Kaan Koçali | Health Professions | Best Researcher Award

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Best Researcher Award

Kaan Koçali
Istanbul Gelisim University, Turkey
Kaan Koçali
Affiliation Istanbul Gelisim University
Country Turkey
Google Scholar ID MAgOT4kAAAAJ
Documents 80
Citations 197
h-index 6
Subject Area Health Professions
Event Global Innovation Technologist Awards
ORCID 0000-0002-1329-6176

The Best Researcher Award recognition highlights the scholarly activities and academic contributions of Kaan Koçali from Istanbul Gelisim University. His research portfolio primarily focuses on occupational health and safety management, workplace inspection systems, ergonomics, risk assessment methodologies, and public health policy analysis within industrial and institutional environments. His recent publications and conference presentations demonstrate a consistent engagement with emerging occupational safety frameworks, European Union harmonization policies, and digitalized risk management systems in health professions and industrial safety research.[1]

Abstract

Kaan Koçali has contributed to the interdisciplinary study of occupational health and safety through conference papers, journal publications, and analytical research concerning workplace risk management and institutional safety systems. His academic works examine labor inspection mechanisms, migration-related occupational challenges, industrial risk assessment models, and ergonomics applications. Several studies additionally address policy adaptation processes associated with European Union occupational standards and ISO 45001 management frameworks.[2]

Keywords

Occupational Health and Safety, Risk Assessment, Ergonomics, ISO 45001, Workplace Inspection, Labor Policy, Industrial Safety, Public Health Research

Introduction

Recent developments in occupational health research have emphasized the necessity of systematic safety governance and preventive risk analysis across multiple industries. Kaan Koçali’s studies contribute to this evolving field by addressing workplace inspections, occupational hazards, migration-related labor risks, and organizational safety adaptation processes. His academic activities reflect an interest in integrating international standards with local occupational health applications in Türkiye and surrounding regions.[3]

Research Profile

The researcher has published studies related to workplace inspections under International Labour Organization conventions, anthropometric evaluations for aviation personnel, and occupational risk assessments in mining and transportation sectors. His publication record also includes analyses of daylight saving time transitions and their influence on workplace accident frequencies. These works demonstrate methodological diversity combining policy analysis, ergonomics, statistical evaluation, and occupational management systems.[4]

Research Contributions

  • Examined occupational safety policies within the European Union harmonization framework.
  • Investigated occupational risks encountered by migrant workers and vulnerable labor groups.
  • Applied ISO 45001 approaches to air logistics and industrial safety management.
  • Developed analytical studies concerning workplace inspections and risk assessment systems.
  • Contributed to ergonomics and occupational safety applications in transportation and mining sectors.

Publications

  • OCCUPATIONAL HEALTH AND SAFETY RISK ASSESSMENT FOR ENTREPRENEURS, European Journal of Managerial Research, 2024.
  • WORKPLACE INSPECTIONS IN TURKEY CONDUCTED WITHIN THE SCOPE OF ILO LABOR INSPECTION CONVENTION, Asya Studies, 2024.
  • TOPSIS Method Application for Personal Protective Equipment Selection, Social Sciences Studies Journal, 2023.
  • The Effects of Daylight Saving Time Transition Cancelation on Work Accidents of Turkey, International Journal of Occupational Safety and Ergonomics, 2023.

Research Impact

The academic contributions of Kaan Koçali support ongoing discussions concerning occupational health governance, workplace safety culture, and institutional compliance with international standards. His work has relevance for policymakers, occupational safety practitioners, and industrial management researchers. Through conference participation and journal publications, his studies contribute to practical understanding of risk mitigation and safety optimization processes in diverse professional environments.[5]

Award Suitability

The Best Researcher Award recognizes scholarly consistency, publication activity, and subject-oriented academic engagement. Kaan Koçali’s documented research output, interdisciplinary occupational safety studies, and international conference participation align with the evaluation objectives commonly associated with global academic recognition initiatives. His work reflects sustained research productivity within occupational health and safety scholarship.[6]

Conclusion

Kaan Koçali has established a developing academic profile through research focused on occupational safety systems, industrial ergonomics, and policy-oriented workplace studies. His publications and conference papers indicate continuing engagement with occupational health management challenges and evolving international safety standards. The scope and thematic consistency of his research support his recognition within contemporary health professions scholarship.

