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)

Veronica Ngunzi | Engineering | Best Researcher Award

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Ms. Veronica Ngunzi | Engineering | Best Researcher Award

Tutorial Fellow at Kenyatta University, Kenya

Veronica Kavila Ngunzi is an experienced professional and educator with over a decade of expertise in renewable energy systems, energy efficiency, and program management. She has an in-depth understanding of Kenya’s power sector, including energy planning, socio-economic data analysis, and the role of development finance in advancing clean energy access. Her work focuses on sustainable energy solutions for critical sectors such as healthcare and agriculture, integrating technical expertise with community empowerment initiatives. She is skilled in energy auditing, hybrid systems design, and capacity-building programs, making significant contributions to the transition to clean energy in Kenya and beyond.

Publication Profile 

Scopus

Orcid

Educational Background 🎓

  • Ph.D. in Renewable Energy Technology (Ongoing) – Kenyatta University, Nairobi, Kenya (2021 – Present)
  • Ph.D. in Agricultural Processing Engineering (Ongoing) – Jomo Kenyatta University of Agriculture and Technology (2020 – Present)
  • M.Sc. in Energy Management – University of Nairobi (2015)
  • B.Sc. in Agricultural Engineering (Double Degree, Second Class Upper Division) – Jomo Kenyatta University of Agriculture and Technology (2018)
  • Postgraduate Diploma in Project Management (Upper Credit) – Kenya Institute of Management (2012)
  • B.Sc. in Biomechanical and Processing Engineering (Second Class Upper Division) – Jomo Kenyatta University of Agriculture and Technology (2009)

Professional Experience 💼

Academic Roles

  • Tutorial Fellow, Kenyatta University, Department of Energy Technology (2020–Present)
    • Teaching and supervising courses in Energy Management, Thermodynamics, and Project Management.
    • Leading research on renewable energy solutions for healthcare and community-focused applications.
    • Guiding students on projects related to Kenya’s energy sector.

Research & Consulting

  • Research Assistant, Free Appropriate Sustainability Technology (FAST) Research Group, Western University Canada (2023–2024)

    • Conducted research on hybrid renewable energy systems for industrial applications.
    • Collaborated with global teams to develop scalable, sustainable clean energy solutions.

  • Energy Consultant (Freelance) – Kenya (2015–2023)

    • Conducted energy audits for industrial and agricultural facilities.
    • Designed hybrid renewable energy systems for critical sectors.
    • Engaged stakeholders to align energy solutions with national planning goals.

Leadership & Advisory Roles

  • Mentor, Women in Energy Empowerment, Accelerating Women’s Empowerment in Energy Program (2024 – Ongoing)

    • Mentoring women in STEM and renewable energy careers.
    • Conducting workshops to promote gender equity in the energy sector.

  • Technical Advisor & Project Team Leader, Milken-Motsepe Prize in Green Energy (2023)

    • Led the implementation of a hybrid solar PV and wind energy system with battery storage.
    • Achieved semifinalist recognition for innovative clean energy solutions.

  • Project Lead, Strathmore Energy Research Centre (SERC) & GIZ (2015–2017)

    • Led a bioenergy analysis project for 30 tea factories, identifying energy-saving opportunities.

  • Trainer, Ministry of Energy Kenya & UNDP (2017)

    • Developed and implemented a solar water heating training manual for Kenyan industries.

  • Researcher, Ministry of Higher Education Science & Technology (2012–2016)

    • Conducted research on biogas resource assessment and purification for household applications.

Research Interests 🔬

  • Renewable energy systems (solar PV, biogas, hybrid systems)
  • Energy efficiency and sector planning
  • Sustainable energy solutions for healthcare and agriculture
  • Socio-economic impacts of clean energy adoption
  • Gender and community empowerment in energy access

Awards and Honors🏆✨

  • Semifinalist, Milken-Motsepe Prize in Green Energy (2023)
  • UNESCO Mentorship Recognition, Accelerating Women’s Empowerment in Energy (2024)
  • Research Grant Recipient, Free Appropriate Sustainability Technology (FAST) Research Group

Conclusion🌟

Veronica Kavila Ngunzi is a dedicated researcher, educator, and renewable energy specialist committed to advancing sustainable energy solutions in Kenya and beyond. With expertise spanning energy policy, hybrid systems, and socio-economic data analysis, she has played a pivotal role in shaping inclusive and impactful energy transitions. Through research, mentorship, and technical innovation, she continues to drive progress in clean energy accessibility and gender equity in the sector.

