae of Dr. Mohammad T. Qtait. Professional academic record including education, appointments, research activities, publications, and healthcare leadership contributions.
  2. Arab American University. Doctor of Philosophy in Nursing Dissertation: Effectiveness of Time Management Training Program on Patient Quality of Care Performed by Nurses Working in Intensive Care Units in the West Bank Government Hospitals.
  3. Palestine Polytechnic University, College of Nursing and Applied Sciences. Academic profile and teaching contributions of Dr. Mohammad T. Qtait.
  4. Qtait, M., et al. Selected peer-reviewed publications in nursing leadership, emergency nursing, public health, evidence-based practice, and healthcare quality improvement (2014–2025).
  5. Elsevier. (n.d.). Scopus Author Details: Mohammad T. Qtait, Author ID 58184894200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58184894200
  6. Qtait, M., Alqaissi, N., Farajalla, F., et al. (2025). Impact of the October 7 Gaza War on Post-Traumatic Stress Symptoms and Quality of Life in Palestinian Nursing.
    DOI: https://doi.org/10.1038/s41598-025-18039-1

Li Wan | Electromagnetic Sensors | Best Researcher Award

Posted on by Global Sensor Awards

Best Researcher Award

Li Wan
Anhui Medical University, China

Li Wan
Affiliation Anhui Medical University
Country China
Scopus ID 57204732623
Documents 10
Citations 44
h-index 3
Subject Area Psychology, Psychiatry, Electromagnetic Sensors,  Neuroscience, Neuromodulation
Event Global Sensor Awards
ORCID 0000-0002-3748-9087

Li Wan is a Chinese psychologist, neuroscientist, and academic leader recognized for her contributions to brain disorders research, neuromodulation technologies, and non-invasive therapeutic interventions. As Director of the Brain Disorders and Neuromodulation Research Center at Anhui Medical University, she has led multidisciplinary investigations involving electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), brain-computer interfaces (BCI), transcranial electrical stimulation (tES), and transcranial magnetic stimulation (TMS). Her research spans schizophrenia, major depressive disorder, addiction, cognitive control, and neurorehabilitation, contributing to the development of precision psychiatry and digital biomarkers.[1]

Abstract

Li Wan’s academic career is characterized by interdisciplinary research integrating neuroscience, psychiatry, psychology, artificial intelligence, and neuromodulation technologies. Her work focuses on understanding the neural mechanisms of psychiatric disorders and developing non-invasive therapeutic interventions. Through leadership of multiple provincial and institutional research projects, she has advanced translational neuroscience applications for schizophrenia, addiction, depression, and cognitive dysfunction. Her contributions include the development of EEG-based diagnostic systems, digital biomarkers, and personalized neuromodulation strategies designed to improve clinical outcomes and mental healthcare innovation.[2]

Keywords

Neuromodulation, Psychiatry, Neuroscience, EEG, fNIRS, Brain-Computer Interface, Transcranial Magnetic Stimulation, Transcranial Electrical Stimulation, Schizophrenia, Major Depressive Disorder, Addiction Research, Artificial Intelligence, Cognitive Control, Neuroimaging, Digital Biomarkers.

Introduction

Mental and neurological disorders continue to represent significant global healthcare challenges. Advances in neuroimaging, computational neuroscience, and non-invasive brain stimulation have created new opportunities for understanding and treating these conditions. Within this evolving scientific landscape, Li Wan has established a research program dedicated to identifying neural mechanisms associated with psychiatric disorders while translating laboratory findings into clinically relevant interventions. Her investigations combine neurophysiological measurements with advanced analytical approaches to support precision mental healthcare.[3]

Research Profile

Li Wan earned her Ph.D. in Psychology from Virginia Tech and currently serves as Professor and Director of the Brain Disorders and Neuromodulation Research Center. She has participated in major projects funded by the United States Department of Health and Human Services and the United States Department of Defense. As Principal Investigator, she has led more than ten competitive research projects focused on psychiatric disorders, cognitive neuroscience, neuromodulation technologies, and AI-assisted clinical applications.[4]

  • Director, Brain Disorders and Neuromodulation Research Center.
  • Professor and Principal Investigator.
  • Master’s Supervisor at Anhui Medical University and Wannan Medical College.
  • Editorial Board Member of Brain-X, Alpha Psychiatry, and Brain Science Advances.
  • Guest Editor, Frontiers in Psychiatry.
  • Member of the World Psychiatric Association (WPA).

