Nawaz Ali | Engineering | Best Researcher Award

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Mr. Nawaz Ali | Engineering | Best Researcher Award

Student at University of Calabria, Sweden

Nawaz Ali is a telecommunications engineer, researcher, and academic with extensive experience in telecommunication networks, database management, and technical education. He has worked in various capacities, including industry roles in GSM networks, IT assistance, and academia, where he has contributed to research and curriculum development. His research interests focus on wireless communications, cognitive radio, vehicular networks, and cloud-based applications.

Publication Profile 

Google Scholar

Educational Background 🎓

  1. Master of Science in Applied Telecommunications and Engineering Management (MASTEAM)

    • Polytechnic University of Catalonia (BarcelonaTech), Spain (2017-2018)

    • Thesis: Performance Comparison of a Platooning Scenario Using EE 802.11p

  2. Master of Science in Mobile and Satellite Communication

    • University of Surrey, UK (2009-2010)

    • Thesis: Performance Evaluation of Spectrum Sensing Techniques in Cognitive Radio

  3. Bachelor of Engineering in Telecommunication Engineering

    • Mehran University of Engineering & Technology, Pakistan (2004-2007)

    • Thesis: Block Error Rate Analysis for WCDMA

  4. Certifications & Training:

    • 5G Implementation: Practices and Case Studies (ITU/Universiti Teknologi Malaysia, 2021)

    • Introduction to Internet of Things (IoT) Certification (Simplilearn, 2021)

    • Wireless Networks Certification Training (CellCom, 2005)

    • Optical Fiber Specialization (NA Telecom Technologies, 2006)

    • CCNA 5.0 (Computer Training and Testing Center, 2006)

    • Graduate Record Examination (GRE) (Score: 329/340)

Professional Experience 💼

  1. Assistant Professor (2014 – Present)

    • Quaid-e-Awam University of Engineering, Science & Technology (Pakistan)

    • Teaching and supervising projects related to telecommunication engineering.

  2. Director Skill Standards & Curricula (BS-19) (2013)

    • National Vocational & Technical Training Commission (Pakistan)

    • Developed national occupational standards and curricula for technical training programs.

  3. Assistant Professor (2011-2013)

    • Quaid-e-Awam University of Engineering, Science & Technology (Pakistan)

    • Delivered courses in telecommunication engineering.

  4. IT Assistant (2009-2010)

    • Shabester-Accountants & Tax Advisors (UK)

    • Managed database security, recovery, and user training.

  5. BSS Engineer (2008-2009)

    • Egyptian Pakistani Telecommunications Services (EPTSC) (Pakistan)

    • Installed and maintained GSM networks and microwave transmission links.

Research Interests 🔬

  • Wireless Communication Networks

  • Cognitive Radio & Spectrum Sensing

  • Internet of Things (IoT)

  • Vehicular Ad-Hoc Networks (VANETs)

  • Machine Learning for Communication Systems

Awards and Honors🏆✨

  • Secured research grants and collaborations in telecommunications.

  • Recognized for contributions to vocational education and training programs.

  • High GRE score (329/340).

Conclusion🌟

Nawaz Ali is an accomplished telecommunications engineer, educator, and researcher with expertise in mobile communication, network security, and IoT applications. His work spans both academia and industry, focusing on wireless networks and emerging technologies. His contributions to curriculum development and technical training have played a crucial role in advancing vocational and higher education in telecommunications.

Publications 📚

📌 Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
📖 A. Lakhan, J. Li, T.M. Groenli, A.H. Sodhro, N.A. Zardari, A.S. Imran, …
📚 Electronics 10(22), 2797 (2021)
📊 Citations: 30

🚗 Adaptive Mobility-Aware and Reliable Routing Protocols for Healthcare Vehicular Network
📖 N.A. Zardari, R. Ngah, O. Hayat, A.H. Sodhro
📚 Mathematical Biosciences and Engineering 19(7), 7156-7177 (2022)
📊 Citations: 18