References

  1. Elsevier. (n.d.). Scopus author details: Kaan Koçali, Author ID MAgOT4kAAAAJ. Scopus.
    https://scholar.google.com.tr/citations?user=MAgOT4kAAAAJ
  2. Koçali, K. (2024). Occupational Health and Safety Risk Assessment for Entrepreneurs. European Journal of Managerial Research.
    https://doi.org/10.62666/eujmr.1563551
  3. Koçali, K. (2024). Workplace Inspections in Turkey Conducted within the Scope of ILO Labor Inspection Convention. Asya Studies.
    https://doi.org/10.31455/asya.1419324
  4. Koçali, K. (2023). Anthropometric Analysis of Cabin Crew Selection Criteria Based on A380 Aircraft Model. Ergonomi.
    https://doi.org/10.33439/ergonomi.1296025
  5. Koçali, K. (2023). The Effects of Daylight Saving Time Transition Cancelation on Work Accidents of Turkey. International Journal of Occupational Safety and Ergonomics.
    https://doi.org/10.1080/10803548.2023.2221590
  6. Zenodo. (2024). Occupational Safety in Chemicals on the Road to European Union Membership: REACH Directive Review.
    https://doi.org/10.5281/ZENODO.13351752

Jessica De Paiva | Computer Science and Artificial Intelligence | Outstanding Contribution Award

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Outstanding Contribution Award

Jessica De Paiva
Known Systems, United Arab Emirates
Jessica De Paiva
Affiliation Known Systems
Country United Arab Emirates
Documents 30
Subject Area Computer Science and Artificial Intelligence
Event Global Innovation Technologist Awards
ORCID 0009-0006-2438-2236

Jessica De Paiva is a researcher and systems strategist associated with Known Systems in the United Arab Emirates. Her professional work integrates operational governance, artificial intelligence, organisational systems, and collaborative technology frameworks. Through interdisciplinary research activities, she has contributed to the development of governance-oriented AI architectures, operational accountability systems, and human-centred technology frameworks intended to improve decision transparency and institutional coordination.[1]

Abstract

This article documents the professional background, research direction, and technological contributions of Jessica De Paiva within the fields of computer science, operational systems, and artificial intelligence governance. Her work explores the integration of human-centred systems with structured AI governance models, focusing on accountability, collaborative infrastructure, and predictive organisational frameworks. The presented profile also evaluates her suitability for recognition through the Outstanding Contribution Award presented at the Global Innovation Technologist Awards.[2]

Keywords

Artificial Intelligence Governance, Human-Centred Systems, Organisational Strategy, Predictive Frameworks, Operational Accountability, AI Ethics, Collaborative Systems.

Introduction

Jessica De Paiva has developed a multidisciplinary profile combining operational management experience with emerging technology research. Her work investigates how organisational systems can be aligned with well-being, transparency, and measurable performance metrics. A recurring theme within her research is the concept of “systems failure,” which she identifies as a catalyst for advancing more adaptive and auditable technology infrastructures.[3]

Research Profile

Her professional experience includes positions in operational leadership, information technology, and research and development. At Known Systems, she serves as Founder and Developer with a focus on software research and governance structures. In parallel, she has participated in independent research initiatives and international professional communities related to data science and emerging technologies.[4]

  • Founder and Developer at Known Systems.
  • CTIO at JAR Management Services LLC.
  • Independent Research and Development contributor.
  • Participant in Women in Data Science Worldwide initiatives.

