Zhiqi Wu | Engineering | Best Researcher Award

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Ms. Zhiqi Wu | Engineering | Best Researcher Award

Student at Anhui University of Science and Technology | China

Zhiqi Wu is a Master’s student in Electrical Engineering at Anhui University of Science and Technology, specializing in computer vision applications for intelligent coal gangue detection. His research emphasizes developing lightweight, high-performance models that improve automation and efficiency in mining operations. Zhiqi proposed a novel model integrating multispectral imaging with knowledge distillation, achieving a precision increase of up to 6% while reducing model size by 21.8%, enabling deployment on mobile and edge devices for real-time sorting. This approach advances intelligent coal industry practices by combining computational efficiency with practical industrial applicability. Zhiqi’s work exemplifies the translation of advanced AI techniques into actionable solutions for industrial automation, with a focus on scalability, accuracy, and sustainability. His contributions are recognized in the research community, with 1 citation for his published work, highlighting its impact and relevance. To date, he has contributed to 4 documents in his research portfolio, reflecting his engagement in ongoing innovation and knowledge dissemination. While his h-index currently stands at 1, it represents a promising start in a career dedicated to applied AI in mining technologies. Zhiqi continues to explore methods for optimizing computer vision systems in industrial contexts, advancing automation, operational safety, and resource efficiency. His work bridges theoretical research and practical deployment, positioning him as an emerging researcher making measurable contributions to intelligent mining technologies.

Profile: Scopus

Featured Publications

Yan, P. (2025). Transformer fault diagnosis based on LIF technology and COA-GRU algorithm. Engineering Research Express, 7(2), 25409.

Ashish Ranjan Dash | Engineering | Best Researcher Award

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Dr. Ashish Ranjan Dash | Engineering | Best Researcher Award

Associate Professor at Centurion University of Technology and Management | India

Dr. Ashish Ranjan Dash is a highly accomplished academic and researcher in the field of electrical engineering, specializing in power electronics, multilevel inverters, and power quality improvement. With a proven track record in research, teaching, and project leadership, he has significantly contributed to advancements in smart infrastructure, renewable energy systems, and IoT-enabled agricultural automation. He has also played a pivotal role in supervising doctoral students, developing innovative solutions for industrial applications, and leading consultancy projects for technology-driven agriculture and smart systems.

Publication Profile 

Scopus

Google Scholar

Educational Background 

Dr. Dash earned his Ph.D. in Power Electronics from the National Institute of Technology (NIT) Rourkela, focusing on cascaded multilevel inverter-based shunt active filters under varying grid voltage conditions. He also holds an M.Tech. in Power Control and Drives from NIT Rourkela, where his dissertation explored control strategies for grid-connected inverter systems during fault conditions. His academic foundation is further strengthened by a B.Tech. in Electrical Engineering and a Diploma in Electrical Engineering, complemented by a strong record of academic excellence throughout his studies.

Professional Experience 

With over a decade of academic and research experience, Dr. Dash serves as an Associate Professor at Centurion University of Technology and Management, Odisha. His prior roles include research and academic positions in engineering colleges and at the Council of Scientific and Industrial Research. He has held key administrative positions such as Dean and Associate Dean of the School of Engineering and CEO of the Smart Infrastructure Research Center, where he has led interdisciplinary projects integrating IoT, automation, and renewable energy systems.

Research Interests 

His research focuses on power electronics, multilevel inverter design, power quality enhancement, electric vehicle charging infrastructure, smart grid systems, and IoT-enabled automation. He also works extensively on agricultural automation, including polyhouse automation, speed breeding chambers, and plant phenotyping systems. Emerging interests include machine learning applications for plant disease detection, robotics, and smart farming technologies.

Awards and Honors 

Dr. Dash has received multiple accolades, including the Distinguished Achiever Award at the Provost Research Awards and recognition as a session chair at IEEE international conferences. He is the founder of a technology-driven startup and actively engages in professional communities such as the IEEE Power Electronics Society, IEEE Industry Applications Society, and IEEE SIGHT.

Research Skills 

He possesses strong expertise in the design, modeling, and implementation of cascaded multilevel inverters, power quality control algorithms, and renewable energy integration. His skills extend to IoT-based system design, automation technologies, electric vehicle charging systems, and cloud-based agricultural monitoring. He is also an experienced reviewer for several high-impact international journals in power electronics and smart grid applications.

Publications 

A unified control of grid-interactive off-board EV battery charger with improved power quality

Citations: 49

Year: 2022

Reactive power compensation using vehicle-to-grid enabled bidirectional off-board EV battery charger

Citations: 34

Year: 2021

Adaptive LMBP training‐based icosϕ control technique for DSTATCOM

Citations: 33

Year: 2020

Analysis of PI and PR controllers for distributed power generation system under unbalanced grid faults

Citations: 33

Year: 2011

Design and implementation of a cascaded transformer coupled multilevel inverter‐based shunt active filter under different grid voltage conditions

Citations: 24

Year: 2019

Conclusion 

Dr. Ashish Ranjan Dash is a forward-looking researcher and educator whose work bridges advanced power electronics with practical applications in smart infrastructure and agricultural automation. His multidisciplinary expertise, leadership in funded projects, and dedication to mentoring the next generation of engineers make him a valuable contributor to both academia and industry. His continued research promises innovative advancements in electric mobility, renewable energy integration, and intelligent automation systems.

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)

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