Hamza Abubakar | Body Area Network | Innovative Research Award

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Innovative Research Award

HAMZA ABUBAKAR, PhD
Department of Mathematics, Isa Kaita College of Education, Dutsin-Ma, Nigeria

HAMZA ABUBAKAR
Affiliation Isa Kaita College of Education
Country Nigeria
Scopus ID 57217009001
Documents 30
Citations 350
h-index 9
Subject Area Applied Mathematics, Financial Mathematics, Neural Networks, Body Area Network
Event Global Sensor Awards
ORCID
0000-0002-9451-0401

Hamza Abubakar is a Nigerian applied mathematician and academic researcher specializing in financial mathematics, optimization algorithms, neural networks, and statistical modelling. He has contributed extensively to interdisciplinary mathematical research through scholarly publications, conference presentations, academic leadership, and funded research initiatives. His work integrates advanced computational techniques with applied statistical frameworks for solving practical problems in finance, engineering, healthcare analytics, and artificial intelligence.[1]

Abstract

This academic article presents the scholarly profile and research achievements of Hamza Abubakar, an applied mathematician with expertise in financial mathematics, neural networks, optimization algorithms, and statistical modelling. Over a professional academic career spanning more than fifteen years, he has contributed to higher education, interdisciplinary research, curriculum development, and mathematical applications in finance and artificial intelligence. His publications and conference presentations demonstrate sustained contributions to optimization theory, stochastic modelling, and machine learning-based analytical systems. His work has received visibility through peer-reviewed international journals and collaborative research activities across Nigeria and Malaysia.[2]

Keywords

Applied Mathematics; Financial Mathematics; Neural Networks; Optimization Algorithms; Statistical Modelling; Machine Learning; Risk Assessment; Weibull Distribution; Hopfield Neural Networks; Artificial Intelligence; Computational Mathematics; Mathematical Modelling.

Introduction

Applied mathematics continues to play an essential role in solving real-world scientific and financial challenges through computational modelling and algorithmic optimization. Researchers working at the intersection of mathematics, artificial intelligence, and financial analytics contribute significantly to modern predictive systems and decision-making frameworks. Hamza Abubakar has developed a research portfolio focused on the application of mathematical optimization techniques and intelligent computational models to finance, risk prediction, healthcare classification systems, and statistical estimation problems.[3]

His academic progression from assistant lecturer to principal lecturer reflects sustained professional growth and commitment to mathematics education and research leadership. In addition to teaching and supervision responsibilities, he has participated actively in professional associations and interdisciplinary collaborations within computational mathematics and artificial intelligence.[4]

Research Profile

Hamza Abubakar obtained his Bachelor of Science in Mathematics Education from the University of Abuja in 2006, followed by a Master of Science degree in Financial Mathematics from the same institution in 2015. He later completed a Doctor of Philosophy degree in Applied Mathematics at Universiti Sains Malaysia in 2022.[5]

His academic and professional engagements include positions at Isa Kaita College of Education, Annahda International University, Universiti Sains Malaysia, and Universiti Utara Malaysia. These appointments enabled him to contribute to teaching, research mentoring, curriculum implementation, and international academic collaboration across mathematics and quantitative sciences disciplines.[6]

Research Contributions

The research contributions of Hamza Abubakar are concentrated on optimization algorithms, generalized linear models, neural network systems, and probabilistic modelling techniques. His studies on Weibull and Gamma distribution parameter estimation introduced optimization-based frameworks that integrate heuristic and artificial intelligence algorithms for statistical inference.[2]

His publications also investigate the application of Hopfield neural networks and satisfiability logic in intelligent classification systems. These studies contribute to computational intelligence by combining neural computation with optimization strategies for financial risk prediction and healthcare-related classification tasks.[3]

Publications

The publication profile of Hamza Abubakar includes peer-reviewed journal articles, conference proceedings, books, and book chapters addressing applied mathematics, computational intelligence, optimization theory, and financial analytics.[5]

  • Abubakar, H., & Sayed, A. A. I. (2025). Estimation of shifted Weibull distribution parameters using continuous Hopfield neural networks. Journal of Applied Statistics, 52(14), 1–33.
  • Abubakar, H. (2025). Random Satisfiability Logic-Driven Approach in Hopfield Neural Networks. International Journal of Applied and Computational Mathematics, 11(3), 117.
  • Ali, G. A., Abubakar, H., et al. (2023). Artificial dragonfly algorithm in the Hopfield neural network. PLOS ONE, 18(9), e0286874.
  • Abubakar, H., & Sabri, S. R. M. (2023). A Bayesian Approach to Weibull Distribution. Journal of Reliability and Statistical Studies, 16(01), 1–24.
  • Abubakar, H., & Madugu, A. (2025). Fundamentals of Mathematics in Finance: A Guide to Undergraduate Financial Mathematics. Ahmadu Bello University Press.

Research Impact

The research activities of Hamza Abubakar demonstrate interdisciplinary impact through the integration of mathematical theories with computational intelligence systems. His work contributes to broader developments in financial analytics, predictive modelling, and optimization-based machine learning approaches. Several of his studies have been indexed in internationally recognized journals and databases, increasing accessibility and scholarly visibility.[1]

In addition to research output, he has secured multiple institutional research grants under the TETFUND Institutional Based Research programme and contributed to academic administration and mentoring within the mathematics community in Nigeria.[1]

Award Suitability

Hamza Abubakar demonstrates suitability for recognition in applied mathematics and computational research due to his sustained academic contributions, interdisciplinary research portfolio, leadership in mathematics education, and involvement in international collaborations. His scholarly activities reflect a balance between theoretical mathematical development and practical computational applications.[2]

His publication record, funded projects, editorial roles, and conference participation collectively indicate active engagement in advancing quantitative sciences and intelligent computational systems. These contributions align with the objectives of international research excellence and innovation awards recognizing impactful academic scholarship.[3]

Conclusion

Hamza Abubakar has established a professional and scholarly profile grounded in applied mathematics, optimization techniques, financial modelling, and neural network systems. Through academic teaching, interdisciplinary research, conference engagement, and institutional leadership, he has contributed meaningfully to the advancement of quantitative sciences and computational methodologies. His body of work reflects ongoing dedication to mathematical innovation, research excellence, and higher education development within both regional and international academic communities.