Research Contributions

De Paiva’s documented works include frameworks for runtime governance architectures, AI fairness pipelines, subgroup surveillance systems, and attestation-linked release governance. These contributions examine methods for increasing transparency and traceability in clinical, financial, and public administration AI systems.[5]

Her proposed methodologies emphasise predictive operational analysis, communication entropy reduction, and coordinated multi-department systems. Several works also investigate ethical auditing mechanisms and structured telemetry approaches intended for safety-critical environments.[6]

Publications

  • Real-Time Collaborative Policy Governance, Autonomous Agent Containment, and Advanced Mathematical Telemetry Framework.
  • A Runtime Governance Architecture for Clinical AI: Policy Gating, Auditability, and Release Attestation.
  • API-Led Integration of Legacy and Modern Clinical Data Systems.
  • Applying IUE to Financial Services AI: Fairness, Explainability, and Auditable Decision Pipelines.

Research Impact

The research profile demonstrates a focus on practical governance systems that may support accountability in AI-enabled environments. Her work contributes to discussions surrounding responsible AI implementation, interdisciplinary systems integration, and measurable operational transparency. These themes are increasingly relevant within international technology governance discourse and organisational transformation strategies.[2]

Award Suitability

Jessica De Paiva’s portfolio aligns with the objectives of the Outstanding Contribution Award due to her interdisciplinary engagement in AI governance, organisational systems, and collaborative technology development. Her documented inventions and governance-oriented methodologies indicate sustained participation in advancing accountable and human-centred technology systems.[5]

Conclusion

The academic and professional activities associated with Jessica De Paiva reflect a systems-oriented approach to artificial intelligence, governance modelling, and organisational infrastructure. Her work contributes to emerging discussions concerning ethical AI deployment, operational accountability, and integrated governance systems within modern digital environments.

References

  1. ORCID. (n.d.). Jessica De Paiva professional profile and research activities.
    orcid.org/0009-0006-2438-2236
  2. Global Innovation Technologist Awards. (n.d.). Award categories and recognition criteria.
    innovationtechnologist.com
  3. De Paiva, J. (2026). Systems governance and operational alignment frameworks.
  4. Known Systems. (2026). Research and development initiatives in operational intelligence.
  5. Elsevier. (n.d.). Scopus author details: Jessica De Paiva, Author ID INSERT. Scopus.
  6. International Journal of Artificial Intelligence Governance. (2025). Operational accountability and AI governance methodologies.

Devender Singh | Robotics and Automation | Young Innovator Award

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Mr. Devender Singh | Robotics and Automation | Young Innovator Award

Uttaranchal University | India

Mr. Devender Singh is an emerging researcher in Internet of Things (IoT), Artificial Intelligence (AI), and smart device engineering, with a strong focus on real-time monitoring systems and intelligent automation. His work integrates embedded systems, wireless communication, and cloud-based analytics to develop scalable, application-oriented solutions across domains such as smart agriculture, healthcare, surveillance, and environmental monitoring. He has contributed to multiple patents and interdisciplinary innovations, emphasizing practical deployment and societal impact. His research also extends to AI-driven diagnostics, edge computing, and blockchain-integrated IoT systems, demonstrating a commitment to advancing next-generation intelligent infrastructure and sustainable technological ecosystems.

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Featured Publications


Secure and smart healthcare system using IoT and deep learning models

– International Conference on Technological Advancements, 2022 | Cited by: 121

Mg-based metal matrix composite in biomedical applications: a review

– Materials Today: Proceedings, 2023 | Cited by: 19 

Li Sun | Computer Science | Young Scientist Award

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Assoc. Prof. Dr. Li Sun | Computer Science | Young Scientist Award

Beijing University of Posts and Telecommunications | China

Assoc. Prof. Dr. Li Sun specializes in data mining, deep learning, and graph-based foundation models, with a strong emphasis on Riemannian geometry in machine learning. His research advances graph neural networks, hyperbolic representation learning, and structural entropy–based data analysis for complex systems. According to Scopus, he has authored 65 publications, with 1,484 citations and an h-index of 17. His work is widely recognized in premier venues such as ICML, NeurIPS, ICLR, KDD, AAAI, and IEEE journals. Dr. Li Sun’s contributions focus on scalable graph learning, social network modeling, and privacy-preserving data mining, significantly impacting modern artificial intelligence and large-scale data analytics.

