Haiwei Wu | Engineering | Best Researcher Award

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Prof. Dr. Haiwei Wu | Engineering | Best Researcher Award

Jilin Agricultural University | China

Prof. Dr. Haiwei Wu is an emerging multidisciplinary researcher whose contributions span energy systems, machine learning, spectroscopy, and intelligent diagnostics. His recent research focuses on advanced computational methods applied to energy storage and electric vehicle systems, including the development of an attention-based multi-feature fusion physics-informed neural network for accurate state-of-health estimation of lithium-ion batteries and the application of queuing-theoretic models for sustainable EV charging infrastructure planning. Beyond energy research, he has contributed significantly to the use of mid-infrared spectroscopy combined with machine learning and support vector machines for the authentication and identification of biological and agricultural products, reflecting strong capabilities in analytical modeling and pattern recognition. His publications from 2022 to 2025 highlight expertise in spectral analysis, counterfeit detection, and quality assessment. In addition, he has explored applications of improved YOLOv8 for mechanical part inspection and contributed to research on task-driven cooperative inquiry learning in education. His innovative work is supported by several patents related to electric vehicle charging technologies, demonstrating a commitment to advancing practical, technology-driven solutions across sectors.

Profile : Scopus | Orcid

Featured Publications

Wu, H., Liu, J., Wang, Z., & Li, X. (2025). An attention-based multi-feature fusion physics-informed neural network for state-of-health estimation of lithium-ion batteries. Energies.

Wang, Z., Zou, J., Tu, J., Li, X., Liu, J., & Wu, H. (2025). Towards sustainable EV infrastructure: Site selection and capacity planning with charger type differentiation and queuing-theoretic modeling. World Electric Vehicle Journal.

He, T., Kaimin, W., & Wu, H. (2025). Research on the construction and implementation of a task-driven cooperative inquiry learning model for postgraduate students majoring in music education. Chinese Music Education, (05), 47–53.

Yang, C.-E., Wu, H., Yuan, Y., et al. (2025). Efficient recognition of plum blossom antler hats and red deer antler hats based on support vector machine and mid-infrared spectroscopy. Journal of Jilin Agricultural University, 1–7.

Yang, C.-E., Su, L., Feng, W.-Z., Zhou, J.-Y., Wu, H.-W., Yuan, Y.-M., & Wang, Q. (2023). Identification of Pleurotus ostreatus from different producing areas based on mid-infrared spectroscopy and machine learning. Spectroscopy and Spectral Analysis.

Yang, C.-E., Su, L., Feng, W., et al. (2023). Identification of Pleurotus ostreatus from different origins by mid-infrared spectroscopy combined with machine learning. Spectroscopy and Spectral Analysis, 43(02), 577–582.

Yang, C.-E., Wu, H.-W., Yang, Y., Su, L., Yuan, Y.-M., Liu, H., Zhang, A.-W., & Song, Z.-Y. (2022). A model for the identification of counterfeited and adulterated Sika deer antler cap powder based on mid-infrared spectroscopy and support vector machines. Spectroscopy and Spectral Analysis.

Yang, C.-E., Wu, H., Yang, Y., et al. (2022). Identification model of counterfeiting and adulteration of plum blossom antler cap powder based on mid-infrared spectroscopy and support vector machine. Spectroscopy and Spectral Analysis, 42(08), 2359–2365.

Fucan Huang | Engineering | Excellence in Research Award

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Dr. Fucan Huang | Engineering | Engineering | Excellence in Research Award

Shandong University of Science and Technology | China

Dr. Fucan Huang is an emerging researcher in mechanical fault diagnosis, known for advancing intelligent diagnostic methods through deep learning, multi-attention mechanisms, and cross-domain adaptability. His work focuses on improving fault detection accuracy in complex industrial environments, particularly under fluctuating conditions, imbalanced datasets, and multi-source domain challenges. He has contributed significantly to Measurement Science and Technology and Machines, co-authoring several influential papers. His research includes the development of an adaptive attenuation self-attention adversarial network for cross-domain diagnosis, a multi-source domain collaborative bearing fault method guided by multi-attention mechanisms, and innovative dual-domain vision transformer frameworks. These contributions enhance the robustness, generalizability, and interpretability of diagnostic models, strengthening intelligent maintenance systems and promoting safer, more efficient industrial operations.

