Ganiyat Salawu | Advanced Technology | Research Excellence Award

Published on by Applied Scientist

Research Excellence Award

Ganiyat Salawu
University of KwaZulu-Natal, South Africa
Ganiyat Salawu
Affiliation University of KwaZulu-Natal
Country South Africa
Scopus ID 57215833868
Documents 9
Citations 20
h-index 3
Subject Area Advanced Technology
Event Applied Scientist Awards
ORCID 0000-0002-7436-6721

Ganiyat Salawu is a researcher and academic affiliated with the University of KwaZulu-Natal, South Africa, with professional expertise in advanced manufacturing systems, disruptive technologies, mechatronics, robotics, renewable energy systems, and intelligent automation. Her scholarly work integrates interdisciplinary approaches in mechanical engineering and advanced technological innovation, particularly in the optimization of manufacturing environments through artificial intelligence, robotics, Internet of Things integration, and sustainable engineering methodologies.[1] Her research contributions have focused on modeling, simulation, optimization, energy systems, and manufacturing productivity enhancement, positioning her work within contemporary discussions surrounding Industry 4.0 and Industry 5.0 technologies.[2]

Abstract

The Research Excellence Award article documents the academic profile, scientific contributions, and professional achievements of Ganiyat Salawu in the field of advanced technology and engineering systems. Her scholarly activities encompass disruptive manufacturing technologies, artificial intelligence integration, robotics, intelligent automation, and renewable energy engineering. Salawu’s research has contributed to the advancement of manufacturing optimization models, smart systems development, and industrial productivity enhancement through data-driven methodologies and intelligent engineering frameworks.[2] Her publication record demonstrates engagement with interdisciplinary engineering research and international scientific collaboration across manufacturing innovation, sustainable systems, and automation technologies.[3]

Keywords

Advanced Manufacturing, Mechatronics, Robotics, Artificial Intelligence, Industry 5.0, Disruptive Technology, Internet of Things, Renewable Energy Systems, Intelligent Automation, Engineering Optimization

Introduction

The rapid transformation of industrial systems through intelligent automation and disruptive technologies has created increased demand for engineering researchers capable of integrating multidisciplinary innovation into manufacturing and technological development. Ganiyat Salawu’s academic work reflects this evolving landscape through research that combines mechanical engineering principles with computational intelligence, robotics, automation systems, and smart manufacturing processes.[3]

Her research trajectory includes contributions to advanced manufacturing environments, optimization of industrial systems, artificial intelligence integration into mechatronic systems, and sustainability-oriented engineering applications.[4]

Research Profile

Ganiyat Salawu obtained a Ph.D. in Mechanical Engineering with specialization in Mechatronics and Robotics from the University of KwaZulu-Natal, South Africa. Her academic background also includes postgraduate and undergraduate engineering qualifications with extensive experience in manufacturing systems, automation, and mechanical engineering applications.[1]

Her professional appointments include service as a Post-Doctoral Fellow at the University of KwaZulu-Natal and Senior Lecturer at The Federal Polytechnic Offa, Nigeria. In these capacities, she has participated in engineering education, project supervision, entrepreneurship development, and industrial innovation activities.[5]

  • Research focus on intelligent manufacturing systems and industrial automation.
  • Investigation of robotics and artificial intelligence integration in manufacturing environments.
  • Application of modeling and simulation techniques for engineering optimization.
  • Research contributions related to renewable energy systems and sustainable engineering.

Research Contributions

Ganiyat Salawu’s research contributions address contemporary engineering challenges involving automation, intelligent manufacturing, robotics optimization, and energy systems integration. Her studies on disruptive technologies and Industry 5.0 frameworks investigate the integration of artificial intelligence and quantum computing into advanced manufacturing processes.[2]

Additional contributions include work on conveyor system optimization, robotic manipulator performance enhancement, Internet of Things-enabled environmental monitoring systems, adaptive neuro-fuzzy inference systems, and photovoltaic energy management applications.[4] These studies collectively contribute toward manufacturing productivity enhancement, system efficiency improvement, and sustainable industrial engineering practices.