📡 Spectrum Sensing in ISM Band Using Cognitive Radio
📖 N. Sohu, N.A. Zardari, M.A. Rahu, A.A. Mirani, N.H. Phulpoto
📚 Quaid-E-Awam University Research Journal of Engineering, Science … (2019)
📊 Citations: 11

🖥 Implementation of Huffman Decoder on FPGA
📖 S.A. Dahri, A.F. Chandio, N.A. Zardari
📚 International Journal of Engineering Research & Applications 6(1), 84-88 (2016)
📊 Citations: 2

☁️ Simulators for System Dataset Generation in the Edge-to-Cloud Continuum
📖 N. Ali, G. Aloi, P. Pace, M. Gianfelice, F. Pupo, R. Gravina, G. Fortino
📚 20th International Conference on Distributed Computing in Smart Systems (2024)
📊 Citations: 1

🏭 Edge-Cloud Continuum Driven Industry 4.0
📖 N. Ali, G. Aloi, F. De Rango, C. Savaglio, R. Gravina
📚 Procedia Computer Science 253, 2586-2594 (2025)

🎨 Design and Development of GUI for the Mitigation of Chromatic Dispersion: A New Approach
📖 B. Das, N.A. Zardari, F. Deeba, D.K. Ramnani
📚 Sukkur IBA Journal of Emerging Technologies 5(1), 19-31 (2022)

Wenzhou Yu | Metallurgical Engineering | Best Researcher Award

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Assoc. Prof. Dr. Wenzhou Yu | Metallurgical Engineering | Best Researcher Award

Associate Professor at Chongqing University, China

Wenzhou Yu is an Associate Professor at Chongqing University, specializing in metallurgical engineering with a focus on metal recovery from industrial solid waste. He obtained his Bachelor’s degree from Central South University (2007), followed by a Master’s and PhD from Kunming University of Science and Technology (2010, 2014). He was a visiting scholar at the University of Tokyo in 2022. With over 40 high-level publications, Wenzhou Yu’s research explores vacuum thermal reduction technology to recover valuable metals from solid waste, achieving significant improvements in recovery efficiency and minimizing secondary waste. He is also a member of The Iron and Steel Institute of Japan (ISIJ).

Publication Profile : 

Scopus

Orcid 

Educational Background 🎓

Wenzhou Yu is an Associate Professor at Chongqing University, specializing in metallurgical engineering. He earned his Bachelor’s degree from Central South University (China) in 2007, followed by a Master’s degree (2010) and a PhD (2014) from Kunming University of Science and Technology (China). In 2022, he served as a visiting scholar at the University of Tokyo for a year. Throughout his academic journey, Wenzhou has published over 40 high-level research papers, contributing significantly to his field. He is also a member of The Iron and Steel Institute of Japan (ISIJ) and serves as a guest editor for Crystals.

Professional Experience 💼

Wenzhou Yu has played a pivotal role in advancing research on metal recovery from industrial waste, with numerous collaborations and contributions to cutting-edge technology. His involvement in projects funded by the National Natural Science Foundation of China and industry consultations has further solidified his reputation in the field. His academic efforts are also recognized internationally, with editorial responsibilities and over 40 published papers in renowned journals. 📚💡

Research Interests 🔬

Wenzhou Yu’s primary research focuses on the recovery of valuable metals from industrial solid waste. His work includes developing a vacuum thermal reduction technology to recover metals from materials like red mud, coal fly ash, and polycrystalline silicon kerf loss. His contributions to improving recovery efficiency and minimizing secondary waste have the potential for industrial applications, promoting sustainable practices in metallurgy and waste management. 🌱🔬

Awards and Patents:

Wenzhou Yu holds multiple patents and has been recognized for his pioneering work in the field of waste-to-metal recovery. He is currently nominated for the Best Researcher Award for his innovative contributions. 🏆🔧

Publications 📚

  • 📝 A new strategy for extracting aluminum and iron from red mud via vacuum thermal reduction, alkali-leaching and magnetic separation
    Wen, J., Yu, W., Yuan, H., Xiong, T., Yang, F.
    Journal of Cleaner Production, 2024, 485, 144409