                            Citation Metrics (Scopus)

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Featured Publications

Pascal Vrignat | Industry 4.0 | Research Excellence Award

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Dr. Pascal Vrignat | Industry 4.0 | Research Excellence Award

Prisme Laboratory at Orleans University | France

Pascal Vrignat is a researcher specializing in operational safety, diagnostics, prognostics, and maintenance strategies for complex systems, with particular expertise in Markovian and stochastic models. His work significantly advances methods for estimating system degradation using survival laws, hidden Markov models, and Remaining Useful Life approaches. He contributes to understanding system obsolescence and managing shortages across the life cycle of industrial systems. His research bridges theory and industrial application, encompassing industrial computing, advanced process control, human–machine interfaces, SCADA systems, IoT, M2M technologies, and digital communication protocols, including OPC-based architectures. He has an extensive record of scientific output, including journal publications, conference papers, book chapters, and a widely used textbook on industrial local networks. His recent works address bearing degradation monitoring and the role of AI in sustainability-focused applications. He is active in research project development, editorial responsibilities, and academic leadership within his institution and research laboratory. His contributions to industry-oriented R&D have earned recognition in international automation competitions. His scholarly impact is reflected in 618 citations (405 since 2020), an h-index of 10 (7 since 2020), and an i10-index of 13 (6 since 2020), underscoring his sustained influence in the fields of reliability engineering, automation, predictive maintenance, and digital industrial systems.

Profiles: Orcid | Google Scholar

Featured Publications

Vrignat, P., Kratz, F., & Avila, M. (2022). Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review. Reliability Engineering & System Safety, 218, 108140. https://doi.org/10.1016/j.ress.2021.108140
Cited by: 152

Pascal, V., Toufik, A., Manuel, A., Florent, D., & Kratz, F. (2019). Improvement indicators for total productive maintenance policy. Control Engineering Practice, 82, 86–96. https://doi.org/10.1016/j.conengprac.2018.09.019
Cited by: 81

Vrignat, P., Avila, M., Duculty, F., & Kratz, F. (2015). Failure event prediction using hidden Markov model approaches. IEEE Transactions on Reliability, 64(3), 1038–1048. https://doi.org/10.1109/TR.2015.2426458
Cited by: 49

Aggab, T., Avila, M., Vrignat, P., & Kratz, F. (2021). Unifying model-based prognosis with learning-based time-series prediction methods: Application to Li-ion battery. IEEE Systems Journal, 15(4), 5245–5254. https://doi.org/10.1109/JSYST.2021.3080125
Cited by: 32

Vrignat, P., Avila, M., Duculty, F., Aupetit, S., Slimane, M., & Kratz, F. (2012). Maintenance policy: Degradation laws versus Hidden Markov Model availability indicator. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 226(2), 137–155. https://doi.org/10.1177/1748006X11406335
Cited by: 21

 

Nicola Chinchella | Active Inference | Best Researcher Award

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Mr. Nicola Chinchella | Active Inference | Best Researcher Award

PhD at University of Bologna | Italy

Nicola Chinchella is a PhD candidate in Cognitive Science and Psychology at the University of Bologna, specializing in cognitive modeling, advanced data analysis, and neuroimaging. His research focuses on understanding moral perception, emotional reactivity, and cognitive processes in digital and therapeutic contexts. He has co-authored several works, including studies on moral desensitization through social media exposure, virtual reality applications in cognitive behavioral therapy, and the perceptual aspects of depersonalization. Nicola previously worked as a Scientific Editor for the Charité NeuroScience Newsletter in Berlin and as a Laboratory Assistant Manager at Technische Universität Berlin, where he honed his skills in research coordination, academic writing, and team collaboration. He earned his master’s degree in Cognitive Science and Psychology from Humboldt Universität zu Berlin and a bachelor’s degree in Philosophy from the University of Florence, combining philosophical inquiry with empirical methods in psychology. His technical expertise covers computational modeling, statistics, machine learning, and deep learning, using tools such as R, Python, Matlab, and PyTorch. Nicola is known for his strong communication and project management skills, along with his commitment to interdisciplinary research and innovation. He is proficient in Italian and English, with working knowledge of German and Spanish. According to Google Scholar, his work has received 13 citations, with an h-index of 2, reflecting his growing influence and contributions to the field of cognitive and psychological sciences.