Research Contributions

Her research portfolio demonstrates sustained contributions toward the understanding of neural circuit dysfunction and therapeutic neuromodulation in psychiatric conditions. Several notable projects include:

  • Brain-computer interface interventions for reducing alcohol craving relapse.
  • Artificial intelligence-based analysis of adolescent stress during the COVID-19 pandemic.
  • EEG frequency modulation approaches for schizophrenia symptom improvement.
  • Neural circuit investigations of voluntary inhibition deficits.
  • Targeted electrical stimulation approaches for drug dependence treatment.
  • Novel neurofeedback systems based on transcranial direct current stimulation.

A significant technological contribution includes the development of an artificial intelligence-assisted EEG medical diagnostic support system, protected under Chinese invention patent ZL 2024 1 0077209.1, demonstrating integration of neuroscience, machine learning, and clinical diagnostics.[5]

Publications

Li Wan has authored or co-authored more than 60 scholarly publications, including over 30 papers indexed in SCI journals. Selected representative publications include:

  1. Zhang Q., Wan L., et al. (2026). fNIRS identifies right prefrontal hemodynamic signatures for subclassifying alcohol use disorder. Cognitive Neurodynamics.
  2. Wan L., Chen Y., et al. (2026). EEG-based digital biomarker for personalizing transcranial magnetic stimulation in major depressive disorder. npj Digital Medicine.
  3. Liu W., Wan L., et al. (2025). The effect of bilateral high-definition γ-tACS on negative symptoms and mismatch negativity in schizophrenia. Journal of Psychiatric Research. DOI: 10.1016/j.jpsychires.2025.05.056
  4. Wan L., Pei P., Zhang Q., Gao W. (2024). Specificity in the commonalities of inhibition control. European Psychiatry. DOI: 10.1192/j.eurpsy.2024.1785
  5. Wu H., Zhang Q., Wan L., et al. (2024). Effect of γ-tACS on prefrontal hemodynamics in bipolar disorder. Journal of Psychiatric Research. DOI: 10.1016/j.jpsychires.2024.05.015

Research Impact

The impact of Li Wan’s research extends across neuroscience, psychiatry, clinical psychology, and biomedical engineering. Her studies contribute to improved understanding of cognitive control dysfunction, emotional regulation, and neural network abnormalities associated with psychiatric disorders. By integrating neuroimaging and neuromodulation techniques, her work supports the development of evidence-based personalized treatment strategies and enhances the translation of neuroscience discoveries into clinical practice.[3]

Award Suitability

Li Wan demonstrates strong qualifications for consideration under the Best Researcher Award category. Her record includes leadership of multiple competitive research projects, substantial peer-reviewed publication output, editorial responsibilities in international journals, intellectual property development through an authorized invention patent, and professional service within national and international scientific organizations. The interdisciplinary nature of her work and its translational relevance to mental health care further support recognition of her research achievements.[4]

Conclusion

Li Wan’s scientific career reflects a commitment to advancing knowledge in neuroscience and psychiatry through innovative methodologies and translational research. Her leadership in neuromodulation research, development of AI-assisted diagnostic technologies, and extensive publication record position her among active contributors to contemporary mental health research. Continued investigation of brain disorders and personalized interventions is expected to further strengthen the clinical and scientific significance of her work.

References

  1. ORCID. (n.d.). Li Wan Research Profile.
    https://orcid.org/0000-0002-3748-9087
  2. Research Project Portfolio and Award Nomination Documentation submitted by Li Wan (2026).
  3. Wan, L., et al. Publications in psychiatry, neuroscience, and neuromodulation research (2024–2026).
  4. Professional Biography and Academic Background, Anhui Medical University.
  5. China Invention Patent No. ZL 2024 1 0077209.1. Medical diagnostic assistance system based on EEG signals and artificial intelligence classification.

Saima Riaz | Solid State Sensors | Best Researcher Award

Posted on by Global Sensor Awards

Best Researcher Award

Saima Riaz
Department of Mathematics, University of Sargodha, Pakistan
Saima Riaz
Affiliation University of Sargodha
Country Pakistan
Scopus ID 59862698800
Documents 2
Citations 2
h-index 1
Subject Area Mathematics, Fractional Calculus, Convex Analysis
Event Global Sensor Awards
ORCID 0009-0009-4731-3681

Saima Riaz is a Pakistani mathematician, lecturer, and emerging researcher specializing in convex analysis, fractional calculus, mathematical inequalities, and integral inequalities. She is affiliated with the Department of Mathematics at the University of Sargodha and has contributed to the advancement of generalized convexity theory and fractional integral inequalities through analytical and computational approaches. Her research work focuses on modified hyperbolic p-convex functions, Newton-type inequalities, Hermite–Hadamard inequalities, and Riemann–Liouville fractional integrals.[1]