  • ♻️ Eco-Friendly and Efficient Alumina Recovery from Coal Fly Ash by Employing CaO as an Additive During the Vacuum Carbothermic Reduction and Alkali Dissolution
    Rao, Z., Yu, W., Yuan, H., Yang, F., Nyarko-Appiah, J.E.
    Journal of Sustainable Metallurgy, 2024, 10(4), pp. 2216–2226, 131010

  • 🌍 A new strategy for CO2 storage and Al2O3 recovery from blast furnace slag and coal fly ash by employing vacuum reduction and alkali dissolution methods
    Yuan, H., Yu, W., Wen, J., Nyarko-Appiah, J.E., Bai, C.
    Energy, 2024, 308, 132865

  • 🔬 Influencing mechanism of (V, Ti)@(C, N) compounds on the viscosity of hot metal
    Jiang, Z., Yu, W., Song, L., Hu, M., Bai, C.
    Ironmaking and Steelmaking, 2024, 51(5), pp. 397–410

  • 🔧 The Enhancing Mechanism of Na2SO4 on Mullite Decomposition and Alumina Recovery During the Vacuum Carbothermic Reduction of Coal Fly Ash
    Nyarko-Appiah, J.E., Yu, W., Song, L., Wei, P., Chen, H.
    Journal of Sustainable Metallurgy, 2024, 10(2), pp. 810–821

  • ⚙️ Separation of magnesium vapor and carbon monoxide during the vacuum carbothermal reduction of MgO by employing polycrystalline silicon cutting waste as the separation agent
    Yang, F., Yu, W., Wang, W., Jiang, W., Zhu, Y.
    Separation and Purification Technology, 2024, 332, 125798

  • 💡 Oxygen removal and silicon recovery from polycrystalline silicon kerf loss by combining vacuum magnesium thermal reduction and hydrochloric acid leaching
    Yang, F., Yu, W., Wen, J., Jiang, W., Emmanuel, N.-A.J.
    Journal of Environmental Management, 2023, 338, 117829

  • 🌱 An efficient and environmental friendly strategy for alumina extraction and Fe–Si alloys production from coal fly ash by combining vacuum thermal reduction, alkali dissolving, and magnetic separation
    Yu, W., Rao, Z., Yuan, H., Nyarko-Appiah, J.E., Jiang, W.
    Journal of Cleaner Production, 2023, 408, 137129

  • 🔨 Fe-Si alloys production and alumina extraction from coal fly ash via the vacuum thermal reduction and alkaline leaching
    Chen, H., Yu, W., Jiang, Z., Wei, P., Nyarko-Appiah, J.E.
    Fuel Processing Technology, 2023, 244, 107702

  • 💎 Softening–Melting Properties and Slag Evolution of Vanadium Titano-Magnetite Sinter in Hydrogen-Rich Gases
    Xin, R., Zhao, J., Gao, X., Dang, J., Bai, C.
    Crystals, 2023, 13(2), 210

 

 

 

Manas Ranjan Sethi | ECE | Best Researcher Award

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Mr. Manas Ranjan Sethi | ECE | Best Researcher Award

Research Scholar at NIT Silchar, India

Manas Ranjan Sethi is a dedicated academic professional currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar, with a strong focus on machine learning applications in fault diagnosis and energy systems. He holds an M.Tech in Electronics & Telecommunication from BPUT, Odisha and has over 12 years of teaching experience, having worked as an Assistant Professor at Gandhi Institute for Technology (GIFT) and as a Lecturer at Koustuv Institute of Self Domain, Bhubaneswar. His research interests include machine learning, signal processing, and sustainable energy systems, particularly in wind turbine diagnostics and emotion recognition using EEG signals. Manas has contributed to numerous journals, conferences, and book chapters, and he has earned distinctions such as qualifying CBSE-UGC NET and GATE. He is also skilled in technical tools, enjoys singing, and has a passion for reading.