References

  1. Elsevier. (n.d.). Scopus author details: HAMZA ABUBAKAR, Author ID 57217009001. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57217009001
  2. ORCID. (n.d.). HAMZA ABUBAKAR researcher profile.
    https://orcid.org/0000-0002-9451-0401
  3. Abubakar, H., & Sayed, A. A. I. (2025). Estimation of shifted Weibull distribution parameters using continuous Hopfield neural networks. Journal of Applied Statistics.
  4. Abubakar, H. (2025). Random Satisfiability Logic-Driven Approach in Hopfield Neural Networks. International Journal of Applied and Computational Mathematics.
  5. Universiti Sains Malaysia. (2022). Doctor of Philosophy in Applied Mathematic

Jyoti Batra | Biological Sensors | Best Researcher Award

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Best Researcher Award

Jyoti Batra, Gladstone Institutes, United States

Jyoti Batra
Affiliation Gladstone Institutes
Country United States
Scopus ID 56661930400
Documents 21
Citations 6,072
h-index 16
Subject Area Molecular Virology, Proteomics, Functional Genomics
Event Global Sensor Awards
ORCID 0000-0002-2335-0607

Jyoti Batra is a molecular virologist and proteomics researcher recognized for contributions to the understanding of virus–host interaction networks, immune evasion mechanisms, and cross-species viral transmission. Her research integrates systems-level molecular sensing approaches with advanced proteomic technologies to investigate emerging RNA viruses, including Ebola virus, influenza virus, and SARS-CoV-2. Her work has contributed to the identification of host restriction factors, therapeutic targets, and molecular determinants associated with zoonotic risk and viral pathogenesis.[1]

Abstract

Jyoti Batra’s research portfolio focuses on molecular virology, systems biology, and host–pathogen interactions. Her studies employ affinity purification mass spectrometry, interaction mapping, CRISPR-based methodologies, and functional genomics to characterize how viruses manipulate host cellular systems. Her work has contributed to understanding immune evasion, viral replication, mitochondrial targeting, and cross-species adaptation in major viral pathogens. Publications in journals such as Cell, Nature, Science, EMBO Journal, and Cell Host & Microbe demonstrate the translational and scientific relevance of her contributions.[2]

Keywords

  • Molecular Virology
  • Virus–Host Interactions
  • Proteomics
  • Functional Genomics
  • SARS-CoV-2
  • Ebola Virus
  • Influenza Virus
  • Immune Evasion
  • Cross-Species Transmission
  • Systems Biology

Introduction

The study of virus–host interactions has become increasingly important in understanding the emergence of infectious diseases and pandemic preparedness. Jyoti Batra has contributed extensively to this field through interdisciplinary research integrating virology, molecular biology, and systems-level proteomics. Her investigations into host restriction factors and viral immune evasion mechanisms have expanded current knowledge regarding zoonotic transmission and viral adaptation in mammalian hosts.[3]

Her research career includes appointments at Gladstone Institutes and Georgia State University, where she participated in collaborative international studies involving emerging viral pathogens. These studies have influenced ongoing research in antiviral drug development, host-targeted therapeutic strategies, and viral systems biology.[4]

Research Profile

Jyoti Batra serves as a Staff Research Scientist at Gladstone Institutes in San Francisco, California. Her expertise includes proteomics-based molecular sensing, interaction network analysis, molecular cloning, RNA sequencing, CRISPR technologies, viral infection assays, and computational analysis platforms such as Cytoscape and MaxQuant.[5]

She completed doctoral training in molecular virology through Monash University Malaysia and the International Centre for Genetic Engineering and Biotechnology in India. Earlier academic training in biochemistry was completed at the University of Delhi. Her educational and research trajectory reflects sustained engagement with infectious disease biology and molecular mechanisms of viral replication.[6]

Research Contributions

Batra’s research has significantly contributed to understanding how viruses interact with host proteins and cellular pathways. Her investigations into Ebola virus replication identified host regulators such as RBBP6 and uncovered non-canonical protein interactions associated with viral RNA synthesis and immune modulation.[1]

Her collaborative work during the COVID-19 pandemic contributed to landmark proteomic and phosphoproteomic studies that mapped SARS-CoV-2 interactions with host cellular machinery. These studies identified host proteins associated with viral replication and provided insight into potential therapeutic targets and antiviral intervention strategies.[3]

A notable recent contribution involved comparative coronavirus interaction mapping in bat and human cells, revealing network rewiring mechanisms associated with immune evasion and zoonotic potential. The work identified amino acid substitutions functioning as molecular switches that altered mitochondrial targeting and host interaction profiles across species.[1]

  • Development of cross-species interactome mapping platforms.
  • Identification of host restriction factors in bat cells.
  • Discovery of host proteins regulating Ebola virus infection.
  • Proteomic analyses of SARS-CoV-2 infection pathways.
  • Research on influenza virus nuclear import and apoptosis pathways.

Publications

Jyoti Batra has authored and co-authored numerous peer-reviewed publications in internationally recognized scientific journals. Several publications have been associated with high-impact discoveries in virology, systems biology, and host-pathogen interaction mapping.[5]

  1. Batra J. et al. Coronavirus protein interaction mapping in bat and human cells reveals network rewiring governing immune evasion and zoonotic potential. Cell Host & Microbe, 2026.
  2. Batra J. et al. Non-canonical proline-tyrosine interactions with multiple host proteins regulate Ebola virus infection. EMBO Journal, 2021.
  3. Bouhaddou M. et al. The Global Phosphorylation Landscape of SARS-CoV-2 Infection. Cell, 2020.
  4. Gordon D.E. et al. Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. Science, 2020.
  5. White K.M. et al. Plitidepsin has potent preclinical efficacy against SARS-CoV-2 by targeting the host protein eEF1A. Science, 2021.