Profile : Orcid

Featured Publications

An, Y., Zhang, D., Zhang, M., Xin, M., Wang, Z., Ding, D., Huang, F., & Wang, J. (2025). Residual attention-driven dual-domain vision transformer for mechanical fault diagnosis. Machines, 13(12), Article 1096.

Huang, F., Zhang, Q., Han, B., Wang, J., Zhang, Z., Ge, R., & Gong, H. (2025). Adaptive attenuation self-attention adversarial network for cross-domain fault diagnosis under imbalanced conditions. Measurement Science and Technology, 31 December 2025.

Ge, R., Zhang, Z., Wang, J., Wang, W., Fan, Z., & Huang, F. (2025). Multi-source domain bearing fault collaborative diagnosis method for unbalanced samples guided by multi-attention mechanism. Measurement Science and Technology, 30 November 2025.

Han, B., Huang, F., Qin, M., Qin, H., Wang, J., Zhang, Z., & Yu, Y. (2025). Dual-domain fused vision transformer for mechanical fault diagnosis under fluctuating working conditions. Measurement Science and Technology, 30 April 2025.

Shima Sadaf | Electrical Engineering | Best Academic Researcher Award

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Assist. Prof. Dr. Shima Sadaf | Electrical Engineering | Best Academic Researcher Award

King Faisal University | Saudi Arabia

Assist. Prof. Dr. Shima Sadaf is a highly accomplished researcher in materials science, nanotechnology, electrochemistry, and energy systems, with a strong publication record reflected in 486 citations, an h-index of 11, and an i10-index of 11, demonstrating the impact and consistency of her scientific contributions. Her research spans advanced materials synthesis, including nanomaterials, thin films, perovskites, and green-synthesized nanoparticles, with applications in electrocatalysis, supercapacitors, photocatalysis, energy storage, and environmental remediation. She has made notable advancements in designing electrocatalysts for hydrogen evolution reactions, developing high-performance supercapacitive materials, and creating photocatalysts capable of degrading pollutants and enhancing hydrogen production. Her work also extends to UV photodetectors, memristor technologies, and electrochemical sensors for detecting heavy metals, glucose, uric acid, and dopamine. In the field of energy systems, she has contributed to innovative DC–DC converters, voltage ripple reduction techniques, and sustainable power solutions for nanogrids and renewable energy integration. Her publications include significant contributions to journals in materials chemistry, ceramics, energy conversion, and semiconductor processing, covering topics such as green-synthesized TiO₂/rGO nanocomposites, lead-free perovskites for solar-driven water splitting, NiCo₂O₄-based electrocatalysts, and advanced transition-metal nanoparticles. Her research continues to advance sustainable materials and energy technologies with broad scientific and industrial relevance.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Utami, M., Ramadhani, M. A., Purnama, I., Purwiandono, G., Yenn, T. W., Husniati, Sadaf, S., Al-Taisan, N. A., Almuhawish, N. F., Al-Farhan, A. M., et al. (2026). Green biogenic synthesis of Ag-loaded TiO₂/rGO nanocomposite and its prospective applications in antibacterial and self-cleaning surface coating. Materials Chemistry and Physics, 131573.

Khan, A. N., Rabhi, S., Khan, N. U., Ansari, S. A., Sadaf, S., & Alam, M. W. (2025). Harnessing solar energy with lead-free Tl₂BPI₆ (B = Cs, Rb) double perovskites for photocatalytic water splitting. Ceramics International.

Ghubayra, R., Shariq, M., Sadaf, S., Almuhawish, N. F., Iqbal, M., & Alam, M. W. (2025). Constructing a hybrid CuO over bimetallic spinal NiCo₂O₄ nanoflower as electrocatalyst for hydrogen evolution reaction. International Journal of Hydrogen Energy.

Kaur, H., Sharma, A., Kumar, S., Alam, M. W., Sadaf, S., & Al-Othoum, M. A. S. (2025). Evaluation of photocatalytic efficacy of biosynthesized cubic NiFe₂O₄ nanoparticles. Nano.

Alam, M. W., Kharade, R. B., Alsulaim, G. M., Aleithan, S. H., Sadaf, S., Chava, R. K., Shin, D.-K., & Yewale, M. A. (2025). Improved Ni₃V₂O₈ supercapacitive performance via urea-driven morphological alteration. Ceramics International.