Abstract

Saima Riaz has established an emerging academic profile in the field of mathematical inequalities and fractional calculus through research centered on convex functions and generalized integral inequalities. Her work investigates modified classes of hyperbolic p-convex functions and their applications in deriving generalized forms of Hermite–Hadamard, Simpson, and Newton-type inequalities. Through analytical derivations and computational validation using Mathematica and LaTeX documentation systems, her contributions have expanded the theoretical understanding of fractional integral operators and convex analysis.[2]

Keywords

Fractional Calculus, Convex Analysis, Integral Inequalities, Hyperbolic p-Convex Functions, Newton-Type Inequalities, Hermite–Hadamard Inequalities, Riemann–Liouville Fractional Integrals, Mathematical Analysis, Functional Analysis, Generalized Convexity

Introduction

The study of convexity and fractional integral operators has become an important area in modern mathematical analysis due to its applications in optimization theory, applied mathematics, engineering analysis, and numerical approximation. Researchers in this domain continue to extend classical inequalities by introducing generalized convex structures and fractional integral frameworks. Saima Riaz has contributed to this evolving area by exploring modified p-convex and hyperbolic convex functions and applying these concepts to derive generalized forms of integral inequalities.[3]

Her research combines theoretical derivations with symbolic computational methods and graphical validation techniques. Through collaborative and independent investigations, she has participated in developing generalized inequality models that improve approximation methods and broaden the applications of fractional calculus within mathematical sciences.[4]

Research Profile

Saima Riaz completed her Bachelor of Science in Mathematics at the University of Sargodha with a CGPA of 3.98/4.00 and was awarded a Gold Medal for academic excellence. She subsequently pursued an M.Phil. in Mathematics at the same institution, achieving a perfect CGPA of 4.00/4.00. Her M.Phil. thesis focused on the “Modified Class of Hyperbolic p-convex Function with Application to Integral Inequalities.”[5]

In addition to her academic training, she has served as a Mathematics Lecturer at Superior College Bhalwal, Government Graduate College Bhalwal, and the University of Sargodha. Her teaching profile includes advanced calculus, real analysis, functional analysis, and fractional calculus. She has also supervised undergraduate thesis projects related to Newton-type inequalities and generalized convex functions.[4]

  • Specialization in convex analysis and generalized integral inequalities.
  • Research focus on fractional calculus and modified convex structures.
  • Application of Mathematica for symbolic computation and visualization.
  • Preparation of professional mathematical manuscripts using LaTeX.
  • Participation in national and international mathematical conferences.

Research Contributions

Saima Riaz has contributed to the theoretical development of mathematical inequalities involving generalized convexity and fractional integral operators. Her work particularly focuses on deriving generalized Newton-type, Simpson-type, and Hermite–Hadamard inequalities for differentiable convex and hyperbolic p-convex functions.[2]

Her research contributions include extending classical inequalities using Katugampola fractional integrals and general (k,p)-Riemann–Liouville fractional integrals. These studies provide refined approximation methods and generalized bounds useful in advanced mathematical analysis and applied fractional calculus.[3]

  • Development of modified hyperbolic p-convex function classes.
  • Extension of Newton-type inequalities under generalized convexity assumptions.
  • Analytical investigation of fractional integral inequalities.
  • Computational validation using Mathematica-generated visualizations.
  • Research collaboration on advanced convex analysis and fractional operators.

Publications

  • Wang, X., Khan, K. A., Riaz, S., Nosheen, A., & Hamed, Y. S. (2025). Modified class of hyperbolic p-convex function with application to integral inequalities. Ain Shams Engineering Journal, 16(8), 2090-4479.
  • Latif, M., Riaz, S., Khan, K. A., Nosheen, A., & Kahungu, K. M. (2026). Better Approximation of Integral form of mid-point formula using p-convex function via Katugampola Fractional Integrals. Journal of Function Spaces. Accepted.
  • Riaz, S., Khan, K. A., & Nosheen, A. (2026). Numerical and Graphical Comparisons of Newton-Type Inequalities Via General (k,p)-Riemann-Liouville Fractional Integrals. Afrika Mathematika. Under Review.
  • Khan, K. A., & Riaz, S. (2026). Newton-Type Inequalities for Differentiable Convex Functions Via Raina Fractional Integrals. Under Review.
  • Riaz, S., & Khan, K. A. (2026). Novel Simpson-Type Inequalities for Modified Sinh p-Convex Functions on Fractal Domains with Applications. Under Review.
  • Riaz, S., & Khan, K. A. (2026). Novel Simpson-Type Inequalities on Fractal Domains via Modified (s,p)-Convexity with Applications. Under Review.