Publications 📚

📄 Optimization of economics of biomass fuel mix for boilers in tea processing through response surface methodology
📚 Heliyon (2024-12) | 🏛️ Journal article
🔗 DOI: 10.1016/j.heliyon.2024.e40875
✍️ Contributors: Veronica K. Ngunzi, Christopher L. Kanali, Gareth M. Kituu, Erick K. Ronoh

📄 Modeling, simulation and performance evaluation of a PVT system for the Kenyan manufacturing sector
📚 Heliyon (2023-08) | 🏛️ Journal article
🔗 DOI: 10.1016/j.heliyon.2023.e18823
✍️ Contributors: Veronica Ngunzi, Francis Njoka, Robert Kinyua

📄 Analysis of Energy Cost Savings by Substituting Heavy Fuel Oil with Alternative Fuel for a Pozzolana Dryer: Case Study of Bamburi Cement
📚 American Journal of Energy Engineering (2015) | 🏛️ Journal article
🔗 DOI: 10.11648/j.ajee.20150306.13
📖 ISSN: 2329-1648

Ikhlef JEBBOR | Industrial engineering | Excellence in Research

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Dr. Ikhlef JEBBOR | Industrial engineering | Excellence in Research

ibn Tofail University at National School of Applied Sciences, Ibn Tofail University, Kenitra, Morocco

A Ph.D. candidate in Sustainable Optimization of Manufacturing and Supply Chain with extensive experience in both academia and industry. Focuses on lean manufacturing, production optimization, and AI for sustainable development. Currently an Engineering Project Leader at Sumitomo Electric Wiring Systems (SEWS-E), leading process improvements in the automotive industry. Expert in project management, operational research, and continuous improvement strategies such as Six Sigma and Kaizen. Has published numerous peer-reviewed articles and presented at international conferences on sustainability and advanced manufacturing techniques.

Professional Profile

Scopus Profile

Education:

  • Ph.D. in Sustainable Optimization of Manufacturing and Supply Chain (ENSA Kenitra, Ibn Tofail University, 2022 – Current)
  • State Engineer, Industrial Engineering (GI) (FST Errachidia, Moulay Ismail University, 2010 – 2013)
  • Physics & Chemistry Teacher Education Diploma (CPR Mohamed V SAFI, Morocco, 2009 – 2010)
  • Professional University Degree, Renewable Energies and Sustainable Development (ERDD) (Faculty of Sciences -Agadir, Ibn Zohr University, 2007 – 2009)
  • General University Degree, Physical Matter Sciences (SMP) (Faculty of Sciences -Agadir, Ibn Zohr University, 2005 – 2007)
  • BAC, Experimental Science (Salah Eddin Elayyoubi High School, Tinghir, 2005)

Professional Experience:

Sumitomo Electric Wiring Systems (SEWS-E)

  • Engineering Project Leader (Feb 2021 – Current)
  • Senior Project Engineer (Aug 2018 – Jan 2021)
  • Process Engineer (Sep 2015 – Aug 2018)
  • Work Study Engineer (May 2014 – Aug 2015)

Research Interests:

  • Facilities Design and Optimization
  • Lean Manufacturing
  • Production Planning and Scheduling
  • Supply Chain Management
  • Mathematical Modeling and Optimization

Awards and Honors:

  • Outstanding Project Leader Award
    Sumitomo Electric Wiring Systems (SEWS-E), 2022
    Recognized for leading key process improvements in automotive production, significantly enhancing efficiency and innovation.
  • Excellence in Lean Manufacturing Implementation
    Sumitomo Electric Wiring Systems (SEWS-E), 2020
    Awarded for implementing lean manufacturing strategies that resulted in significant cost savings and production efficiency.
  • Best Paper Award
    International Conference on Industrial Engineering and Applications (ICIEA), 2023
    Awarded for presenting the paper on “Improvement of an Assembly Line in the Automotive Industry: A Case Study in Wiring Harness Assembly Line.”
  • Research Excellence Award
    ENSA Kenitra, Ibn Tofail University, 2022
    For contributions to sustainable optimization of manufacturing and supply chain research, particularly in the automotive industry.
  • Innovation Award for Sustainable Practices
    Sustainability and Advanced Manufacturing Techniques Conference, 2023
    Honored for innovative research in applying AI and optimization techniques for sustainable manufacturing practices.

Conclusion:

With an extensive background in industrial engineering, lean manufacturing, and AI applications, I have consistently delivered impactful results in both academia and industry. My experience as an Engineering Project Leader at Sumitomo Electric Wiring Systems (SEWS-E) and my ongoing doctoral research on the sustainable optimization of manufacturing and supply chain systems equip me with a strong foundation for tackling complex industry challenges.