Research Impact

The scientific contributions of Jyoti Batra have influenced contemporary research on emerging infectious diseases and host-targeted antiviral strategies. Her collaborative studies have been widely referenced within the scientific community and have contributed to advancing systems-level approaches in virology research.[1]

Her work on coronavirus interaction networks and proteomics has provided foundational datasets for understanding viral immune evasion and therapeutic targeting. These contributions have supported multidisciplinary collaborations across virology, structural biology, computational biology, and translational medicine.[2]

Award Suitability

Jyoti Batra’s research achievements demonstrate suitability for recognition in the fields of molecular virology, proteomics, and infectious disease biology. Her interdisciplinary investigations have contributed to the scientific understanding of viral evolution, host adaptation, and immune regulation. The breadth of her publication record, participation in high-impact international collaborations, and contributions to emerging virus research collectively support her recognition within academic and scientific award frameworks.[3]

  • Extensive expertise in virus–host interaction biology.
  • High-impact publications in internationally recognized journals.
  • Contributions to pandemic-related virology research.
  • Leadership in interdisciplinary scientific collaborations.
  • Advanced methodological contributions in proteomics and genomics.

Conclusion

Jyoti Batra has established a research profile characterized by interdisciplinary innovation, methodological rigor, and impactful contributions to molecular virology. Her work has advanced scientific understanding of host–virus interactions across several major viral pathogens and has contributed to the broader field of infectious disease research. Through collaborative and translational research initiatives, she continues to contribute to the development of systems-level approaches for studying viral pathogenesis and immune evasion.[4]

References

  1. Elsevier. (n.d.). Scopus author details: Jyoti Batra, Author ID 56661930400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56661930400
  2. Batra J. et al. (2026). Coronavirus protein interaction mapping in bat and human cells reveals network rewiring governing immune evasion and zoonotic potential. Cell Host & Microbe.
    https://doi.org/10.1016/j.chom.2026.04.015
  3. Batra J. et al. (2021). Non-canonical proline-tyrosine interactions with multiple host proteins regulate Ebola virus infection. EMBO Journal.
  4. Gordon D.E. et al. (2020). Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. Science.
  5. Gladstone Institutes. (n.d.). Research activities and institutional profile.
    https://www.gladstone.org/

Monica Mir | Biological Sensors | Innovative Research Award

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Innovative Research Award

Mònica Mir – Institute for Bioengineering of Catalonia (IBEC), Biomedical Research Center in Bioengineering (CIBER-bbn), and University of Barcelona, Spain

Mònica Mir
Affiliation IBEC, CIBER-bbn, University of Barcelona
Country Spain
Scopus ID 12647442200
Documents 60
Citations 2,256
h-index 22
Subject Area Biomedical Engineering, Biosensors, Organ-on-a-Chip
Event Global Sensor Awards
ORCID 0000-0002-1490-8373

Mònica Mir is a Spanish biomedical engineer and researcher recognized for her contributions to biosensors, microfluidic systems, point-of-care diagnostics, and organ-on-a-chip technologies. Her interdisciplinary research integrates bioengineering, nanotechnology, and translational medicine to improve disease diagnostics and develop advanced in vitro disease models for neurological and neurodegenerative disorders.[1] She has contributed extensively to blood-brain barrier-on-a-chip systems, electrochemical biosensors, and neurovascular modeling platforms designed for personalized medicine and pharmaceutical evaluation.[2]

Abstract

This academic article presents the scientific profile and research accomplishments of Dr. Mònica Mir, a senior researcher specializing in biomedical engineering and biosensor technologies. Her work focuses on translational bioengineering approaches for disease diagnosis, monitoring, and advanced in vitro modeling systems. Dr. Mir has contributed significantly to the development of electrochemical biosensors, blood-brain barrier-on-a-chip systems, neurovascular models, and implantable sensing devices. Her collaborative and interdisciplinary research has supported advances in personalized medicine, neurodegenerative disease studies, and point-of-care technologies.[3]

Keywords

Biomedical Engineering; Biosensors; Organ-on-a-Chip; Blood-Brain Barrier; Microfluidics; Electrochemical Sensors; Point-of-Care Systems; Neuroengineering; Nanobiotechnology; Translational Medicine; Alzheimer’s Disease; Personalized Medicine

Introduction

The integration of bioengineering and nanotechnology has transformed modern healthcare research by enabling sophisticated diagnostic and therapeutic platforms. Among the leading contributors in this field is Dr. Mònica Mir, whose research addresses the need for reliable biosensing systems and physiologically relevant disease models.[4] Her scientific contributions are particularly relevant to neurological diseases, blood-brain barrier functionality, and organ-on-a-chip technologies designed to emulate complex biological environments.[5]

Dr. Mir’s academic journey includes training in analytical chemistry, chemical engineering, biotechnology, and biosensor technologies at institutions including the Universitat Rovira i Virgili, the University of Bath, and the Max Planck Institute. Her multidisciplinary expertise has enabled her to bridge engineering methodologies with biomedical applications.[1]

Research Profile

Dr. Mir currently serves as a Consolidated Senior Researcher at the Biomedical Research Center in Bioengineering (CIBER-bbn) and as Assistant Professor at the University of Barcelona. Her research profile reflects more than two decades of experience in translational bioengineering and biosensor development.[1]

Her scientific activities encompass biosensors, microfluidics, neurovascular modeling, implantable electrochemical devices, and organ-on-a-chip systems. She has coordinated European Union and national research projects focused on personalized medicine, blood-brain barrier models, and neurodegenerative disease monitoring platforms.[5]

  • Principal Investigator of the EIC Pathfinder Challenge project “IV-Lab” focused on implantable smart sensing systems.
  • Lead investigator of the eBRAIN project involving hippocampal blood-brain barrier-on-a-chip technologies.
  • Scientific Coordinator for collaborative industrial projects involving HPV diagnostic point-of-care systems.
  • Mentor and supervisor for doctoral, master’s, and postdoctoral researchers in biomedical engineering.

Research Contributions

One of Dr. Mir’s notable contributions is the development of advanced blood-brain barrier-on-a-chip models integrated with microelectrodes and electrochemical sensing systems. These platforms provide realistic physiological environments for evaluating nanoparticle permeability, neurovascular interactions, and therapeutic responses associated with neurodegenerative diseases such as Alzheimer’s disease.[3]

Her research has also explored implantable electrochemical microsensors for monitoring oxygen and pH levels in fetal ischemia and hypoxia studies. These technologies demonstrate potential clinical utility in prenatal diagnostics and real-time physiological monitoring.[4]

Dr. Mir has contributed to biosensor integration within organ-on-a-chip systems, enabling improved monitoring of biological responses and enhanced analytical performance for translational medicine applications.[5]

  • Development of neurovascular unit-on-a-chip technologies.
  • Electrochemical immunosensors for Alzheimer’s disease biomarker detection.
  • Microfluidic biosensing systems for cancer liquid biopsy applications.
  • Implantable multiparametric microsensors for physiological monitoring.