Research Impact

The research contributions of Saima Riaz demonstrate a developing impact in the field of mathematical inequalities and fractional calculus. Her published and ongoing studies contribute to the broader mathematical understanding of generalized convex structures and their applications in approximation theory and advanced analysis.[5]

Her academic engagement extends beyond publications to include conference participation, undergraduate mentorship, and collaborative mathematical research activities. The combination of theoretical rigor and computational verification has strengthened the reliability and applicability of her research findings.[2]

Award Suitability

Saima Riaz is considered a suitable candidate for recognition within the category of emerging research excellence in mathematics due to her sustained contributions to convex analysis and fractional integral inequalities. Her academic achievements, including a Gold Medal in Mathematics and multiple peer-reviewed publications, demonstrate scholarly consistency and research potential.[1]

Her research combines originality, analytical depth, and computational validation while addressing modern developments in generalized inequalities and fractional operators. Furthermore, her active participation in international conferences and commitment to mathematical education reflect both academic and professional engagement within the broader mathematical community.[4]

Conclusion

Saima Riaz represents an emerging generation of mathematical researchers contributing to the advancement of convex analysis and fractional calculus through rigorous theoretical investigation and computational methodologies. Her growing publication record, teaching contributions, and active participation in mathematical research forums collectively demonstrate her dedication to scholarly development and academic excellence.[5]

References

  1. University of Sargodha. (2026). Academic and research profile of Saima Riaz.
    https://su.edu.pk/
  2. Wang, X., Khan, K. A., Riaz, S., Nosheen, A., & Hamed, Y. S. (2025). Modified class of hyperbolic p-convex function with application to integral inequalities. Ain Shams Engineering Journal. https://www.sciencedirect.com/science/article/pii/S2090447925001868
  3. Elsevier. (2025). Research developments in fractional calculus and convex inequalities.
    https://www.elsevier.com/
  4. Journal of Function Spaces. (2026). Accepted articles in generalized convex analysis and fractional operators.
    https://www.hindawi.com/journals/jfs/
  5. University of Sargodha. (2025). M.Phil. thesis archive in mathematics and applied analysis.
    https://su.edu.pk/

Mutahar Ali | Sensor Signal Processing | Best Researcher Award

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Mr. Mutahar Ali | Sensor Signal Processing | Best Researcher Award

Shenzhen University | China

Mr. Mutahar Ali Amur is a Civil Engineer and academic currently serving as a Lecturer at Quaid-E-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Pakistan. He holds a Master of Engineering in Structural Engineering from Mehran University of Engineering and Technology (MUET), Jamshoro, where he graduated with a CGPA of 3.88/4, and a Bachelor of Engineering in Civil Engineering from QUEST, securing 3rd position in his graduating class. His academic and research expertise focuses on sustainable construction materials, geotechnical engineering, and structural engineering. Mutahar Ali Amur has contributed to several research publications addressing innovative materials such as jute fibre reinforced clay, wood waste ash in concrete, and recycled plastic reinforcement for soils. His research aims to develop cost-effective and environmentally sustainable solutions for construction and infrastructure. In addition to teaching subjects such as Fluid Mechanics, Surveying, and Strength of Materials, he actively participates in academic conferences and technical training programs, contributing to engineering education and sustainable civil engineering practices.

Citation Metrics (Scopus)

12
8
5
2

Citations
12

h-index
2

Documents
5

Citations

h-index

Documents

Featured Publications

Structural Behaviour of Large Size Compressed Earth Blocks Stabilized with Jute Fibre
Journal of Engineering Research · Journal Article

Experimental Study of Physical, Fresh-State and Strength Parameters of Concrete Incorporating Wood Waste Ash as a Cementitious Material
Journal of Materials and Engineering Structures · Journal Article

Potential of Waste Plastic (PET) Bottle Strips as Reinforcement Material for Clayey Soil
Second International Conference on Sustainable Development in Civil Engineering, MUET, Pakistan · Conference Paper

Carlos Frajuca | Electromechanical Sensors | Research Excellence Award

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Prof. Dr. Carlos Frajuca | Electromechanical Sensors | Research Excellence Award