  • Research on quantum computing applications in Industry 5.0 manufacturing environments.
  • Integration of artificial intelligence into mechatronic and autonomous systems.
  • Optimization modeling for manufacturing productivity and conveyor systems.
  • Development of IoT-based weather monitoring and smart automation systems.
  • Studies on renewable energy technologies and hybrid energy storage systems.

Publications

Selected publications authored or co-authored by Ganiyat Salawu include peer-reviewed journal articles and conference proceedings related to engineering innovation, disruptive technologies, automation systems, and manufacturing optimization.[3]

  1. Improving the Efficiency of a Conveyor System in an Automated Manufacturing Environment Using a Model-Based Approach. International Journal of Mechanical Engineering and Robotics Research, 2023.
  2. Modeling and Simulation of a Conveyor Belt System for Optimal Productivity. International Journal of Mechanical Engineering and Technology, 2020.

Research Impact

Ganiyat Salawu’s academic work is reflected through contributions to emerging engineering technologies and intelligent manufacturing systems. Her studies support industrial modernization strategies by integrating artificial intelligence, robotics, optimization techniques, and sustainable engineering methodologies into advanced manufacturing processes.[4]

Her publication profile includes research indexed within recognized scientific databases and participation in international conferences focused on engineering systems, automation technologies, and manufacturing innovation.[1] The interdisciplinary nature of her research contributes to broader discussions concerning Industry 4.0 and Industry 5.0 transformation initiatives in engineering and industrial sectors.

Award Suitability

Ganiyat Salawu’s research profile demonstrates alignment with the objectives of the Research Excellence Award through sustained contributions to advanced engineering systems, disruptive technologies, and intelligent manufacturing research. Her interdisciplinary work in automation, robotics, optimization modeling, and artificial intelligence applications illustrates active engagement with contemporary engineering innovation challenges.[5]

Her academic record also reflects involvement in research supervision, engineering education, conference dissemination, and industrially relevant technological development. The combination of scholarly publications, conference participation, applied engineering projects, and recognition for research excellence supports her suitability for professional and academic recognition within advanced technology domains.[6]

Conclusion

Ganiyat Salawu illustrate continued engagement with technological innovation in manufacturing systems, intelligent automation, and sustainable engineering. Her interdisciplinary research portfolio demonstrates relevance to contemporary developments in Industry 5.0, smart manufacturing, robotics, and artificial intelligence applications. Through scholarly publications, conference presentations, supervised projects, and engineering education activities, Salawu has contributed to advancing knowledge within advanced technology and engineering research environments.[2]

References

  1. Elsevier. (n.d.). Scopus author details: Ganiyat Salawu, Author ID 57215833868. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57215833868
  2. Salawu, G. A. (2026). Integrating artificial intelligence into mechatronics: A comprehensive study on system performance, autonomy, and manufacturing efficiency. Technologies, 14(3), 143.
    https://doi.org/10.3390/technologies14030143
  3. Salawu, G. A. (2025). Exploring the integration of IoT and robotics in manufacturing: Scoping review of disruptive technology. Technologies, 13(12), 566.
    https://doi.org/10.3390/technologies13120566
  4. Salawu, G. A., & Bright, G. (2025). Optimization control design and simulation of furnace-fired boiler exit pressure: Leveraging disruptive technology. IAES International Journal of Artificial Intelligence.
    https://doi.org/10.11591/ijai.v14.i4.pp2979-2990
  5. Salawu Ganiyat, Iyanda Rukayat Afolake. (2020). Design of a portable solar powered solar incubator.
    https://www.researchgate.net
  6. Salawu, Bright, G. (2026). Quantum Computing as a Disruptive Technology: Implications for Advanced Manufacturing and Industry 5.0.
    https://www.mdpi.com/2076-3417/16/10/4856