Publications

Dr. Mir has authored more than 59 peer-reviewed scientific publications, including articles in high-impact journals such as ACS Sensors, Journal of Nanobiotechnology, Materials Today Bio, and Biosensors & Bioelectronics.

  1. Arellano, A. et al. (2025). Attenuation of blood-brain barrier dysfunction by functionalized gold nanoparticles against amyloid-β peptide in an Alzheimer’s disease-on-a-chip model. Materials Today Bio.
  2. Palma-Florez, S. et al. (2024). Neurovascular unit on a chip: The relevance and maturity as an advanced in vitro model. Neural Regeneration Research.
  3. Mir, M. et al. (2022). Biosensors Integration in Blood−Brain Barrier-on-a-Chip. ACS Sensors.
  4. Marrugo-Ramírez, J. et al. (2021). Kynurenic Acid Electrochemical Immunosensor: Blood-Based Diagnosis of Alzheimer’s Disease. Biosensors.
  5. Rivas, L. et al. (2020). Micro-needle implantable electrochemical oxygen sensor: ex-vivo and in-vivo studies. Biosensors & Bioelectronics.

Research Impact

Dr. Mir’s research has achieved measurable academic and translational impact through scientific publications, patent development, industrial collaborations, and interdisciplinary project leadership.[3] Her work has contributed to the advancement of personalized medicine and neuroengineering by improving experimental disease modeling systems and biosensor technologies.

Her scientific output includes over 2180 citations and an h-index of 21 according to Scopus metrics. She has served as editor and reviewer for several international journals and funding agencies, including the Swiss National Science Foundation, DBT India Alliance, and Agence Nationale de la Recherche.[1]

In addition to academic contributions, Dr. Mir co-founded the spin-off company NewCo S.L., highlighting the translational and entrepreneurial dimensions of her research activities.[2]

Award Suitability

Dr. Mònica Mir demonstrates strong suitability for recognition in biomedical engineering and biosensor innovation due to her sustained contributions to translational healthcare technologies. Her interdisciplinary expertise in organ-on-a-chip systems, electrochemical biosensors, and neuroengineering aligns with contemporary priorities in personalized medicine and biomedical diagnostics.[9]

Her leadership in European and national research initiatives, mentorship activities, editorial responsibilities, and technology transfer initiatives further support her profile as a distinguished researcher contributing to both scientific advancement and societal healthcare applications.[4]

Conclusion

Dr. Mònica Mir has established a significant research career in biomedical engineering, biosensors, and organ-on-a-chip technologies. Her scientific achievements reflect interdisciplinary innovation, translational healthcare applications, and collaborative research leadership. Through her contributions to biosensing systems, neurovascular disease models, and implantable diagnostic technologies, she continues to advance the field of biomedical engineering and translational medicine.[5]

References

  1. Elsevier. (n.d.). Scopus author details: Mònica Mir, Author ID 12647442200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=12647442200
  2. Mir, M. et al. (2022). Biosensors Integration in Blood−Brain Barrier-on-a-Chip. ACS Sensors.
    https://doi.org/10.1021/acssensors.2c00123
  3. Palma-Florez, S. et al. (2024). Neurovascular unit on a chip: The relevance and maturity as an advanced in vitro model. Neural Regeneration Research.
  4. Marrugo-Ramírez, J. et al. (2021). Kynurenic Acid Electrochemical Immunosensor: Blood-Based Diagnosis of Alzheimer’s Disease. Biosensors.
  5. Palma-Florez, S. et al. (2023). BBB-on-a-chip with integrated micro-TEER for permeability evaluation. Journal of Nanobiotechnology.

Dr. Khaled Alhawiti | Parkinson’s Monitoring | Best Researcher Award

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Dr. Khaled Alhawiti | Parkinson’s Monitoring | Best Researcher Award 

Dr. Khaled Alhawiti | Parkinson’s Monitoring | University of Tabuk | Saudi Arabia

Dr. Khaled M. Alhawiti is an accomplished Associate Professor in the Faculty of Computers and Information Technology at the University of Tabuk, recognized for his scholarly contributions in artificial intelligence, natural language processing, and Arabic language processing. He completed his Ph.D. in Computer Science from the University of Wales, Bangor University, where he focused on computational models and language technologies that support intelligent information processing. His academic path includes a Master of Science in Information Technology from the University of Technology Malaysia and a Bachelor’s degree in Computer Science from the University of Jordan, reflecting strong foundations in computing and higher education across multiple countries. Professionally, Dr. Khaled M. Alhawiti has built extensive experience in teaching, mentoring, research development, and academic leadership, actively contributing to curriculum enhancement and collaborative research initiatives within his institution and beyond. His research interests span artificial intelligence, data science, natural language processing, Arabic text modeling, speech-based systems, and intelligent educational technologies. He possesses strong research skills in machine learning, adaptive modeling, text compression techniques, rule-based systems, language preprocessing, and large-scale corpus analysis. His publications have been widely cited and indexed in Scopus and leading AI venues, demonstrating the impact of his contributions to computational linguistics and AI-driven text analysis. Dr. Khaled M. Alhawiti has collaborated on multiple international research activities, contributing to academic exchanges across Saudi Arabia, Malaysia, the United Kingdom, and Jordan, strengthening global partnerships in computer science. His awards and honors include recognition for high-impact publications, contributions to AI education research, and active participation in academic committees and professional societies. He is also associated with leading research communities such as IEEE and ACM, promoting engagement in emerging technological advancements.

Professional Profiles: ORCID  | Google Scholar

Featured Publications 

  1. Alhawiti, K. M. (2014). Natural language processing and its use in education. 161 citations.

  2. Alhawiti, K. M. (2015). Advances in artificial intelligence using speech recognition. 42 citations.

  3. Alhawiti, K. M. (2014). Adaptive models of Arabic text. 20 citations.

  4. Zerrouki, T., Alhawiti, K., & Balla, A. (2014). Autocorrection of Arabic common errors for large text corpus. 16 citations.