Yewale, M. A., Shin, D. K., Alam, M. W., Teli, A. M., Nabi, S., Ansari, S. A., Sadaf, S., & Al-Kahtani, A. A. (2024). Controlled synthesis and electrochemical characterization of Co₃V₂O₈ hexagonal sheets for energy storage applications. Colloids and Surfaces A: Physicochemical and Engineering Aspects.

Alam, M. W., Nivetha, A., BaQais, A., Ansari, S. A., Yewale, M. A., & Sadaf, S. (2024). Development and analysis of novel Sm-doped LaSiO for photocatalytic degradation and electrochemical sensing of heavy metals. Ceramics International.

Alam, M. W., Ambikapathi, R., Nabi, S., Nivetha, A., Abebe, B., Almutairi, H. H., Sadaf, S., & Almohish, S. M. (2024). Advancements in green-synthesized transition metal/metal-oxide nanoparticles for sustainable wastewater treatment: Techniques, applications, and future prospects. Materials Research Express.

Aldughaylibi, F. S., Ulla, H., Allag, N., Alam, M. W., BaQais, A., Al-Othoum, M. A. S., & Sadaf, S. (2024). Development of molybdenum trioxide–based modified graphite sheet electrodes for enhancing the electrochemical sensing of dopamine. Materials Science in Semiconductor Processing.

Kumar, J. V., Alam, M. W., Selvaraj, M., Almutairi, H. H., Albuhulayqah, M., Sadaf, S., Dhananjaya, M., & Joo, S. W. (2024). Fluorescent carbon dots for biodiesel production: A comprehensive review (2019–2024). Inorganic Chemistry Communications.

Alam, M. W., Allag, N., Utami, M., Waheed-Ur-Rehman, M., Al-Othoum, M. A. S., & Sadaf, S. (2024). Facile green synthesis of α-bismuth oxide nanoparticles: Its photocatalytic and electrochemical sensing of glucose and uric acid in an acidic medium. Journal of Composites Science.

Luigi Fortuna | Engineering | Excellence in Innovation Award

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Prof. Luigi Fortuna | Engineering | Excellence in Innovation Award

Universit Di Catania | Italy

Prof. Luigi Fortuna is a distinguished researcher whose prolific contributions have significantly advanced the fields of automation, nonlinear systems, bioengineering, and control theory. Over his career, he has published 760 scientific documents, accumulating 14,687 citations and achieving an impressive h-index of 67, reflecting the depth and impact of his scholarly output. His extensive body of work spans topics such as robust control, model order reduction, nonlinear electronic circuits, bio-inspired robotics, and complex system engineering. He has co-authored 24 internationally recognized books, including Nonlinear Resonance from Circuits to Systems (2025) and Essentials of Automatic Control with MATLAB in 20 Lessons (2025), which have become key academic resources. A mentor to over 400 thesis projects and 60 Ph.D. students, his dedication to education and innovation is unparalleled. Prof. Fortuna’s research integrates theory and application, exemplified by his 11 industrial patents that bridge academic insight with technological innovation. His leadership roles—such as Dean of Engineering at the University of Catania and Director of the Innovation Relay Center—underscore his influence in academia and industry alike. His interdisciplinary vision continues to inspire advancements in nonlinear dynamics, intelligent systems, and quantum-inspired engineering research worldwide.

Profiles : Scopus | Google Scholar

Featured Publications

Yadav, U. K., Singh, V. P., Fortuna, L., & Sahu, U. K. (2025). SMART-based multi-point matching assisted approximation of renewable interconnected power system. IEEE Access.

Lai, Q., Liu, Y., & Fortuna, L. (2024). Dynamical analysis and fixed-time synchronization for secure communication of hidden multiscroll memristive chaotic system. IEEE Transactions on Circuits and Systems I: Regular Papers.

Fortuna, L., & Buscarino, A. (2024). The impact of circuits and systems on the Etna Valley site [CAS Regional Report]. IEEE Circuits and Systems Magazine, 24(2), 98–100.

Bucolo, M., Buscarino, A., Famoso, C., Fortuna, L., & Frasca, M. (2019). Control of imperfect dynamical systems. Nonlinear Dynamics, 98, 2989–2999.