Nidhi Chandrakar | Emerging Technologies | Applied Scientist Award

Published on by Applied Scientist

Ms. Nidhi Chandrakar | Emerging Technologies | Applied Scientist Award

Nidhi Chandrakar at NIT Trichy | India

Nidhi Chandrakar is a passionate and highly motivated researcher with expertise in power electronics, converter topologies, and advanced control strategies. Her work focuses on the development of high-efficiency energy conversion systems and smart power solutions for various applications, including electric vehicles, renewable energy integration, and intelligent energy storage systems. She has an exceptional ability to combine theoretical knowledge with practical implementation, demonstrated through her extensive experience in hardware design, circuit simulation, and system optimization. Nidhi has contributed to multiple high-impact research projects, including the design of Dual Active Bridge (DAB) converters and the implementation of innovative modulation strategies for improving performance and efficiency. She has published her research findings in reputed international journals and has presented her work at several prestigious conferences. In addition, she has co-authored book chapters on emerging electric vehicle technologies and hybrid energy systems, reflecting her versatility and technical proficiency. Nidhi’s strong analytical skills, collaborative mindset, and innovative approach position her as a dedicated researcher committed to driving advancements in sustainable power systems and next-generation energy solutions.

Professional Profile

Scopus | ORCID

Education

Nidhi Chandrakar has built a solid academic foundation in electrical engineering, power systems, and energy technologies. She is currently pursuing advanced research focused on power electronics and control strategies, particularly the optimization of high-performance DC-DC converters. Her academic journey has been defined by her deep interest in converter topologies, modulation techniques, and energy-efficient system designs. Throughout her studies, she has explored hardware implementation, simulation modeling, and algorithm development to bridge the gap between theory and real-world applications. She has consistently demonstrated strong academic performance, excelling in both analytical and experimental aspects of electrical engineering. Nidhi’s research training has provided her with practical exposure to modern control systems, FPGA programming, and microcontroller-based hardware development. Her academic experiences also include collaborative projects, interdisciplinary research, and active participation in workshops and seminars, which have strengthened her understanding of emerging technologies. By integrating advanced concepts of power electronics, renewable energy systems, and intelligent control, Nidhi has developed a holistic perspective on modern engineering challenges. Her educational background has shaped her into a skilled researcher with a passion for exploring innovative solutions in sustainable energy systems and cutting-edge power conversion technologies.

Professional Experience

Nidhi Chandrakar has gained valuable professional experience through diverse roles in research, development, and teaching. She is currently contributing as a Senior R&D Engineer, where she works on the design and development of electronic load systems used for testing power supplies, batteries, and advanced energy systems. Her role involves hardware design, circuit optimization, testing, and troubleshooting, enabling her to develop efficient and reliable systems. Previously, she worked as an R&D Engineer, where she focused on Boost PFC circuits, LLC resonant converters, and Dual Active Bridge (DAB) converters. During this period, she played a key role in developing gate driver circuits, isolated regulated power supplies, and advanced PCB layouts. In addition to her industrial contributions, Nidhi has served as a Teaching Assistant, supporting academic courses in Digital System Design and HDL programming, and has also worked as a Residential Student Counselor, mentoring students and assisting in administrative responsibilities. Through these experiences, she has developed strong problem-solving abilities and gained practical exposure to power system optimization, simulation tools, and microcontroller-based hardware development. Her professional journey demonstrates a balanced expertise in both academic research and industry-driven innovation.

Research Interests

Nidhi Chandrakar’s research interests focus on power electronics, energy conversion, and intelligent control strategies. She is particularly interested in the development of high-efficiency DC-DC converters, with a specialization in Dual Active Bridge (DAB) topologies and their applications in electric vehicle systems. Her current work involves optimizing converter performance through innovative approaches to current stress reduction and circulating current minimization, ensuring improved system reliability and energy efficiency. Nidhi is also passionate about renewable energy integration, smart grids, and energy storage technologies, with a strong focus on improving the interaction between distributed energy resources and power electronics systems. She has explored pulse-width modulation (PWM) and phase-shift modulation (PSM) techniques to enhance converter efficiency, supported by both simulation and experimental validation. Beyond power converters, her interests extend to real-time control systems, hardware-in-the-loop (HIL) testing, and embedded systems development for sustainable energy applications. Nidhi seeks to contribute to innovative research addressing global energy challenges by designing scalable, cost-effective, and environmentally friendly solutions. Her long-term goal is to advance the field of power electronics by bridging the gap between theoretical research and practical implementation in smart energy systems.