Publication Profile : 

Scopus

 

🎓 Educational Background :

Manas Ranjan Sethi is currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar (since March 2020). He holds an M.Tech in Electronics & Telecommunication (Specialization in Communication Engineering) from BPUT, Odisha (2012), with a CGPA of 8.20. He completed his B.E. in Electronics & Telecommunication from BPUT, Odisha, in 2006, securing a 62.19%. Additionally, he completed his +2 Science and Matriculation from MP Board, Madhya Pradesh.

💼 Professional Experience :

Manas has a rich academic career spanning over 12 years. He served as an Assistant Professor in the Electronics & Communication Engineering Department at Gandhi Institute for Technology (GIFT), Bhubaneswar, from November 2013 to March 2020. Prior to that, he worked as a Lecturer in the Electronics & Telecommunication Engineering Department at Koustuv Institute of Self Domain, Bhubaneswar, from July 2007 to November 2013. He has a strong foundation in teaching and mentoring students in the field of Electronics and Communication Engineering.

📚 Research Interests : 

Manas’s research interests lie in the domains of Machine Learning, Signal Processing, and Fault Diagnosis. His work focuses on vibration signal-based diagnostics and energy extraction using wind turbines. He is passionate about leveraging machine learning techniques for predictive maintenance and condition monitoring. His recent research includes the application of meta-classifiers for diagnosing wind turbine blade faults and exploring emotion recognition through EEG signals.

🏆Achievements & Certifications :

Manas has earned several academic distinctions, including qualifying the CBSE-UGC NET (Electronic Science) in July 2018, and securing GATE scores of 260 (2016) and 218 (2011) in Electronics and Communication. He has also attended and contributed to various seminars, workshops, and short-term courses in fields such as VLSI Design, Microwave Filters, and Adaptive Signal Processing.

📝 Publication Top Notes :

  • Sethi, M. R., Subba, A. B., Faisal, M., Sahoo, S., & Koteswara Raju, D. (2024). Fault diagnosis of wind turbine blades with continuous wavelet transform based deep learning model using vibration signal. Engineering Applications of Artificial Intelligence, 138, 109372.
  • Sethi, M. R., Sahoo, S., Dhanraj, J. A., & Sugumaran, V. (2023). Vibration Signal-Based Diagnosis of Wind Turbine Blade Conditions for Improving Energy Extraction Using Machine Learning Approach. Smart and Sustainable Manufacturing Systems, 7(1), 14–40.
  • Chatterjee, S., Sethi, M. R., & Asad, M. W. A. (2016). Production phase and ultimate pit limit design under commodity price uncertainty. European Journal of Operational Research, 248(2), 658–667.
  • Sethi, M. R., Parhi, S. S., Sahoo, S., Sugumaran, V., & Mohanty, S. R. (2023). Fault Diagnosis of Wind Turbine Blades Through Vibration Signal Using Filtered Cultivation Data: A Comparative Study. Proceedings of the 2023 IEEE Region 10 Symposium, TENSYMP 2023.
  • Kar, P., Hazarika, J., & Sethi, M. R. (2023). A Comparative Study between Supervised and Unsupervised Techniques for Two Class Emotion Recognition using EEG. Proceedings of the 2023 IEEE 8th International Conference for Convergence in Technology, I2CT 2023.
  • Banala, H. S., Sahoo, S., Sethi, M. R., & Sharma, A. K. (2023). Fault Diagnosis in Wind Turbine Blades Using Machine Learning Techniques. In R. Doriya, B. Soni, A. Shukla, & X. Z. Gao (Eds.), Machine Learning, Image Processing, Network Security and Data Sciences (Lecture Notes in Electrical Engineering, Vol. 946), 401–411. Springer, Singapore.
  • Sethi, M. R., Sahoo, S., Kanoongo, S., & Hemasudheer, B. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Rule Classifier. Proceedings of the 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET 2022), 1–6. doi: 10.1109/ICEFEET51821.2022.9848401.
  • Sethi, M. R., Hemasudheer, B., Sahoo, S., & Kanoongo, S. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Vibration Data through META Classifiers. Proceedings of the 2022 4th International Conference on Energy, Power, and Environment (ICEPE 2022), 1–5. doi: 10.1109/ICEPE55035.2022.9798026.