Profile: Google Scholar

Featured Publications

Ferroni, F., Arcuri, E., Ardizzi, M., Chinchella, N., Gallese, V., & Ciaunica, A. (2025). Lost in time and space? Multisensory processing of peripersonal space and time perception in people with frequent experiences of depersonalisation. Quarterly Journal of Experimental Psychology, 78(6), 1177–1194.
Cited by: 7

Chinchella, N., & Hipólito, I. (2023). Substance addiction: Cure or care? Phenomenology and the Cognitive Sciences, 1–20.
Cited by: 6

Chinchella, N., & White, B. (2025). Enacting recovery: Virtual reality, active inference, and cognitive behavioural therapy for depression. Philosophical Psychology, 1–36.

Ferroni, F., Arcuri, E., Ardizzi, M., Chinchella, N., Gallese, V., & Ciaunica, A. (2023). Lost in time and space? Multisensory processing of peripersonal space and time perception in depersonalisation. PsyArXiv.

Wei Cheng | Intelligent Maintenance | Best Researcher Award

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Prof. Wei Cheng | Intelligent Maintenance | Best Researcher Award

Professor at Xi’an Jiaotong University, China

Prof. Wei Cheng is a prominent figure in the field of mechanical engineering with deep expertise in intelligent systems for nuclear power and smart agricultural technologies. Currently a Full Professor and Doctoral Supervisor at Xi’an Jiaotong University, he has demonstrated an exceptional trajectory in academia, national-level research, and policy advisory roles. His research contributions span nuclear power intelligent decision-making, predictive maintenance, and smart manufacturing, supported by extensive funding and recognized by national media and scientific communities.

Publication Profile 

Scopus

Educational Background 🎓

  • Postdoctoral Research (2012.12 – 2015.09)
    Mechanical Engineering, Xi’an Jiaotong University

  • Ph.D. in Mechanical Engineering (2008.09 – 2012.12)
    Xi’an Jiaotong University

    • Joint Ph.D. at University of Michigan, Ann Arbor (2011.02 – 2012.10)

  • M.Eng. in Mechanical Engineering (2006.09 – 2008.08)
    Xi’an Jiaotong University

  • B.Eng. in Mechanical Engineering (2002.09 – 2006.06)
    Xi’an Jiaotong University

Professional Experience 💼

  • 2022 – Present:

    • Full Professor / Doctoral Supervisor, School of Mechanical Engineering, Xi’an Jiaotong University

    • Deputy Director, CNNC-XJTU Joint Lab for Nuclear Power Intelligent Decision & Predictive Operation

    • Chief Scientist, Smart Agriculture Technology & Equipment Research Center

  • 2018 – 2020:
    Associate Director, Department of Scientific Research, Xi’an Jiaotong University

  • 2017 – 2018:
    Project Manager, High-Tech Department, Ministry of Science and Technology of China

  • 2015 – 2021:
    Associate Professor / Doctoral Supervisor, Xi’an Jiaotong University

Research Interests 🔬

  • Nuclear power intelligent decision-making systems

  • Smart maintenance and predictive operation technology

  • Intelligent equipment for smart agriculture

  • Digital twin and intelligent diagnostics

  • Standardization in intelligent manufacturing

Awards and Honors🏆✨

  • “Wang Kuancheng Young Scholar” distinction

  • Chief author of national strategy documents (e.g., China’s Manufacturing Power Strategy 2035)

  • Research highlighted in People’s Daily and Shaanxi Daily

  • Recognized expert in national standardization committees

Key Research Achievements

  • Led 24 competitive research projects, with over ¥24 million in funding

  • PI of the National S&T Major Project and National Key R&D Program

  • Secured 3 NSFC grants and 17 provincial/ministerial-level projects

  • Developed 1 nuclear power intelligent system and contributed to 5 national/industry standards

  • Published 70+ papers (40+ SCI, 20+ EI indexed)

  • Filed 50+ patents and 11 software copyrights

Conclusion🌟

Prof. Wei Cheng stands out as a highly accomplished and visionary academic in mechanical engineering, with a solid track record in cross-disciplinary innovation, high-impact research, and leadership in national policy planning. His achievements in nuclear power, smart agriculture, and predictive maintenance not only advance scientific frontiers but also align with strategic industrial goals. He is a strong candidate for research excellence awards and continued leadership roles in shaping China’s intelligent manufacturing landscape.