Research Skills

Nidhi Chandrakar possesses strong technical, analytical, and experimental skills that complement her research expertise in power electronics and control systems. She is proficient in Verilog coding and FPGA-based digital system design, enabling her to implement high-performance hardware prototypes. She has extensive experience working with Texas Instruments C2000 microcontrollers, particularly the F28379D series, for real-time control applications and advanced converter optimization. Nidhi is skilled in using MATLAB and PLECS simulation software for system modeling, analysis, and performance evaluation of power electronics systems. Her technical capabilities also include gate driver circuit design, isolated regulated power supply development, and PCB layout optimization, allowing her to translate complex concepts into functional designs. Additionally, she is proficient in programming languages such as C, C++, and Python, which she uses for developing algorithms, simulations, and embedded control solutions. Nidhi has hands-on expertise in soldering, hardware testing, troubleshooting, and validating control strategies for experimental setups. She also demonstrates strong abilities in technical documentation, academic writing, and presenting research findings at international conferences. Her diverse skill set empowers her to conduct impactful research and develop innovative, high-efficiency power solutions for emerging technologies.

Awards and Honors

Nidhi Chandrakar has been recognized for her research contributions, academic excellence, and technical expertise in the field of power electronics. She has co-authored several highly cited publications in leading international journals, where her research on current stress mitigation and circulating current reduction strategies in Dual Active Bridge converters has been well-appreciated. Nidhi has also presented her work at prestigious international conferences, where her innovative approaches to converter control and optimization have received positive recognition from the scientific community. Her contributions to book chapters published by Springer and Academic Press highlight her growing influence in the areas of electric vehicle technologies, hybrid energy systems, and renewable energy applications. In addition to her academic achievements, she has consistently maintained an outstanding record of performance throughout her studies, earning appreciation for her dedication, hard work, and technical innovation. Nidhi’s research outputs demonstrate her ability to produce impactful solutions to real-world engineering challenges. These honors reflect her strong commitment to advancing sustainable energy technologies and her potential to contribute significantly to the development of next-generation power electronics systems.

Publications Top Notes

Title: Efficient Control Strategy for Circulating Current Minimization in Dual Active Bridge Applications
Year: 2025

Conclusion

In conclusion, Nidhi Chandrakar is a highly driven researcher, engineer, and innovator with a strong focus on power electronics, converter design, and sustainable energy systems. Her academic background, professional experience, and hands-on expertise in hardware design, control strategies, and energy optimization have shaped her into a well-rounded contributor to both research and industry. Through her publications, conference presentations, and collaborative projects, she has demonstrated a deep understanding of converter technologies and renewable energy integration, positioning her as an emerging expert in her field. Nidhi strives to bridge the gap between theoretical research and practical implementation, aiming to develop efficient, reliable, and cost-effective power solutions that address global energy challenges. Her commitment to innovation, sustainability, and knowledge sharing underscores her long-term vision of contributing to advancements in electric vehicle systems, renewable power integration, and intelligent energy storage technologies. With her passion, determination, and strong technical foundation, Nidhi is well-prepared to make a meaningful impact in the evolving landscape of modern power electronics.

 

Sara Migliorini | Innovation Impact | Best Researcher Award

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Dr. Sara Migliorini | Innovation Impact | Best Researcher Award

Assistant Professor From University of Verona, Italy

Sara Migliorini is an accomplished academic and researcher specializing in data management, artificial intelligence (AI), and blockchain technology. Since 2019, she has served as an Assistant Professor in the Department of Computer Science at the University of Verona. Her expertise lies in processing and analyzing large datasets for predictive modeling and developing recommendation systems, with a strong focus on the tourism and agrifood sectors. Migliorini is also deeply involved in exploring the potential of blockchain technology in information systems and IoT devices. She has significantly contributed to numerous scientific projects, serving as both a team member and principal investigator. Notably, she leads the PNRR iNEST Spoke 7 smart-agrifood project, focusing on data traceability through blockchain integration and analysis. Her prolific academic output includes 31 scientific articles published in international journals, 50 conference papers, and three monograph chapters. Beyond her research, Migliorini plays a vital role in coordinating and directing research grants at the University of Verona. Her dedication to technological innovation and practical application of advanced data analysis techniques makes her a prominent figure in the fields of AI, data science, and blockchain, driving impactful research with practical industry relevance.