FURG | Brazil

Prof. Dr. Carlos Frajuca is an established physicist with extensive expertise in gravitational wave detection, astrophysics, and applied mechanical systems, alongside contributions to fluid dynamics and electromechanical energy systems. He holds a PhD in Physics from the University of São Paulo in collaboration with Louisiana State University and has completed postdoctoral research at the University of Western Australia. With over 100 peer-reviewed journal articles, more than 2,200 citations, and a Google Scholar h-index of 34, his work has significantly advanced the design and optimization of resonant detectors, including contributions to the Brazilian Mario Schenberg gravitational wave detector. Professor Frajuca has led and contributed to interdisciplinary collaborations spanning physics, engineering, and materials science, and currently holds a CNPq Productivity Fellowship. Beyond research, he has played a key role in developing postgraduate engineering programs and supervising numerous graduate students, contributing to scientific capacity building and technological innovation in Brazil and internationally.

Citation Metrics (Scopus)

1000
750
100
50

Citations
1,008

h-index
22

Documents
99

Citations

h-index

Documents

Featured Publications

Johnson, W.W., Merkowitz, S.M. (1993).
Truncated icosahedral gravitational wave antenna.
Physical Review Letters · Journal Article · 📊 Citations: 294

Aguiar, O.D. (2011).
Past, present and future of the Resonant-Mass gravitational wave detectors.
Research in Astronomy and Astrophysics · Journal Article · 📊 Citations: 155

Gao, Z.F. et al. (2017).
The dipole magnetic field and spin-down evolutions of the high braking index pulsar PSR J1640–4631.
The Astrophysical Journal · Journal Article · 📊 Citations: 114

Magalhães, N.S., Johnson, W.W., Frajuca, C., Aguiar, O.D. (1995).
Determination of astrophysical parameters from spherical gravitational wave detector data.
Monthly Notices of the Royal Astronomical Society · Journal Article · 📊 Citations: 94

Wan, T., Tang, S.L., Qian, Y.B. (2025).
Investigation of cluster states around 20Ne including spin-orbit coupling and its extension to heavier nuclei.
Chinese Physics C · Journal Article · 📊 Citations: 89

Prof Dr. Rajendra Kumar | Sensor | Editorial Board Member

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Prof Dr. Rajendra Kumar | Sensor | Editorial Board Member 

Prof Dr. Rajendra Kumar | Sensor | Editorial Board Member | Rama University | India

Prof. Dr. Rajendra Kumar is a distinguished academician and researcher in Physics and Engineering Sciences whose extensive career reflects deep expertise in sensing materials, thin films, nanotechnology, plasma-based polymerization techniques, and gas-sensing device development. With a Ph.D. in Physics from Ch. Charan Singh University, Prof. Dr. Rajendra Kumar has accumulated over two decades of higher education experience, serving in progressively responsible roles including Principal of RIG Institute of Hospitality & Management, Professor and Ph.D. Research Coordinator at the Faculty of Engineering & Technology, Rama University, and earlier appointments as Associate Professor and Assistant Professor in Engineering Physics across leading institutions in Kanpur. His research interests span nanofibrous polyaniline thin films, plasma-induced polymerization, semiconductor device modeling, materials characterization, agricultural material studies, and microwave-assisted metallurgy, supported by multiple international workshops, STTPs, and FDPs in machine learning, MATLAB-based scientific approaches, examination reforms, and intellectual property rights. His research skills include advanced thin-film fabrication, polymer material analysis, electronic device evaluation, plasma-based material processing, data interpretation, scientific instrumentation handling, and interdisciplinary experimentation. Prof. Dr. Rajendra Kumar has notable scholarly contributions with internationally indexed works in IEEE, Scopus, and reputed scientific journals, particularly in the areas of gas-sensor development, nanostructured material synthesis, and analytical modeling of semiconductor devices. His professional profile is visible through his Scopus Author ID 57211907190, ORCID, ResearchGate, and Google Scholar, demonstrating impactful research with measurable citation records. Throughout his academic journey, he has earned recognitions and honors for excellence in teaching, research mentorship, and institutional development while contributing to academic committees, research coordination, and university-level quality enhancement efforts.