 

 

 

ABLA CHAOUNI BENABDELLAH | Engineering | Best Researcher Award

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Assist. Prof. Dr. ABLA CHAOUNI BENABDELLAH | Engineering | Best Researcher Award

BEST RESEARCHER at International University of rabat, Morocco

Abla Chaouni Benabdellah is an Assistant Professor of Supply Chain Management and Information Systems at Rabat Business School, International University of Rabat (UIR). She holds a Ph.D. in Industrial Engineering from Moulay Ismail University, Meknes, and a Master’s in Mathematics and Statistics from Mohamed V University, Rabat. With extensive teaching experience across various institutions including EUROMED University and Private University of Fez, she specializes in project management, risk management, and supply chain strategies.

Publication Profile : 

Scopus

🎓 Educational Background :

  • Ph.D. in Industrial Engineering (2016 – 2019), Moulay Ismail University, ENSAM, Meknes
  • Master in Mathematics and Statistics (2012 – 2014), Mohamed V University, Rabat
  • Bachelor in Applied Mathematics (2009 – 2012), Moulay Ismail University, Faculty of Science, Meknes
  • Baccalaureate in Mathematics (2008 – 2009), Moulay Ismail College, Meknes

💼 Professional Experience :

  • Assistant Professor of Supply Chain Management & Information Systems (Since 2022), Rabat Business School, International University of Rabat (UIR), Rabat
  • Human Resources Consultant (2021), Expert Human Capital (EHC), Casablanca
  • Professor (2020), School of Digital Engineering and Artificial Intelligence (EIDIA), EUROMED University, Fez
  • Professor (2020), Private University of Fez, Fez
  • Seminar Presenter (2020), “Holonic Multi-Agent Systems for Decision Making -Application to Knowledge Management-“, ENSAM, Meknès
  • Doctoral Course Instructor (2019), Statistical Modeling with R Software, ENSAM-Meknès
  • Coordinator (2018), Artificial Intelligence and Data Science Master, SUPMTI, Meknes
  • Professor (2016), Higher School of Management, Telecommunications and IT (SUPMTI), Meknes

📚 Research Interests : 

  • Supply Chain Management
  • Industrial Engineering
  • Digital Supply Chains
  • Blockchain Technology
  • Artificial Intelligence and Data Science
  • Statistical Modeling

📝 Publication Top Notes :

  1. Blockchain Technology in Supply Chains: Discusses blockchain’s role in enhancing digital supply chains and evaluates implementation barriers.
  2. Big Data Analytics in Supplier Selection: Explores a multi-agent system for supplier selection using big data analytics.
  3. Smart Product Design and Digital Agility: Develops an ontology for managing agility in digital product design.
  4. Blockchain and Smart Contracts in Automotive Supply Chains: Examines how blockchain and smart contracts can optimize automotive supply chains.
  5. Medical Waste Management Optimization: A multi-agent system approach for improving medical waste management.
  6. Sustainable Supplier Selection in Circular Economy: Uses an ontology-based model to improve supplier selection under a circular economy framework.
  7. Environmental Supply Chain Risk Management: Proposes a data mining framework for managing supply chain risks in Industry 4.0.
  8. Lean and Green Practices in Supply Chains: Integrates lean and green practices to enhance sustainable and digital supply chain performance.
  9. Digital Technologies and Circular Economy: Investigates how digital technologies support sustainable supply chain management post-COVID-19.
  10. Circular Digital Supply Chain Design: Focuses on sustainable design practices within digital supply chains.
  11. Supplier Selection Ontology: Develops an ontology for effective supplier selection in digital supply chains.
  12. Intersection of Design for X and Business Strategies: Analyzes the integration of design techniques and business strategies for product lifecycle management.
  13. Knowledge Discovery for Sustainability: Discusses methods for enhancing sustainability through knowledge discovery in design processes.