  5. Teahan, W. J., & Alhawiti, K. M. (2015). Preprocessing for PPM: Compressing UTF-8 encoded natural language text. 13 citations.

  6. Elfaki, A. O., Alhawiti, K. M., AlMurtadha, Y. M., Abdalla, O. A., & Elshiekh, A. A. (2014). Rule-based recommendation for supporting student learning-pathway selection. 13 citations.

  7. Alhawiti, K. M. (2014). Adaptive Arabic text modeling using computational techniques. (Derived from thesis-related work). 20 citations.

Mr. Mohamed Hamroun | Healthcare | Breakthrough Research Award

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Mr. Mohamed Hamroun | Healthcare | Breakthrough Research Award

Mr. Mohamed Hamroun | Healthcare | XLIM/ University of Limoges | France

Dr. Mohamed Hamroun is an accomplished computer scientist and engineer specializing in artificial intelligence, image processing, and multimodal information retrieval. Currently serving as a researcher and lecturer at the 3iL School and the XLIM Laboratory at the University of Limoges, France, he has made significant contributions to the fields of deep learning, computer vision, and semantic data indexing. His multidisciplinary expertise spans across AI, VR/AR systems, big data analytics, and intelligent information retrieval systems, positioning him as a leading researcher in computational intelligence and multimedia data analysis. Through his work, Dr. Hamroun has advanced both theoretical understanding and practical applications of machine learning and artificial intelligence for complex visual and semantic data challenges.

Professional Profile

Google Scholar

Summary of Suitability for the “Breakthrough Research Award” 

Dr. Mohamed Hamroun is an exceptionally qualified candidate for the Research for Breakthrough Research Award, demonstrating a strong academic foundation, extensive research experience, and impactful scientific contributions in the fields of artificial intelligence (AI), image processing, deep learning, and multimodal information retrieval.

Education

Dr. Hamroun’s academic journey reflects a deep commitment to advancing computer science and AI-driven data analysis. He earned his Ph.D. in Computer Science from the University of Bordeaux, where his doctoral research focused on “Indexing and retrieval by visual, semantic, and multi-level content of multimedia documents,” under the supervision of Professors Henri Nicolas and Ikram Amous. His doctoral work bridged the gap between computational semantics and large-scale multimedia information retrieval. He later completed his Habilitation to supervise research at the University of Limoges, where his postdoctoral contributions were consolidated into a major research theme titled “Contributions to indexing and information retrieval: application to generalist and medical multimodal data,” under the guidance of Professor Damien Sauveron. Before his doctoral studies, he obtained a Computer Engineering degree from the University of Sfax, Tunisia, and a Bachelor’s degree in Computer Science from the same institution. His undergraduate and graduate projects revolved around multilingual search engine development and database management systems, establishing his foundation in applied informatics and intelligent systems.

Professional Experience

Dr. Hamroun’s professional experience demonstrates a steady trajectory of academic excellence and applied innovation. He began his career as an R&D Engineer at SIM-SOFT in Tunisia, where he was involved in software development and data-driven industrial applications. Following this, he pursued his Ph.D. research jointly between the University of Bordeaux and the University of Sfax, working on hybrid semantic and visual content retrieval models. After completing his Ph.D., he joined the XLIM Laboratory at the University of Limoges as a Postdoctoral Researcher, where he focused on the integration of deep learning and ontology-based frameworks for medical and multimedia data analysis. Later, he was appointed as a Lecturer at EILCO Engineering School in France, contributing to both teaching and research in computer science and artificial intelligence. He now holds the position of Associate Professor at 3iL Engineering School, affiliated with the XLIM Laboratory, where he supervises research projects and mentors graduate students in AI, machine learning, and multimedia information systems.

Research Interests

Dr. Hamroun’s research interests cover a wide spectrum of computational and artificial intelligence domains. His core expertise includes image and signal processing, deep learning architectures for data classification and clustering, virtual and augmented reality applications, and semantic data mining. His studies often combine statistical learning, ontology modeling, and multimodal data fusion to enhance human-computer interaction and knowledge extraction. A significant part of his current research focuses on developing intelligent systems for multimodal medical data retrieval and applying AI to improve healthcare diagnostics and decision support. His recent work also extends to federated learning frameworks and semantic interpretation in multimedia environments, bridging applied computer science with real-world AI applications.

Awards

Dr. Hamroun has been recognized for his innovative research in artificial intelligence and multimedia information systems through various academic honors and nominations. His outstanding work in deep learning-based image analysis and computational semantics has earned him recognition among peers in the international AI research community. He has contributed as a co-author to several highly cited papers and participated in collaborative European research projects aimed at integrating AI into real-world industrial and medical systems. His nomination for the award highlights his leadership in combining artificial intelligence with practical problem-solving across domains such as emotion recognition, diabetic foot ulcer diagnosis, and semantic retrieval.

Publication Top Notes

  • Title: Emotion recognition from speech using spectrograms and shallow neural networks
    Authors: A. Slimi, M. Hamroun, et al.
    Year: 2020
    Citations: 47

  • Title: DFU-Siam: A novel diabetic foot ulcer classification with deep learning
    Authors: M. S. A. Toofanee, M. Hamroun, et al.
    Year: 2023
    Citations: 43

  • Title: A survey on intention analysis: successful approaches and open challenges
    Authors: M. Hamroun
    Year: 2020
    Citations: 21

  • Title: An interactive engine for multilingual video browsing using semantic content
    Authors: M. B. Halima, M. Hamroun, et al.
    Year: (arXiv preprint, circa 2013)
    Citations: 16

  • Title: DFU-Helper: Innovative framework for longitudinal diabetic foot ulcer evaluation using deep learning
    Authors: M. S. A. Toofanee, M. Hamroun, et al.
    Year: 2023
    Citations: 11

Dr. Wanderimam Tuktur | Medical | Best Researcher Award

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Dr. Wanderimam Tuktur | Medical | Best Researcher Award

Dr. Wanderimam Tuktur | Medical | DC Department of Health | United States

Dr. Wanderimam R. Tuktur, MBBS, MPH, PhD, is an accomplished and analytical public health professional with over twelve years of diverse experience in epidemiological research, geospatial analysis, health equity, and community-focused health interventions. Currently serving as a Public Health Analyst at the District of Columbia Department of Health, Office of Health Equity, he is dedicated to addressing the root causes of health disparities and advancing data-driven policies that promote equitable health outcomes for all communities. Dr. Tuktur’s professional journey reflects a seamless integration of clinical expertise and public health research, having previously held roles as an Epidemiologist at the Virginia Department of Health, a Research Analyst at Capital Area Health Network, and a Research Associate at Virginia Commonwealth University. His research and analytical proficiency span a wide spectrum, including predictive modeling, GIS-based health mapping, and the development of innovative tools like the DC Health Opportunity Index—an evidence-based framework for understanding social determinants of health.