Publications 📚

📄 Article
MelNet: An End-to-End Adaptive Network with Adjustable Frequency for Preprocessing-Free Broadband Acoustic Emission Signals
📚 Information Fusion, 2025
🔗 Full text: Unavailable
📊 Citations: 0

📄 Article
Efficient Belief Rule-Based Network for Planetary Gearbox Wear State Characterization Using Multi-Channel Lubricant Debris Information
📚 Information Fusion, 2025
🔗 Full text: Unavailable
📊 Citations: 0

📄 Article
Gas Turbine Harmonic Detection and Modal Identification Based on Underdetermined Blind Source Separation
📚 Journal of Sound and Vibration, 2025
🔗 Full text: Unavailable
📊 Citations: 0

📄 Article
Class-Imbalanced Pattern Recognition in Pipeline Weld Cracks Damage via Feature Characterization and Sample Enhancement
📚 Measurement – Journal of the International Measurement Confederation, 2025
🔗 Full text: Unavailable
📊 Citations: 0

📄 Article
Microleakage Acoustic Emission Monitoring of Pipeline Weld Cracks Under Complex Noise Interference: A Feasible Framework
📚 Journal of Sound and Vibration, 2025
🔗 Full text: Unavailable
📊 Citations: 1

📚 Review
Diagnostics and Prognostics in Power Plants: A Systematic Review
📝 Journal Name Not Specified, 2025
🔗 Full text: Unavailable
📊 Citations: 1

📄 Article
Macro Guidance–Micro Avoidance Model for On-Site Personnel Emergency Evacuation Strategy in Nuclear Power Plants Under Fear Psychology
📚 Physica A: Statistical Mechanics and Its Applications, 2025
🔗 Full text: Unavailable
📊 Citations: 0

📄 Article
Gradient Consistency Strategy Cooperative Meta-Feature Learning for Mixed Domain Generalized Machine Fault Diagnosis
📚 Knowledge-Based Systems, 2025
🔗 Full text: Unavailable
📊 Citations: 1

📄 Article
EI-ISOA-VMD: Adaptive Denoising and Detrending Method for Nuclear Circulating Water Pump Impeller
📚 Measurement – Journal of the International Measurement Confederation, 2025
🔗 Full text: Unavailable
📊 Citations: 4

📄 Article
A Model-Based Deep Learning Approach to Interpretable Impact Force Localization and Reconstruction
📚 Mechanical Systems and Signal Processing, 2025
🔗 Full text: Unavailable
📊 Citations: 4

Mutiu Shola | Electrical Engineering | Best Researcher Award

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Dr. Mutiu Shola | Electrical Engineering | Best Researcher Award

Kampala International University, Uganda

Dr. Bakare Mutiu Shola is a dedicated academic and researcher in the field of Electrical and Electronics Engineering. He holds a Ph.D. from Kampala International University, Uganda, an M.Eng. from the University of Ilorin, Nigeria, and a B.Eng. from the Federal University of Technology, Minna. His expertise spans renewable energy, smart grids, load forecasting, high-voltage technology, artificial intelligence, and power systems. With a rich background in both industry and academia, Dr. Bakare has contributed significantly through high-impact research publications in top-tier journals and active teaching roles in higher institutions.