Through my research, publications, and practical experience, I aim to contribute to the development of more efficient, sustainable, and innovative manufacturing processes. I am committed to driving continuous improvement through the application of cutting-edge methodologies such as Six Sigma, Kaizen, and AI-driven optimizations. As I continue to advance in both academia and industry, I strive to shape the future of sustainable industrial engineering and contribute to global efforts for sustainable development.

Publication Top Notes

  1. 📊 Article: Forecasting supply chain disruptions in the textile industry using machine learning: A case study
    • Authors: Jebbor, I., Benmamoun, Z., Hachimi, H.
    • Journal: Ain Shams Engineering Journal, 2024, 15(12), 103116
    • Citations: 1
  2. 🌍 Conference Paper: Optimization of Carbon Emissions in Asphalt Pavement Construction
    • Authors: Benmamoun, Z., Elkhechafi, M., Abdo, A.A., Jebbor, I.
    • Conference: 10th Edition of the International Conference on Optimization and Applications, ICOA 2024 – Proceedings
    • Citations: 0
  3. 🧠 Conference Paper: Comparison of Generative AI Models in Supply Chain Management: Benefits, Applications and Challenges
    • Authors: Khlie, K., Benmamoun, Z., Jebbor, I., Hachimi, H.
    • Conference: 10th Edition of the International Conference on Optimization and Applications, ICOA 2024 – Proceedings
    • Citations: 0
  4. 🤖 Article: Generative AI for enhanced operations and supply chain management
    • Authors: Khlie, K., Benmamoun, Z., Jebbor, I., Serrou, D.
    • Journal: Journal of Infrastructure, Policy and Development, 2024, 8(10), 6637
    • Citations: 1
  5. 🌱 Article: Revolutionizing cleaner production: The role of artificial intelligence in enhancing sustainability across industries
    • Authors: Jebbor, I., Benmamoun, Z., Hachmi, H.
    • Journal: Journal of Infrastructure, Policy and Development, 2024, 8(10), 7455
    • Citations: 1
  6. 📉 Article: Leveraging variational autoencoders and recurrent neural networks for demand forecasting in supply chain management: A case study
    • Authors: Khlie, K., Benmamoun, Z., Fethallah, W., Jebbor, I.
    • Journal: Journal of Infrastructure, Policy and Development, 2024, 8(8), 6639
    • Citations: 5
  7. 📚 Conference Paper: Application of Fuzzy Logic for Evaluating Student Learning Outcomes in E-Learning
    • Authors: Mousse, M.A., Almufti, S.M., García, D.S., Aljarbouh, A., Tsarev, R.
    • Conference: Lecture Notes in Networks and Systems, 2024, 935 LNNS, pp. 175–183
    • Citations: 2
  8. 🚗 Conference Paper: Application of Manufacturing Cycle Efficiency to Increase Production Efficiency: Application in Automotive Industry
    • Authors: Jebbor, I., Benmamoun, Z., Hachimi, H.
    • Conference: 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2024
    • Citations: 3
  9. 🔧 Conference Paper: Process Improvement of Taping for an Assembly Electrical Wiring Harness
    • Authors: Jebbor, I., Raouf, Y., Benmamoun, Z., Hachimi, H.
    • Conference: Lecture Notes in Business Information Processing, 2024, 507 LNBIP, pp. 35–48
    • Citations: 3
  10. ⚙️ Article: Optimizing Manufacturing Cycles to Improve Production: Application in the Traditional Shipyard Industry
  • Authors: Jebbor, I., Benmamoun, Z., Hachimi, H.
  • Journal: Processes, 2023, 11(11), 3136
  • Citations: 10

 

 

 

Rajesh Singh | Engineering | Best Researcher Award

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Prof. Dr. Rajesh Singh | Engineering | Best Researcher Award

Professor at Uttaranchal University, India

Rajesh Singh, Ph.D., is an accomplished academician and researcher with over 20 years of experience in engineering and innovation. He currently serves as the Director of Research & Innovation at Uttaranchal University, as well as the Head of Innovation & Entrepreneurship at Lovely Professional University and Head of the Robotics Research Centre at the University of Petroleum & Energy Studies. Dr. Singh has been instrumental in driving various research and innovation initiatives, with notable accomplishments in the fields of Wireless Sensor Networks, Embedded Systems, Robotics, Artificial Intelligence, Machine Learning, Automation, IoT, and Raspberry Pi.