Professional Profile

ORCID

Suitability Summary

Dr. Wanderimam R. Tuktur is exceptionally well-qualified for the Best Researcher Award, standing out as a seasoned and analytical public health professional with over 12 years of diverse experience spanning epidemiological research, geospatial analysis, health equity studies, and quantitative/qualitative data analytics. His multidisciplinary expertise bridges medicine, data science, and public health, demonstrating excellence in both applied research and community-focused interventions.

Education

  • Doctorate Degree in Public Health (Epidemiology) – Walden University, 2024

  • Master of Public Health (Global Health) – Liberty University, 2017

  • Bachelor of Medicine, Bachelor of Surgery (MBBS) – Ahmadu Bello University, 2012

Professional Experience

  • Public Health Analyst | District of Columbia Department of Health, Office of Health Equity (2022 – Present)
    Leads data-driven projects and research to address social determinants of health and health disparities. Oversees the DC Health Opportunity Index development, manages equity programs such as the Advancing Health Literacy Project (AHLP), and supports multi-sector collaborations aimed at improving population health outcomes and advancing health equity in Washington, D.C.

  • Epidemiologist | Virginia Department of Health, Office of Health Equity (2021 – 2022)
    Applied epidemiological and geospatial methods to identify health disparities, performed predictive modeling, and guided public health policy through data-informed recommendations for improving healthcare access across Virginia.

  • Data/Research Analyst | Capital Area Health Network (2021 – 2022)
    Ensured integrity of clinical and financial data systems, analyzed data for accurate reporting to HRSA, and trained staff in health information management software.

  • Research Analyst | Capital Area Analytica Inc. (capAHEC Data Center) (2018 – 2021)
    Conducted predictive modeling on healthcare disparities, managed large datasets, and generated insights for public health policies aimed at underserved communities.

  • Research Associate | Virginia Commonwealth University, Department of Family Medicine & Population Health (2017 – 2018)
    Contributed to a longitudinal cohort study on stress and social disparities in diabetes, managed community-based research partnerships, and supported manuscript preparation for publication.

  • Teaching Instructor | Liberty University, School of General Studies (2015 – 2016)
    Delivered undergraduate instruction, developed course materials, and provided academic mentorship to enhance student learning outcomes.

  • Teaching Assistant | Liberty University, Department of Public & Community Health (2016 – 2017)
    Supervised student projects, supported professors in course delivery, and participated in simulation-based teaching sessions.

  • Medical Officer | National Assembly Clinic & National Hospital, Abuja, Nigeria (2013 – 2015)
    Delivered inpatient and outpatient care, performed clinical evaluations, and participated in rotations across Surgery, Medicine, Pediatrics, and Obstetrics & Gynecology.

Achievements

  • Led the creation of the DC Health Opportunity Index, a comprehensive data visualization tool mapping health inequities and social determinants across Washington, D.C.

  • Directed the Advancing Health Literacy Project (AHLP), resulting in a model toolkit and curriculum for community-based organizations.

  • Provided epidemiological and analytic leadership in multiple CDC-funded Health Disparities Grants, improving COVID-19 vaccine outreach and equity strategies.

  • Developed predictive geospatial models to identify High Priority Health Target Areas in Virginia, influencing healthcare access and policy designations.

  • Published reports and guided evidence-based policymaking to address health disparities in marginalized populations.

Awards and Honors

  • Certificate of Practicing License as a General Practitioner

  • Certificate of Completion – Collaborative Institutional Training Initiative (CITI) in Responsible Conduct of Research (RCR) and Human Subjects Research (HSR), Liberty University

  • Program Evaluation Training Certification, Ahmadu Bello University

  • Sphere Training Certification on Humanitarian and Disaster Relief

  • Virginia Commonwealth University Medication Management Training

  • American Red Cross First Aid and CPR Certification

  • Guest Lectureship Recognition, Liberty University (2015–2017)

Professional Memberships and Affiliations:

  • Active Member, Rotary Club of Richmond, Virginia

  • Member, Academy of Nutrition and Dietetics

  • Member, American Public Health Association

Publication Top Notes

A Geographic Weighted Regression Analysis of the Health Opportunity Index and Stroke Prevalence in Health and Human Services Region 3
Metachronous Malignancy (Pancreatic Endocrine Neoplasm And Renal Cell Carcinoma): Case Report.

Ms. Soree Hwang | Healthcare Intelligence Awards | Best Sensor for Health Monitoring Award

Posted on by Global Sensor Awards

Ms. Soree Hwang | Healthcare Intelligence Awards | Best Sensor for Health Monitoring Award 

Ms. Soree Hwang, Korea Institute of Science and Technology (KIST), South Korea

So Ree Hwang is a dedicated researcher in the field of biomedical engineering currently pursuing her Ph.D. at Korea University. She holds a Master’s degree in Design and Engineering from Seoul National University of Science and Technology and a Bachelor’s degree in Mechanical Engineering from Korea Aerospace University. Since May 2022, she has been a student researcher at the Korea Institute of Science and Technology (KIST), where she contributes to the development of AI-based health management platforms, including lifelog acquisition systems and fatigue and stress detection technologies. Her research also focuses on gait analysis and stroke assessment using motion signal processing and wearable devices. So Ree has published numerous papers as a main and co-author in reputable journals such as Sensors, Frontiers in Human Neuroscience, and IEEE journals. Her work integrates machine learning and biomedical signal analysis to advance rehabilitation technologies and health monitoring systems.

Professional Profile:

GOOGLE SCHOLAR

SCOPUS

Summary of Suitability for Best Researcher Award – So Ree Hwang

Dr. So Ree Hwang is a highly suitable candidate for the Best Researcher Award in the domain of health monitoring and biomedical engineering, with a strong multidisciplinary background and an impressive portfolio of impactful, AI-integrated sensor-based research.