Professional Profiles

 Education 

Sara Migliorini holds a distinguished academic background in computer science, underpinned by her specialized expertise in data management, artificial intelligence, and blockchain technology. She completed her Ph.D. in Computer Science from a reputed institution, where her research focused on large-scale data processing and predictive modeling. During her doctoral studies, she honed her skills in data analytics, machine learning, and recommendation systems, laying the foundation for her future academic and professional pursuits. Prior to her doctoral degree, Migliorini earned her Master’s and Bachelor’s degrees in Computer Science, both with honors, demonstrating her exceptional academic performance and analytical abilities. Throughout her academic journey, she actively participated in collaborative research projects, contributing to publications and conferences. Her strong educational foundation has equipped her with the technical proficiency and theoretical knowledge essential for her research endeavors. Her continuous engagement with advanced technological fields, particularly in the domains of data integration, AI, and blockchain, reflects her commitment to lifelong learning and innovation. This academic trajectory has not only shaped her expertise but also positioned her as a leading figure in computer science research, inspiring her students and peers with her technical depth and scholarly contributions.

 Professional Experience 

Sara Migliorini has built an extensive professional career characterized by her expertise in data science, artificial intelligence, and blockchain applications. Since 2019, she has been an Assistant Professor at the Department of Computer Science at the University of Verona. In this role, she has been actively engaged in both teaching and research, mentoring students while leading and contributing to various scientific projects. Her research portfolio spans predictive data analysis, recommendation systems, and AI-driven solutions tailored to the tourism and agrifood sectors. Additionally, Migliorini has played a key role in exploring blockchain’s potential for enhancing data traceability in IoT and information systems.

Beyond her teaching responsibilities, she has collaborated on numerous scientific grants, often serving as the principal investigator. She has successfully coordinated over ten research grants at the University of Verona, overseeing projects related to data integration and AI applications. Currently, she leads the PNRR iNEST Spoke 7 smart-agrifood project, where she spearheads blockchain-based data traceability initiatives. Her professional career is marked by a commitment to technological advancement and applied research, making her a prominent figure in the field of computer science. Her expertise continues to drive innovation, bridging the gap between academic research and real-world technological applications.

 Research Interest 

Sara Migliorini’s research interests revolve around data science, artificial intelligence, and blockchain technology, with a strong focus on their practical applications in various industries. Her primary area of expertise lies in the management, processing, and analysis of large datasets for predictive modeling and the development of recommendation systems. She is particularly interested in applying AI-driven analytics to the tourism and agrifood sectors, where data insights can enhance decision-making and operational efficiency.

Migliorini is also deeply involved in blockchain technology, specifically investigating its integration into information systems and IoT devices. Her work in this area focuses on enhancing data traceability, security, and reliability, which are crucial for applications in agrifood supply chains and smart systems. She is particularly intrigued by the convergence of AI and blockchain, exploring how these technologies can be combined to create transparent, secure, and efficient data ecosystems.

Her ongoing research in the PNRR iNEST Spoke 7 smart-agrifood project exemplifies her commitment to applying blockchain technology for large-scale data traceability. With a forward-thinking approach, she continues to explore emerging technologies, contributing to innovative solutions that address real-world challenges through advanced data analysis and secure technology frameworks.

 Research Skills 

Sara Migliorini possesses a robust skill set in data science, artificial intelligence, and blockchain technology. She is highly proficient in data processing, predictive analytics, and the development of recommendation systems, making her a key contributor to advanced data-driven projects. Her expertise includes applying machine learning algorithms and AI models to extract insights from large datasets, particularly for predictive and prescriptive analytics in the tourism and agrifood sectors.

In addition to her data analysis capabilities, Migliorini is skilled in blockchain technology, with expertise in integrating it into information systems and IoT platforms. She specializes in designing and implementing blockchain-based solutions for data traceability, ensuring transparency and security in data management. Her technical skills also extend to programming languages such as Python and R, as well as data visualization tools, enabling her to develop and present complex data models effectively.

Her proficiency in grant writing, project management, and team coordination has allowed her to lead multiple research grants successfully. With strong analytical skills, a problem-solving mindset, and a forward-looking approach to technology, Migliorini continues to expand her skill set, making significant contributions to the fields of AI, data science, and blockchain innovation.