Buscarino, A., Corradino, C., Fortuna, L., Frasca, M., & Chua, L. O. (2016). Turing patterns in memristive cellular nonlinear networks. IEEE Transactions on Circuits and Systems I: Regular Papers, 63(8), 1222–1230.

Buscarino, A., Gambuzza, L. V., Porfiri, M., Fortuna, L., & Frasca, M. (2013). Robustness to noise in synchronization of complex networks. Scientific Reports, 3(1), 2026.

Frasca, M., Bergner, A., Kurths, J., & Fortuna, L. (2012). Bifurcations in a star-like network of Stuart–Landau oscillators. International Journal of Bifurcation and Chaos, 22(7), 1250173.

Fortuna, L., Frasca, M., & Xibilia, M. G. (2009). Chua’s circuit implementations: Yesterday, today and tomorrow (Vol. 65). World Scientific.

Caponetto, R., Fortuna, L., Fazzino, S., & Xibilia, M. G. (2003). Chaotic sequences to improve the performance of evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 7(3), 289–304.

Bucolo, M., Caponetto, R., Fortuna, L., Frasca, M., & Rizzo, A. (2002). Does chaos work better than noise? IEEE Circuits and Systems Magazine, 2(3), 4–19.*

Rocío Mingorance | Chemical Engineering | Best Research Award

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Mrs. Rocío Mingorance | Chemical Engineering | Best Research Award

Ikerlan Technology Research Center | Spain

Author Profile

Orcid

Early Academic Pursuits

Mrs. Rocío Mingorance began her academic journey with a strong foundation in chemical engineering from the University of Granada, where she developed expertise in process engineering and industrial systems. Her educational path expanded with a master’s degree in industrial maintenance engineering from the University of Huelva, which enriched her technical and managerial skills in plant operations and system reliability. Continuing her pursuit of advanced research, she enrolled in a doctoral program in naval and industrial engineering at the University of Coruña in collaboration with the Ikerlan Technology Research Center, where her focus lies on the development of digital twins for process plants.

Professional Endeavors

Her professional career reflects a steady progression through diverse engineering and industrial roles. Beginning with junior engineering positions in thermosolar power plants, she gained hands-on experience in thermal balances, plant operations, and preventive maintenance. Over the years, she expanded her portfolio through roles in research, consultancy, and control room operations, working with leading companies such as Abengoa, Birchman Consulting, Grupo Cosentino, and Marquesado Solar. Currently, she serves as a thermal engineer and algorithms manager at Sunntics, where she leads the design and implementation of advanced thermal control systems to optimize concentrated solar power plants.

Contributions and Research Focus

Mrs. Mingorance’s research and technical contributions have centered on advancing renewable energy technologies, thermal engineering, and digital solutions for industrial systems. Her expertise in developing and applying thermal models for heat and mass transfer has contributed significantly to improving system performance under standard and unexpected conditions. She has also pioneered work on digital twins, offering innovative methodologies to enhance operational strategies and resilience in manufacturing and energy plants. Her publications highlight her contribution to bridging traditional engineering with modern computational tools.

Accolades and Recognition

Her research and professional achievements have been recognized through publications in reputed international journals and conferences. Notably, her work on the evolution of digital twin solutions was presented at the IEEE Smart World Congress, reflecting her standing in the global research community. In addition, her continued contributions to the field of industrial and thermal engineering have positioned her as a promising scholar and professional in advancing sustainable and technologically driven energy solutions.

Impact and Influence

Through her interdisciplinary expertise, Mrs. Mingorance has influenced both industrial practices and academic research. Her ability to integrate advanced modeling techniques with real-world plant operations has enhanced the reliability, efficiency, and safety of thermal and renewable energy systems. Her contributions extend beyond direct applications, inspiring new approaches in engineering education, collaborative industry research, and the adoption of digital innovations in traditional sectors.

Legacy and Future Contributions

Looking forward, Mrs. Mingorance’s ongoing doctoral research in digital twins for process plants is expected to leave a lasting legacy in the field of industrial and naval engineering. By combining her strong background in thermal sciences with cutting-edge computational techniques, she is poised to contribute transformative solutions that support sustainability, automation, and resilience in complex industrial systems. Her career trajectory suggests continued advancements that will influence both academia and industry in the years to come.