🎓 Education

  • Ph.D. in Biomedical Engineering
    Korea University, Seoul, Republic of Korea (2021 – Present)

  • M.S. in Design and Engineering
    Seoul National University of Science and Technology, Seoul, Republic of Korea (2018 – 2020)

  • B.S. in Mechanical Engineering
    Korea Aerospace University, Goyang-si, Republic of Korea (2011 – 2017)

💼 Work Experience

  • Student Researcher – Korea Institute of Science and Technology (KIST)
    📍 Seoul, Republic of Korea (2022.05.01 – Present)

    • 🧠 Developed a lifelog system and AI-based fatigue/stress management platform

    • 🚶‍♂️ Contributed to gait analysis tech for knee disorder recovery

    • 🧪 Worked on motion signal-based stroke assessment technologies

  • Research Intern – Korea Institute of Science and Technology (KIST)
    📍 Seoul, Republic of Korea (2020.03.01 – 2021.12.31)

    • 🧠 Focused on stroke assessment using motion signal analysis

🏆 Achievements & Research Contributions

  • 📝 8 SCI-indexed papers as main or co-author, including in top journals like Sensors, Frontiers in Human Neuroscience, and IEEE

    • 📊 Topics: Gait phase classification, stroke severity assessment, fatigue detection using AI, wearable systems

  • ⚙️ First-author of applied engineering papers on 3D printing and IMU validation

  • 🤖 Integrated machine learning models (CNN-LSTM-Attention, RNNs) into biomedical signal analysis

  • 🧩 Contributed to the advancement of intelligent health monitoring and gait recovery systems

Publication Top Notes:

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Mr. Foad Zahedi | Digital Twin Awards | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Foad Zahedi | Digital Twin Awards | Best Researcher Award 

Mr. Foad Zahedi, Washington State University, Iran

Foad Zahedi is a seasoned Procurement Director with over 18 years of comprehensive experience in procurement management, technical management, and contract management across a diverse range of projects, including multipurpose complexes, dams, roads, tunnels, and industrial structures. Based in Tehran, Iran, he has successfully led procurement and purchase engineering efforts to ensure optimal logistics, quality, and cost-effectiveness. Foad’s expertise encompasses tender management, contract oversight, and project management, where he skillfully navigates the complexities of EPC, PC, and E projects from both the employer and contractor perspectives. He holds a Master’s degree in Civil Engineering (Construction Management) and another Master’s in Civil Engineering (Marine Structures Engineering) from Islamic Azad University, along with a Bachelor’s degree in Civil Engineering. A certified Project Management Professional (PMP) and a Professional Engineer, Foad is proficient in areas such as cost estimation, value engineering, and building information modeling. His strategic insights and consultancy roles for boards and CEOs have been pivotal in aligning project goals with organizational objectives.

Professional Profile:

GOOGLE SCHOLAR

Research for Best Researcher Award – Foad Zahedi

Profile Overview: Foad Zahedi has over 18 years of extensive experience in procurement and project management across a variety of large-scale civil engineering projects, including multipurpose complexes, dams, and tunnels. His diverse skill set encompasses technical management, contract management, and procurement engineering, showcasing his ability to lead complex projects effectively.

Education 🎓

  • M.S. Civil Engineering (Construction Management)
    Islamic Azad University of Central Tehran Branch, Tehran, IR
    GPA: 3.53 | Year: 2020
  • M.S. Civil Engineering (Marine Structures Engineering)
    Islamic Azad University of Science and Research Branch, Tehran, IR
    GPA: 3.72 | Year: 2016
  • B.S. Civil Engineering
    Islamic Azad University of Shahr-e-kord Branch, Shahrekord, IR
    Year: 2004

Work Experience 💼

  • Procurement Director
    Iran Mall, Tehran, Iran
    Years: 20XX – Present

    • Led procurement and purchase engineering management for various complex projects, ensuring high quality and timely logistics support.
    • Managed the technical office, handling invoices, quantity surveying, and as-built drawings in EPC, PC, and E projects.
    • Conducted national and international tenders, preparing comprehensive technical and financial submissions.
    • Oversaw contract management in diverse roles (Employer, Contractor, Consultant) for EPC, PC, and E projects.
    • Provided consultancy to boards and CEOs, developing strategic plans to achieve project goals.

Achievements 🌟

  • Successfully managed procurement for multiple large-scale projects, including multipurpose complexes, dams, and industrial structures.
  • Developed effective strategies for cost estimation and value engineering, resulting in significant savings for projects.
  • Implemented advanced Building Information Modelling (BIM) and soil-structure interaction modelling techniques to enhance project outcomes.

Awards and Honors 🏆

  • Project Management Professional (PMP)
    Licensure #: 3203610 | Year: 2022
  • Professional Engineer (Grade 2: Supervision)
    Licensure #: 17-31-12174 | Year: 2014
  • Professional Engineer (Grade 1: Construction)

Publication Top Notes:

Global BIM Adoption Movements and Challenges: An Extensive Literature Review
Development of a BIM Implementation Roadmap: The Case of Iran
Robot-BIM integration for underground canals life-cycle management
Digital Twins in the Sustainable Construction Industry
BIM Implementation for PMBOK Enhancement in the Construction Industry

Prof. Dr. Mahmoud Abulmeaty | Remotecare Awards | Best Researcher Award

Posted on by Global Sensor Awards

Prof. Dr. Mahmoud Abulmeaty | Remotecare Awards | Best Researcher Award 

Prof. Dr. Mahmoud Abulmeaty, King Saud University, Saudi Arabia

Mahmoudd Mustafa Ali Abulmeaty is an esteemed Egyptian academic and physician specializing in clinical nutrition and metabolism. Dakahlia Governorate, Egypt, he earned his M.B. B.Ch. from Zagazig University in 2003 with honors. He further pursued advanced studies, obtaining a Master’s degree in Basic Medical Sciences (Physiology) in 2007 and an M.D. in Medical Physiology in 2012, both from Zagazig University. Abulmeaty has also earned multiple certifications, including those in obesity management, acupuncture, and clinical nutrition. He has held various academic positions, starting as an intern at Zagazig University Hospitals in 2004, then progressing through roles as demonstrator, assistant lecturer, and clinical nutritionist. In 2012, he joined King Saud University in Riyadh, Saudi Arabia, where he has served as an assistant professor, associate professor, and is currently a professor of clinical nutrition and metabolism. His professional expertise extends to weight reduction clinics and therapeutic nutrition, where he also serves as a physician consultant. With a wealth of experience and expertise in obesity management and clinical nutrition, Abulmeaty is recognized for his contributions to both research and clinical practice in these fields.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Dr. Mahmoudd Mustafa Ali Abulmeaty

Dr. Mahmoudd Mustafa Ali Abulmeaty stands out as a distinguished academic and researcher in the field of clinical nutrition, obesity management, and metabolism. His academic qualifications, extensive experience, and significant contributions to the medical and scientific community make him a strong contender for the Best Researcher Award.