Publication Profile : 

Scopus

Educational Background 🎓

  • Ph.D. in Electronics Engineering from the University of Petroleum and Energy Studies, Dehradun (2016).
  • M.Tech in Electronics & Communication Engineering from Rajiv Gandhi Technical University (2009).
  • B.E. in Electronics & Communication Engineering from Dr. B.R Ambedkar University, Agra (2002).

Professional Experience 💼

Held various positions in academia, including Associate Professor, Assistant Professor, and Director, with a focus on innovation, research, and entrepreneurship across multiple institutions, including Uttaranchal University, Lovely Professional University, and University of Petroleum & Energy Studies.

Research Interests 🔬

  • Wireless Sensor Networks
  • Embedded Systems
  • Robotics
  • Artificial Intelligence
  • Machine Learning
  • Internet of Things (IoT)
  • Automation

Awards & Recognition

  • Award of Excellence for Research and Innovation in Science, conferred by the State Minister of Uttarakhand, India
  • Recognized for significant contributions to innovation, technology, and academic excellence both nationally and internationally.

Publications 📚

  • Title: Lumpy skin disease virus identification using image-based and deep learning approach
  • Authors: Sharma, S., Joshi, K., Singh, R., Sharma, G., Kumar, G.
  • Conference: Computational Methods in Science and Technology – Proceedings of the 4th International Conference on Computational Methods in Science and Technology, ICCMST 2024
  • Year: 2025
  • Volume: 2
  • Pages: 30–35
  • Title: Leveraging wireless technology and IoT in developing a smart judiciary system with smart dust sensors
  • Authors: Vaish, K., Sharma, M., Kathuria, S., Akram, S.V., Malik, P.K.
  • Book: Intelligent Networks: Techniques, and Applications
  • Year: 2024
  • Pages: 129–151
  • Title: Design of an iterative method for disease prediction in finger millet leaves using graph networks, dyna networks, autoencoders, and recurrent neural networks
  • Authors: Tiwari, S., Gehlot, A., Singh, R., Twala, B., Priyadarshi, N.
  • Journal: Results in Engineering
  • Year: 2024
  • Volume: 24
  • Article ID: 103301
  • Title: Vision-based approach for human motion detection and smart appliance control
  • Authors: Swami, S., Singh, R., Gehlot, A., Kumar, D., Shah, S.K.
  • Journal: IAES International Journal of Robotics and Automation
  • Year: 2024
  • Volume: 13(4)
  • Pages: 445–451
  • Title: Various computational methods for highway health monitoring in terms of detection of black ice: a sustainable approach in Indian context
  • Authors: Kumar, V., Singh, R., Gehlot, A., Priyadarshi, N., Twala, B.
  • Journal: Discover Sustainability
  • Year: 2024
  • Volume: 5(1)
  • Article ID: 245
  • Title: The Image Classification Method for Eddy Current Inspection of Titanium Alloy Plate Based on Parallel Sparse Filtering and Deep Forest
  • Authors: Yidan, Z., Zou, H., Li, Z., Singh, R., Abbas, M.
  • Journal: Journal of Nondestructive Evaluation
  • Year: 2024
  • Volume: 43(4)
  • Article ID: 103
  • Title: Unleashing the power of advanced technologies for revolutionary medical imaging: pioneering the healthcare frontier with artificial intelligence
  • Authors: Chauhan, A.S., Singh, R., Priyadarshi, N., Suthar, S., Swami, S.
  • Journal: Discover Artificial Intelligence
  • Year: 2024
  • Volume: 4(1)
  • Article ID: 58
  • Title: Integrating industry 4.0 technologies for the administration of courts and justice dispensation—a systematic review
  • Authors: Bhatt, H., Bahuguna, R., Swami, S., Priyadarshi, N., Twala, B.
  • Journal: Humanities and Social Sciences Communications
  • Year: 2024
  • Volume: 11(1)
  • Article ID: 1076
  • Title: Use of IoT sensor devices for efficient management of healthcare systems: a review
  • Authors: Gopichand, G., Sarath, T., Dumka, A., Priyadarshi, N., Twala, B.
  • Journal: Discover Internet of Things
  • Year: 2024
  • Volume: 4(1)
  • Article ID: 8
  • Title: Detailed-based dictionary learning for low-light image enhancement using camera response model for industrial applications
  • Authors: Goyal, B., Dogra, A., Jalamneh, A., Singh, R., Jyoti Saikia, M.
  • Journal: Scientific Reports
  • Year: 2024
  • Volume: 14(1)
  • Article ID: 17122

 

 

 

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.