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