Publications

  • Title: A methodology leveraging digital twins to enhance the operational strategy of manufacturing plants in unexpected scenarios

  • Authors: Rocío Mingorance, Diego Crespo Pereira, Jone Uribetxebarria, Urko Leturiondo

  • Journal: Results in Engineering

  • Year: 2025

  • Title: Evolution of Digital Twin solutions in the manufacturing industry

  • Authors: Rocío Mingorance, Diego Crespo Pereira, Jone Uribetxebarria, Urko Leturiondo

  • Journal/Conference: Proceedings of the 2023 IEEE Smart World Congress (SWC)

  • Year: 2023

Conclusion

Mrs. Rocío Mingorance exemplifies the synergy between engineering practice and academic research. With a solid educational foundation, diverse professional experiences, and impactful research contributions, she stands as a leading figure in renewable energy and digital innovation. Her work continues to shape sustainable industrial practices and drive the integration of advanced technologies in energy systems, reflecting a career dedicated to both excellence and progress.

 

Hafiz Mohammad Hasan Babu | Computer Science | Lifetime Achievement in Books Award

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Prof. Hafiz Mohammad Hasan Babu | Computer Science | Lifetime Achievement in Books Award

University of Dhaka | Bangladesh

Author Profile

Scopus

Orcid

Google Scholar

Early Academic Pursuits

Prof. Hafiz Mohammad Hasan Babu began his academic journey in the realm of computer science and engineering with a strong foundation from the Brno University of Technology, Czech Republic, where he completed his M.Sc. with a focus on logic network automation. His curiosity for advanced computational systems took him to the Kyushu Institute of Technology in Japan, where he earned his Ph.D. in Computer Science and Electronics. His doctoral work concentrated on data structures for multiple-output functions and their applications in VLSI CAD, under the guidance of Prof. Dr. Tsutomu Sasao. These formative years laid the groundwork for his future innovations in quantum computing, reversible logic, and nanotechnology.

Professional Endeavors

Prof. Hasan Babu's academic career spans several decades and institutions, notably the University of Dhaka, where he served in various capacities, including as professor in the departments of Computer Science and Engineering, and Robotics and Mechatronics Engineering. His early academic roles also included positions at Khulna University. He has been deeply involved in curriculum development, student mentorship, and departmental leadership. Beyond teaching, he also contributed significantly as a research supervisor and played a critical role in developing the academic and research culture of computer science in Bangladesh.

Contributions and Research Focus

A prolific researcher, Prof. Hasan Babu has made groundbreaking contributions in the fields of quantum computing, reversible logic design, DNA computing, and machine learning applications in healthcare and agriculture. His interdisciplinary research integrates electronics, artificial intelligence, and biological systems. His most recent works delve into quantum biocomputing and nanotechnology, as evidenced by his multi-volume publications with Springer Nature and CRC Press. He has also authored numerous peer-reviewed articles on topics such as cardiovascular disease detection using mobile AI, air quality forecasting, and toxic substance identification in fruits through deep learning.

Accolades and Recognition

Prof. Hasan Babu has received numerous prestigious awards recognizing his excellence in research and scholarly contributions. These include the Dhaka University Research Excellence Recognition, the UGC Gold Medal, and the Dr. M. O. Ghani Memorial Gold Medal from the Bangladesh Academy of Sciences. His biography has been featured in “Who's Who in the World, USA.” He has also received international fellowships such as the Japanese Government Scholarship, the DAAD Fellowship from Germany, and a Czechoslovakian Government Scholarship, marking his global academic influence.

Impact and Influence

Throughout his academic life, Prof. Hasan Babu has significantly influenced the fields of computer science, electronics, and artificial intelligence. His innovations in reversible logic and DNA computing have shaped research methodologies and applications in both academia and industry. He has been instrumental in advancing computational methods that address real-world problems, particularly in environmental monitoring, biomedical diagnostics, and agricultural automation. His role as a mentor to doctoral and master’s students further amplifies his impact on the next generation of scholars.