Education:

  • October 2003: M.B. B.CH. (Total grade: Excellent with Honors), Faculty of Medicine, Zagazig University, Egypt
  • November 2007: M.Sc. in Basic Medical Sciences (Physiology), Faculty of Medicine, Zagazig University, Egypt
  • August 2008: Professional Certificate in Obesity Management (Children & Adults), Cairo University, Egypt
  • January 2009: Professional Certificate in Acupuncture, Zagazig University, Egypt
  • November 2009: Professional Certificate in Office Management of Obesity, American Medical Association, USA
  • April 2011: Diploma in Endocrinology and Metabolism, Faculty of Medicine for Girls, Al Azhar University, Egypt
  • July 2011: ESPEN Diploma in Clinical Nutrition & Metabolism, Faculty of ESPEN, European Union
  • March 2012: M.D. in Medical Physiology, Zagazig University, Egypt
  • September 2012: Diploma in Clinical Nutrition, AICPD, Egypt
  • November 2017: Fellowship FACN, American College of Nutrition, USA

Work Experience:

  • March 2004: Intern at Zagazig University Hospitals
  • July 2005: Demonstrator of Physiology, Faculty of Medicine, Zagazig University
  • April 2008: Assistant Lecturer in the Endocrine Research Unit, Physiology Department, Faculty of Medicine, Zagazig University
  • July 2011: Clinical Nutritionist in Obesity Management and Research Unit, Faculty of Medicine, Zagazig University
  • April 2012: Lecturer in Medical Physiology Department and Obesity Management and Research Unit, Faculty of Medicine, Zagazig University
  • September 2012: Assistant Professor, Clinical Nutrition Program, and Senior Registrar, Weight Reduction Clinic, Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University
  • January 2018–2022: Associate Professor of Clinical Nutrition and Metabolism, Clinical Nutrition Program, and Physician Consultant at Primary Care Clinic and Therapeutic Nutrition Clinic, Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University
  • June 2022–Present: Professor of Clinical Nutrition and Metabolism, Clinical Nutrition Program, and Physician Consultant at Primary Care Clinic and Therapeutic Nutrition Clinic, Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University
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Mr. Mohammad Ahmadi | physiological Sensors | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Mohammad Ahmadi | physiological Sensors | Best Researcher Award 

Mr. Mohammad Ahmadi, University of Auckland, New Zealand

Ted Ahmadi is a seasoned game developer based in Toronto, with a strong focus on designing Mixed/Augmented/Virtual Reality (MR/AR/VR) games using Unity3D and C#. With over 6 years of experience, he is proficient in utilizing the Microsoft Mixed Augmented Reality Toolkit (MRTK) and has expertise in designing Mixed Reality games for platforms such as Magic Leap, Vive/Vive Pro Eye, Oculus Quest/Quest 2&3/Quest Pro, HP Omnicept, Hololens 2, and Apple Vision Pro. Ted’s career spans across various aspects of game development, including 2D game design for Android using Unity3D, game networking with Photon and Ubiq, and integrating technologies like OpenGL, Blender, and iClone 3D animation toolkit. He is also skilled in using Leap Motion for enhancing interactive experiences in game applications. Beyond game development, Ted is proficient in C++/C# programming across different applications and has experience in Agile/Rapid development methodologies, Waterfall, and Continuous Integration. His expertise extends to embedded systems such as ROS in Linux/Windows, particularly in VR applications for robotics, and enterprise web server applications where he excels in Java programming, software optimization, debugging, and troubleshooting.

Professional Profile:

ORCID

 

Education

University of Auckland

  • Bachelor of Science in Computer Science
    Date: Graduated in 2018

Work Experience

Design School, University of Auckland
Teaching and Tutoring Assistant
July 2022 – Nov 2022

  • Responsibilities: Assisted in teaching and tutoring the course “Designing Mix Realities” at the School of Design.
  • Skills: Unity3D, Blender (3D modeling and animation for rapid prototyping), Adobe Aero (3D modeling).

Skills

  • Game Design: Unity3D, MRTK and XR SDK, AR Kit, AR Core, Leap Motion, OpenGL, Vuforia, Blender, iClone 7.
  • Programming: C++/C#, Java, JavaScript, PHP/CSS/HTML, jQuery, mySQL, JSON/XML, Matlab.
  • HMD: Vive/Vive Pro Eye, Oculus Quest/Quest 2/Quest 3/Quest Pro, HP Omnicept, Magic Leap, Hololens 2, Apple Vision Pro.
  • API: WebGL, OpenGL.
  • Web API: .Net/ASP.Net MVC.
  • J2EE API: Java Servlet and EJB.
  • Version Control: git and GitHub.
  • OS: Linux, Windows.
  • Embedded Systems: ROS.

Employment History

🏫 Design School, University of Auckland
Teaching and Tutoring Assistant (July 2022 – Nov 2022)

  • Teaching and tutoring assistant for the course “Designing Mix Realities” at the school of design.
  • Skills: Unity3D, Blender (3D modeling and animation for rapid prototyping), Adobe Aero (3D modeling).

Publication top Notes:

EEG, Pupil Dilations, and Other Physiological Measures of Working Memory Load in the Sternberg Task

Cognitive Load Measurement with Physiological Sensors in Virtual Reality during Physical Activity

Comparing Performance of Dry and Gel EEG Electrodes in VR using MI Paradigms

PlayMeBack – Cognitive Load Measurement using Different Physiological Cues in a VR Game