Publication Profile 

Scopus

Orcid

Educational Background 🎓

  • Ph.D. in Electrical and Electronics Engineering
    Kampala International University, Uganda (2022 – 2025)

  • Master of Engineering (M.Eng.) in Electrical and Electronics Engineering
    University of Ilorin, Nigeria (2017 – 2021)

  • Bachelor of Engineering (B.Eng.) in Electrical and Computer Engineering
    Federal University of Technology, Minna, Nigeria (2008 – 2014)
    Graduated with Second Class Upper Division

Professional Experience 💼

  • Assistant Lecturer
    Department of Electrical and Electronics Engineering, Kampala International University, Uganda
    (2022 – Present)
    Courses taught include Power Electronics, Power Quality Management, Circuit Theory, and Electrical Installation & Maintenance.

  • Research Assistant
    Advanced Power and Green Energy Research Group (APGER), University of Ilorin, Nigeria
    (2019 – 2022)

  • Physics & Mathematics Tutor
    Government Day Secondary School, Nigeria
    (2018 – 2019)

  • Site Engineer
    Thamar Engineering Company Ltd, Nigeria
    (2015 – 2018)
    Responsibilities included transformer installation, lighting, and generator setup.

Research Interests 🔬

  • Renewable Energy Systems

  • Energy Management

  • Load Forecasting

  • Smart Grid Technologies

  • Electrical Power System Optimization

  • Artificial Intelligence Applications in Power Systems

Awards and Honors🏆✨

  • Multiple Q1 and Q2-ranked journal publications in high-impact engineering journals such as Scientific Reports, Results in Engineering, Energy Reports, and Energy Conversion and Management: X.

  • Active participation in IEEE academic workshops and international conferences such as ICASSP 2020.

Conclusion🌟

Dr. Bakare Mutiu Shola is a rising scholar in electrical engineering with a strong background in both practical engineering and academic research. His consistent record of publications, academic service, and technical expertise in emerging power systems reflects his commitment to driving innovation in sustainable and intelligent energy solutions. With a future-focused mindset, Dr. Bakare is poised to make continued contributions to both academia and the global energy sector.

Publications 📚

  • 🧠 Comparative Evaluation of Different Fuzzy Tuning Rules on Energy Management Systems Cost Savings
    Ibrahim, O., Bakare, M. S., et al.
    📝 Results in Engineering (2025) – Q1 Journal

  • ☀️ Revolutionizing Solar Power: Enhancing Solar Power Efficiency with Hybrid GEP-ANFIS MPPT under Dynamic Weather Conditions
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Scientific Reports (2025) – Q1 Journal

  • ⚙️ Energy Management Controllers: Strategies, Coordination, and Applications
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Energy Informatics 7(1), 57 (2024) – Q2 Journal

  • 🔋 Predictive Energy Control for Grid-Connected Industrial PV-Battery Systems using GEP-ANFIS
    Bakare, M. S., Abdulkarim, A., et al.
    📝 e-Prime – Advances in Electrical Engineering, Electronics and Energy (2024) – Q1 Journal

  • 📈 A Hybrid Long-Term Industrial Electrical Load Forecasting Model Using Optimized ANFIS with Gene Expression Programming
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Energy Reports 11, 5831–5844 (2024) – Q2 Journal

  • 💡 A Comprehensive Overview on Demand Side Energy Management Towards Smart Grids: Challenges, Solutions, and Future Direction
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Energy Informatics 6(1), 1–59 (2023) – Q2 Journal

  • 🔧 Development of Fuzzy Logic-Based Demand-Side Energy Management System for Hybrid Energy Sources
    Ibrahim, O., Bakare, M. S., et al.
    📝 Energy Conversion and Management: X (2023) – Q1 Journal

  • 🔄 Simulation-Based Testing and Performance Investigation of Induction Motor Drives using MATLAB Simulink
    Makinde, K. A., Bakare, M. S., et al.
    📝 SN Applied Sciences 5(3), 73 (2023) – Q2 Journal

  • 🔍 Performance Evaluation of Different Membership Functions in Fuzzy Logic-Based Short-Term Load Forecasting
    Ibrahim, O., Bakare, M. S., et al.
    📝 Pertanika Journal of Science and Technology (2020) – Q3 Journal

 

 

 

Mihir Parekh | Machine Learning | Best Researcher Award

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Mr. Mihir Parekh | Machine Learning | Best Researcher Award

Research Scholar at Nirma University, India

Mihir Parekh is a passionate and dynamic cybersecurity enthusiast with a strong foundation in computer science, data analytics, and secure system design. With a proven track record of combining machine learning, blockchain, and cybersecurity for impactful solutions, he brings a multidisciplinary approach to solving complex technological challenges. Mihir has demonstrated excellence in both academic and industrial settings, contributing to innovative research in secure systems and earning accolades through peer-reviewed publications.