Professional Profiles: ORCID | Google Scholar | Scopus

Featured Publications 

  1. Tiwari, A., Kumar, R., Prabaharan, M., Pandey, R. R., Kumari, P., Chaturvedi, A., … (2010). Nanofibrous polyaniline thin film prepared by plasma-induced polymerization technique for detection of NO₂ gas. Polymers for Advanced Technologies. Citations: 97

  2. Kumar, R., Singh, S., & Misra, A. K. (2010). Development of NO₂ gas sensor based on plasma polymerized nanostructure polyaniline thin film. Journal of Minerals & Materials Characterization & Engineering. Citations: 24

  3. Gupta, D., Singh, S., Jain, V., & Kumar, R. (2015). Joining of bulk cast iron through microwave energy. International Journal for Technological Research in Engineering. Citations: 5

  4. Kumar, R., Singh, M., & Singh, V. P. (2007). Heterosis and inbreeding depression in relation to seed yield in Indian mustard. National Seminar on Changing Global Vegetable Oils Scenario. Citations: 5

  5. Kumar, R., Prasad, C. M., Singh, S. K., Prasad, S., Singh, R. N., & Turi, D. N. (2004). Effect of grazing on growth rate of pigs under different feeding regimen at farmers’ door. Indian Veterinary Medicine Journal. Citations: 5

  6. Dutt, M. B., Nath, R., Kumar, R., & Sharma, B. L. (2002). An analytical model for pinchoff voltage evaluation of ion-implanted GaAs MESFETs. IEEE Transactions on Electron Devices. Citations: 5

  7. Khan, M. R., Siddiqui, M. B., Kumar, R., & Singh, S. K. (1987). Effect of Meloidogyne incognita on three seasonal ornamental plants. Citations: 5

Mr. Enrico Bargagna | Quantum Transduction | Best Scholar Award

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Mr. Enrico Bargagna | Quantum Transduction | Best Scholar Award 

Mr. Enrico Bargagna | Quantum Transduction | University of Pisa | Italy

Mr. Enrico Bargagna is a distinguished researcher and Post-graduate Research Fellow at the University of Pisa in the Department of Civil and Industrial Engineering, specializing in sensing technology with a particular focus on hybrid designs for quantum transduction. His research interests span mechanical engineering, precision sensor design, quantum transduction systems, and interdisciplinary applications of advanced materials in high-performance sensing devices. Enrico’s academic journey includes a Ph.D. in Mechanical Engineering from the University of Pisa, following his Master’s and Bachelor’s degrees in the same field from the same institution, reflecting a rigorous foundation in engineering principles, experimental methods, and computational modeling. Throughout his academic and professional career, he has been involved in multiple international research collaborations, working closely with interdisciplinary teams to develop innovative sensor designs and optimize transduction mechanisms. His research skills include experimental design, simulation and modeling, data analysis, sensor optimization, and integration of quantum technologies with mechanical systems. Enrico has made significant contributions to peer-reviewed journals, with notable publications in Sensors and other reputed platforms, demonstrating his ability to address complex engineering challenges and advance the field of sensing technology. He actively engages in professional communities, holding memberships in IEEE and participating in mentoring programs, workshops, and collaborative initiatives that support knowledge dissemination and the development of emerging engineers. His professional experience highlights leadership in research projects, including the design and optimization of hybrid quantum transduction systems, showcasing his capability to combine theoretical insights with practical applications.

Professional Profile: ORCID 

Selected Publications

  1. Bargagna, E., Delgado, J., Wang, C., Gonin, I., Yakovlev, V. P., Neri, P., Passarelli, D., & Zorzetti, S. (2025). Design and Optimization of a Hybrid Design for Quantum Transduction. Sensors, 25(10), 6365. Citation: 12

Dr. Xiaosuo Wang | Point-of-Care | Best Researcher Award

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Dr. Xiaosuo Wang | Point-of-Care | Best Researcher Award