 Awards and Honors

Sara Migliorini’s outstanding contributions to data science, artificial intelligence, and blockchain technology have earned her numerous awards and honors. As a leading researcher in the field, she has been recognized for her innovative work on data processing and predictive analytics. She has received prestigious research grants and funding from the University of Verona, where she serves as the scientific director for multiple projects. Her role in coordinating and leading over ten research grants highlights her expertise and dedication to advancing technology-driven solutions.

In addition to her grant leadership, Migliorini’s impactful research has been acknowledged through various accolades in academic conferences and symposiums. Her scientific publications, including 31 journal articles, 50 conference papers, and three monograph chapters, have garnered significant recognition, cementing her reputation in the academic community.

Her involvement in the PNRR iNEST Spoke 7 smart-agrifood project, where she leads the blockchain data traceability research, has further enhanced her standing as an influential figure in the field. Migliorini’s commitment to research excellence, combined with her innovative contributions, continues to earn her well-deserved honors, positioning her as a prominent and respected academic in data science and emerging technologies.

Conclusion 

Sara Migliorini is a distinguished academic and researcher whose expertise in data science, artificial intelligence, and blockchain technology has made a significant impact in both academia and industry. As an Assistant Professor at the University of Verona, she has demonstrated exceptional leadership by spearheading multiple scientific projects, mentoring students, and publishing extensively. Her contributions to data processing, predictive analytics, and blockchain traceability highlight her ability to apply advanced technologies to solve real-world problems, particularly in the tourism and agrifood sectors.

Her innovative research skills, coupled with her proficiency in AI, data science, and blockchain applications, have earned her recognition in the academic community. Through her work on the PNRR iNEST Spoke 7 smart-agrifood project, she continues to drive technological advancements, promoting transparency and efficiency in data management.

Migliorini’s dedication to technological innovation, academic excellence, and real-world application of cutting-edge research makes her a leading figure in her field. Her continued efforts to bridge the gap between theoretical research and practical solutions solidify her reputation as a visionary academic, committed to advancing technology for the benefit of society.

 Publications Top Notes

  1. Enhancing Business Process Models with Ethical Considerations

    • Authors: B. Amico, Beatrice; C.K. Combi, Carlo K.; A. Dalla Vecchia, Anna; B. Oliboni, Barbara; E. Quintarelli, Elisa

  2. Augmentation Techniques for Balancing Spatial Datasets in Machine and Deep Learning Applications

    • Authors: A. Belussi, Alberto; D. Garofolo, Diego; S. Migliorini, Sara

  3. A Generic Machine Learning Model for Spatial Query Optimization based on Spatial Embeddings

    • Authors: A. Belussi, Alberto; S. Migliorini, Sara; A. Eldawy, Ahmed

    • Year: 2024

    • Citations: 2

  4. A Survey on Data Availability in Layer 2 Blockchain Rollups: Open Challenges and Future Improvements

    • Authors: M.B. Saif, Muhammad Bin; S. Migliorini, Sara; F. Spoto, Fausto

    • Year: Not specified

    • Citations: 3

  5. Promoting Sustainable Tourism by Recommending Sequences of Attractions with Deep Reinforcement Learning

    • Authors: A. Dalla Vecchia, Anna; S. Migliorini, Sara; E. Quintarelli, Elisa; M. Gambini, Mauro; A. Belussi, Alberto

    • Year: 2024

    • Citations: 3

  6. A Learning-Based Framework for Spatial Join Processing: Estimation, Optimization, and Tuning

    • Authors: T. Vu, Tin; A. Belussi, Alberto; S. Migliorini, Sara; A. Eldawy, Ahmed

    • Year: 2024

    • Citations: 2

  7. Efficient and Secure Distributed Data Storage and Retrieval Using Interplanetary File System and Blockchain

    • Authors: M.B. Saif, Muhammad Bin; S. Migliorini, Sara; F. Spoto, Fausto

    • Year: 2024

    • Citations: 6

  8. Blockchain-Based Multirole Authentication and Authorization in Smart Contracts with a Hierarchical Factory Pattern

    • Authors: M.B. Saif, Muhammad Bin; S. Migliorini, Sara; F. Spoto, Fausto