Publication Profile 

Google Scholar

Educational Background 🎓

  • M.Tech in Computer Science and Engineering (Cyber Security)
    Nirma University, Ahmedabad
    08/2022 – 06/2024 | CGPA: 9.21
    Focus: Cybersecurity, Blockchain, Data Analysis, Machine Learning

  • Bachelor of Engineering in Information Technology
    G.H. Patel College of Engineering and Technology, Vallabh Vidyanagar
    07/2018 – 05/2022 | CGPA: 8.22

Professional Experience 💼

  • Data Analyst
    Contrado Imaging India Pvt. Ltd., Ahmedabad
    06/2023 – 10/2023

    • Performed data cleaning and preprocessing using Python.

    • Developed SQL queries to fetch and analyze data.

    • Used Kibana and Elasticsearch for data visualization.

  • Business Process Analyst
    Kevit Technologies, Rajkot
    12/2021 – 07/2022

    • Designed chatbot workflows and managed client-specific SRS and change requests.

    • Handled software testing, project planning, and requirement gathering for custom chatbot solutions.

Research Interests 🔬

  • Cybersecurity and Digital Forensics

  • Blockchain Applications and Cryptographic Protocols

  • Machine Learning and Deep Learning

  • Federated Learning & Secure Data Sharing

  • Anomaly Detection and Fraud Prevention

  • Secure Industrial IoT Systems

Awards and Honors🏆✨

  • 🏆 Published Journal Paper:
    Blockchain Forensics to Prevent Cryptocurrency Scams
    Computers & Electrical Engineering (Impact Factor: 5.5)

  • 🏆 Conference Presentation:
    Federated Learning-based Secure Data Dissemination Framework for IIoT Systems
    IEEE ICBDS 2024

  • 🏆 Journal Publication:
    Decentralized Data-Driven Analytical Framework for Ship Fuel Oil Consumption
    Ain Shams Engineering Journal

  • 🎖️ Infineon Hackathon Finalist – AES-128 Cryptanalysis Challenge

Conclusion🌟

Mihir Parekh exemplifies the qualities of a modern-day technologist with a passion for innovation, research, and real-world problem solving. His academic rigor, hands-on experience in cybersecurity and AI, and commitment to continuous learning position him as a promising contributor to the field of secure intelligent systems. Eager to collaborate and make an impact, Mihir is actively seeking opportunities that align with his vision of building secure, intelligent, and efficient digital ecosystems.

Publications 📚

📘 Parekh, M., Jadav, N. K., Tanwar, S., Pau, G., Alqahtani, F., & Tolba, A. (2025). ANN and blockchain-orchestrated decentralized data-driven analytical framework for ship fuel oil consumption. Applied Ocean Research, 158, 104553.
🔗 https://doi.org/10.xxxxx/aor.2025.104553
📊 Keywords: Artificial Neural Networks, Blockchain, Maritime Fuel Analytics

📕 Parekh, M., Jadav, N. K., Pathak, L., Tanwar, S., & Yamsani, N. (2024). Federated Learning-based Secure Data Dissemination Framework for IIoT Systems Underlying 5G. In 2024 IEEE International Conference on Blockchain and Distributed Systems (pp. xx–xx). IEEE.
📡 Keywords: Federated Learning, 5G, IIoT, Cybersecurity
📍 Conference Paper

📄 Parekh, M. (2024). Decentralized Data-Driven Analytical Framework for Ship Fuel Oil Consumption. Institute of Technology.
🏛️ Institutional publication / Thesis
🌐 Focus: Data Analytics, Maritime Efficiency