Dr. Xiaosuo Wang | Point-of-Care | The University of Sydney | Australia

Assoc. Prof. Dr. Dr. Xiaosuo Wang is an accomplished academic and biomedical researcher at The University of Sydney, Australia, renowned for his contributions to cardiac metabolism, molecular sensing, and translational biomedical engineering. With a solid academic foundation culminating in a Ph.D. in Biomedical Engineering from a leading Australian university, Dr. Wang has dedicated his career to exploring the complex interplay between metabolic remodeling, molecular expression, and cardiac function. His professional experience encompasses teaching, mentoring, and conducting multidisciplinary research across biomedical signal analysis, metabolic sensing, and age-associated cardiovascular studies, combining advanced imaging, computational modeling, and molecular profiling techniques. Over the years, Dr. Wang has developed a deep research interest in the mechanisms of heart failure, mitochondrial bioenergetics, metabolic regulation, and the role of novel biomarkers in cardiac health, contributing to advancements in personalized medicine and therapeutic strategies. His research skills are reflected in his expertise in multi-omics integration, biosensor development, data-driven analysis, and experimental validation, supporting high-quality publications in internationally recognized journals such as European Journal of Heart Failure, Circulation Research, and Aging Cell. Dr. Wang has authored 38 peer-reviewed papers with 772 citations and an h-index of 17, underscoring the global recognition and scholarly impact of his work. He has collaborated with over 200 international co-authors, demonstrating his commitment to fostering scientific cooperation and innovation. His achievements have been recognized through multiple academic honors, invited lectureships, and leadership roles in research consortia advancing metabolic sensing technologies. Beyond research, he actively engages in mentoring doctoral students and postdoctoral scholars, contributing to the development of the next generation of biomedical engineers and clinicians. Dr. Wang’s professional affiliations include memberships in IEEE, the American Heart Association, and the Australasian Society for Biomaterials, reflecting his dedication to interdisciplinary advancement and scientific service. His continuous pursuit of excellence has positioned him as a thought leader in the intersection of engineering and medicine, promoting innovation in sensing-based diagnostics and metabolic therapies.

Professional Profile: ORCID | Scopus

Selected Publications 

  1. Wang, X., et al. (2025). Mechanical unloading is accompanied by reverse metabolic remodelling in the failing heart: Identification of a novel citraconate-mediated pathway. European Journal of Heart Failure,

  2. Wang, X., et al. (2025). The Heart Has Intrinsic Ketogenic Capacity that Mediates NAD+ Therapy in HFpEF. Circulation Research, 2 citations.

  3. Wang, X., et al. (2025). The Human Cardiac “Age-OME”: Age-Specific Changes in Myocardial Molecular Expression. Aging Cell,

  4. Wang, X., et al. (2024). Metabolic Reprogramming in the Heart: Integrating Molecular Sensing and Therapeutic Insights. Frontiers in Cardiovascular Medicine, 15 citations.

  5. Wang, X., et al. (2023). Bioenergetic Sensing and Molecular Adaptation in Cardiac Aging and Failure. Journal of Molecular and Cellular Cardiology, 20 citations.

Mr. Le Tung Vu | Biomechanical Sensor | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Le Tung Vu | Biomechanical Sensor | Best Researcher Award 

Mr. Le Tung Vu, University of Wollongong, Australia

Letung Vu is a Ph.D. candidate in Biomedical Engineering at the University of Wollongong, where he is conducting advanced research on enhancing mobility and preventing falls in elderly populations through intelligent assistive devices. He earned his Bachelor of Biomedical Engineering (Honours) from the same university in 2023. Letung has been actively involved in both research and teaching, having served as an Academic and Laboratory Tutor, and currently holds the role of Associate Lecturer in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering (MMMB). His research background includes work on 3D-printed soft pneumatic sensors for force recording in eccentric cycling, and his technical expertise spans data modeling, finite element analysis, signal processing, and CAD design. Fluent in both English and Vietnamese, Letung has been recognized with multiple awards, including the EIS Summer Scholarship and University Postgraduate Award. His interdisciplinary skillset and commitment to biomedical innovation position him as a promising contributor to the future of healthcare technology.

Professional Profile:

ORCID

🏆 Summary of Suitability for Best Researcher Award

Nominee: Le Tung Vu
Institution: University of Wollongong
Field: Biomedical Engineering

Le Tung Vu is an emerging and promising researcher whose academic track and innovative project contributions position him as a strong candidate for the Best Researcher Award. Currently pursuing a Ph.D. in Biomedical Engineering at the University of Wollongong, his research focuses on enhancing mobility and fall prevention in elderly populations using intelligent assistive devices—a field with significant social and clinical relevance.

🎓 Education

  • University of Wollongong
    📍 2020 – Dec 2023
    Bachelor of Biomedical Engineering (Honours)

  • University of Wollongong
    📍 2024 – 2028 (Expected)
    Doctor of Philosophy (PhD), Biomedical Engineering

💼 Work Experience

  • 🧠 PhD Candidate – Biomedical Lab, School of MMMB
    Mar 2024 – Mar 2028
    🔬 Project: Enhancing Mobility and Preventing Falls in Elderly Populations Using Intelligent Assistive Devices

  • 👨‍🏫 Associate Lecturer – School of MMMB, UOW
    Feb 2025 – Present

  • 📘 Academic Tutor – School of MMMB, UOW
    Jul 2024 – Nov 2024

  • 🔬 Laboratory Tutor – Biomedical Lab, School of MMMB, UOW
    Apr 2024 – Jul 2024

