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

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.

Dr. Suvendu Mohanty | Health Monitoring | Best Sensor for Health Monitoring Award

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Dr. Suvendu Mohanty | Health Monitoring | Best Sensor for Health Monitoring Award  

Dr. Suvendu Mohanty, Indian Institute of Technology Madras, India

Dr. Suvendu Mohanty is a Postdoctoral Researcher in Mechanical Engineering at the Indian Institute of Technology Madras, specializing in machine health monitoring, predictive maintenance, and remaining useful life (RUL) estimation of mechanical systems. He holds a Ph.D. in Production Engineering from NIT Agartala, with a research focus on failure prediction of CNG-driven engines. With over a decade of academic and research experience, including prior roles as Assistant Professor, Dr. Mohanty has led and contributed to high-impact projects in collaboration with industry giants such as Walmart Inc. and Honeywell International Inc. His interdisciplinary expertise spans wear analysis, tribology, AI-driven diagnostics, and multi-sensor data fusion. A prolific researcher and active contributor to conferences and workshops, he is passionate about translating research into real-world engineering solutions that enhance reliability and sustainability in industrial systems.

Professional Profile:

SCOPUS

ORCID

GOOGLE SCHOLAR

🏅 Summary of Suitability for Best Sensor for Health Monitoring Award

Nominee: Dr. Suvendu Mohanty
Designation: Postdoctoral Researcher, Mechanical Engineering
Institution: Indian Institute of Technology Madras, India

Dr. Suvendu Mohanty is an exceptional candidate for the Best Sensor for Health Monitoring Award, recognized for his impactful research in multi-sensor data fusion, predictive diagnostics, and machine health monitoring systems. His work lies at the critical intersection of mechanical engineering, artificial intelligence, and sensor-based prognostics, directly advancing the field of health monitoring technologies for both machines and potential extensions to biomedical systems

🎓 Education

  • Ph.D. in Production Engineering
    🏫 National Institute of Technology (NIT) Agartala, India | 📅 2024
    📚 Thesis: Failure Prediction of Engine Driven by CNG Through Prognostic Approach
    📊 CGPA: 8.93/10

  • M.Tech. in Thermal Engineering
    🏫 NIT Patna, India | 📅 2013
    📚 Thesis: Analysis of Exhaust Emission of Internal Combustion Engine Using Biodiesel Blend
    📊 CGPA: 7.73/10

  • B.Tech. in Mechanical Engineering
    🏫 Bhadrak Institute of Engineering & Technology (BIET), Odisha, India | 📅 2011
    📚 Thesis: Turbulent Fluid Flow & Heat Transfer in Mixing Junction Using Gambit and Fluent
    📊 CGPA: 7.32/10

🛠️ Work Experience

  • 🔬 Postdoctoral Researcher
    🏢 Engineering Asset Management Group, Mechanical Engineering, IIT Madras
    📅 Aug 2024 – Present
    ✅ Focus: Predictive maintenance, multi-sensor data integration, AI-based diagnostics
    🤝 Industrial Collaborations: Walmart Inc., Honeywell International Inc.

  • 👨‍🏫 Assistant Professor
    🏫 Hi-Tech Institute of Technology, Bhubaneswar
    📅 June 2013 – July 2015
    🧪 Courses: IC Engine, Thermodynamics, Heat Transfer

  • 👨‍🏫 Assistant Professor
    🏫 Gandhi Institute for Education and Technology, Bhubaneswar
    📅 Aug 2015 – Dec 2016
    🧪 Courses: Mechanical Measurements, Heat Transfer, Labs

🏆 Achievements

  • 🔧 Successfully executed multiple research collaborations with Honeywell and Walmart Inc. on predictive maintenance and diagnostics.

  • 📊 Developed AI-integrated health monitoring systems for rotating machinery and induction motors.

  • 📝 Published and presented several research papers in national seminars and workshops.

  • 🧪 Led experimental diagnostics on bearing systems using the Honeywell Versatile Transmitter (HVT) system.

🥇 Awards & Honors

  • 🧭 Postdoctoral Research Fellowship, IIT Madras (2024–Present)

  • 🏅 Organising Committee Member – International Conference on Next Generation Technologies: Design and Manufacturing (ICNGT), IIT Madras, Nov 2024

  • 🏅 Organising Member, FFMA-2012, NIT Patna

  • 🧠 National Cyber Olympiad Participant – Science Olympiad Foundation

  • 🎤 Seminar Presenter – RTMERAF at the Institution of Engineers, Tripura

  • 🎓 Workshop Participation – CTSR and ECED programs at NIT Agartala

Publication Top Notes:

Maintenance analytics for achieving sustainability using CNG as alternative fuel

A frame work for comparative wear based failure analysis of CNG and diesel operated engines

Application of Artificial Intelligence for Failure Prediction of Engine Through Condition Monitoring Technique

Fractal mathematics applications for wear image analysis of engines using biofuels

Artificial Neural Network coupled Condition Monitoring for advanced Fault Diagnosis of Engine

Experimental Investigation of Tribo-Corrosive Nature of Biodiesel and its Effect on Lubricating System

Intelligent prediction of engine failure through computational image analysis of wear particle

Importance of Tribological study for Internal Combustion Engines using Biofuel

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

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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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