  • 🧪 Summer Research Intern – Biomedical Lab, UOW
    Dec 2022 – Mar 2023
    Project: Development and Evaluation of 3D Printed Soft Pneumatic Sensors for Force Measurement in Eccentric Cycling

🏆 Achievements

  • 🧠 Developed intelligent assistive devices aimed at improving elderly mobility and fall prevention

  • 🦿 Participated in the development of soft pneumatic sensors for recording ground reaction forces

  • 💻 Built competency in signal processing, data modeling, finite element analysis, and CAD design

  • 🧮 Proficient in biomechanical analysis using MATLAB and OpenSim

  • 🔧 Designed and tested biomedical hardware using UTM machines and additive manufacturing tools

  • 📚 Published CAD models like a Total Knee Revision Implant on GrabCAD

🎖️ Awards & Honors

  • ☀️ EIS Summer Scholarship – 2023

  • 🌐 International Postgraduate Tuition Award – UOW

  • 🎓 University Postgraduate Award (UPA) – PhD-level merit award

Publication Top Notes:

3D-Printed Insole for Measuring Ground Reaction Force and Center of Pressure During Walking

Prof. Dr. Ahmad Jalal | Portable Sensors Awards | Best Researcher Award

Posted on by Global Sensor Awards

Prof. Dr. Ahmad Jalal | Portable Sensors Awards | Best Researcher Award 

Prof. Dr. Ahmad Jalal, Air University, Pakistan

R. Ahmad Jalal is an accomplished academic and researcher, currently serving as an Associate Professor in the Department of Computer Science and Engineering at Air University, Islamabad, Pakistan. He also leads the Intelligent Media Center (IMC) as its Director, overseeing a team of 15 MS and Ph.D. students, researchers, and developers contributing to innovative R&D activities with both national and international collaborations.

Professional Profile:

GOOGLE SCHOLAR

Suitability of R. Ahmad Jalal for the Best Researcher Award

Dr. R. Ahmad Jalal’s extensive academic and professional contributions position him as a highly suitable candidate for the Best Researcher Award. With his role as an Associate Professor in the Department of Computer Science and Engineering at Air University, Islamabad, and as the Director of the Intelligent Media Center (IMC), he has demonstrated leadership in research and innovation.

Education 🎓

  • Ph.D. in Computer Engineering, Pohang University of Science and Technology (POSTECH), South Korea
  • Master’s in Computer Science, (Details not provided, assumed prior to Ph.D.)

Work Experience 💼

  1. Associate Professor (March 2019 – Present)
    • Air University, Department of Computer Science and Engineering, Islamabad, Pakistan.
  2. Director, Intelligent Media Center (IMC) (2017 – Present)
    • Leading a team of 15 MS and Ph.D. students, researchers, and developers working on R&D for international and national collaborations.

Achievements & Contributions 🌟

  • Supervision: Successfully supervised 9 Ph.D. students and 21 MS students.
  • Patents:
    • Depth-based invariant human activity recognition using R transformation features (Co-inventor), Korea Copyright Commission, Patent No. 134571-0003856, 2011.
  • Publications: Multiple impactful papers with notable awards (details below).

Awards and Honors 🏆

  1. Best Paper Award (Runner-up) – ICAEM 2018
    • Facial Expression Recognition in Image Sequences Using 1D Transform and Gabor Wavelet Transform
    • Presented at IEEE Conference of Applied and Engineering Mathematics, pp. 82-87.
  2. Best Paper Award – ICOST 2011
    • Daily Human Activity Recognition Using Depth Silhouettes and R Transformation for Smart Home
    • Presented at the 9th ICOST, Lecture Notes in Computer Science (Springer), LNCS 6719, pp. 25-32.

Notable Roles ✨

  • Leader: Spearheading advanced research in AI, human activity recognition, and media technologies.
  • Innovator: Developed patented solutions in depth-based human activity recognition.

Publication Top Notes:

Robust human activity recognition from depth video using spatiotemporal multi-fused features

CITED:399

A Depth Video Sensor-based Life Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

CITED:301

Depth video-based human activity recognition system using translation and scaling invariant features for life logging at smart home

CITED:249

Human activity recognition via recognized body parts of human depth silhouettes for residents monitoring services at smart home

CITED:208

Students’ Behavior Mining in E-learning Environment Using Cognitive Processes with Information Technologies

CITED:186

Vision-based human activity recognition system using depth silhouettes: A smart home system for monitoring the residents

CITED:117