Legacy and Future Contributions

Prof. Hasan Babu’s extensive scholarly contributions, particularly in the emerging domains of quantum AI and biocomputing, position him as a thought leader in futuristic technologies. His upcoming publications promise to offer new paradigms in nanotechnology and molecular-level computing. As he continues to mentor new researchers and expand the boundaries of interdisciplinary science, his legacy will be defined by his relentless pursuit of innovation and his dedication to fostering a globally relevant research ecosystem.

List of Book Publications

Books Published in 2025:

1. Quantum AI Emerging Technologies: Driving Innovation and Shaping the Future of Nanotechnology, Volume I, Springer Nature, Singapore.

2. Quantum AI Emerging Technologies: Driving Innovation and Shaping the Future of Nanotechnology, Volume II, Springer Nature, Singapore.

3. Quantum Biocomputing in Quantum Biology, Volume I, Springer Nature, Singapore.

4. Quantum Biocomputing in Quantum Biology, Volume II, Springer Nature, Singapore.

Book Published in 2024:
5. DNA Logic Design: Computing with DNA, World Scientific Publishing Co Pte Ltd., Singapore.

Books Published in 2023:
6. Multiple-Valued Computing in Quantum Molecular Biology, Volume I, CRC Press, USA.
7. Multiple-Valued Computing in Quantum Molecular Biology, Volume II, CRC Press, USA.

Books Published in 2022:
8. VLSI Circuits and Embedded Systems, CRC Press, USA.
9. Control Engineering Theory and Applications (Co-authored with Md. Jahangir Alam, Guoqing Hu, and Huazhong Xu), CRC Press, USA.

Books Published in 2020:
10. Quantum Computing: A Pathway to Quantum Logic Design, 2nd Edition, IOP Publishers, Bristol, UK.
11. Reversible and DNA Computing, Wiley Publishers, UK.

Journal Publications

Analyzing infant cry to detect birth asphyxia using a hybrid CNN and feature extraction approach
Authors: Samrat Kumar Dey, Khandaker Mohammad Mohi Uddin, Arpita Howlader, Md Mahbubur Rahman, Hafiz Md Hasan Babu, Nitish Biswas, Umme Raihan Siddiqi, Badhan Mazumder
Journal: Neuroscience Informatics (Elsevier)
Year: 2025

Empowering early detection: A web-based machine learning approach for PCOS prediction
Authors: Md. Mahbubur Rahman, Ashikul Islam, Forhadul Islam, Mashruba Zaman, Md Rafiul Islam, Md Shahriar Alam Sakib, Hafiz Md Hasan Babu
Journal: Journal of Informatics in Medicine (Elsevier)
Year: 2024

Computer vision based deep learning approach for toxic and harmful substances detection in fruits
Authors: Abdus Sattar, Md. Asif Mahmud Ridoy, Aloke Kumar Saha, Hafiz Md. Hasan Babu, Mohammad Nurul Huda
Journal: Heliyon (Cell Press)
Year: 2024

A Comprehensive Approach to Detecting Chemical Adulteration in Fruits Using Computer Vision, Deep Learning, and Chemical Sensors
Authors: Abdus Sattar, Md. Asif Mahmud Ridoy, Aloke Kumar Saha, Hafiz Md. Hasan Babu, Mohammad Nurul Huda
Journal: Journal of Intelligent Systems with Applications (Elsevier)
Year: 2024

A Voice assistive mobile application tool to detect cardiovascular disease using machine learning approach
Authors: Khandaker Mohammad Mohi Uddin, Samrat Kumar Dey, Hafiz Md Hasan Babu
Journal: Biomedical Materials & Devices (Springer US)
Year: 2024

Conclusion

Prof. Hafiz Mohammad Hasan Babu embodies the spirit of academic excellence and innovation in computer science. With a career rich in scholarly output, international collaborations, and student mentorship, he has become a beacon of transformative research and a visionary in integrating quantum theory with computational systems. His work continues to influence the scientific community both in Bangladesh and globally, promising continued advancements in technology and applied sciences.

Ming Cao | Engineering | Best Researcher Award

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Prof. Dr. Ming Cao | Engineering | Best Researcher Award

Nanchang University | China

Author Profile

Orcid

🎓 Early Academic Pursuits

Prof. Dr. Ming Cao embarked on his academic journey with a Bachelor's degree in Software Engineering  from Nanchang University. His interdisciplinary curiosity led him to pursue a Master's in Vehicle Engineering , followed by a Doctorate in Mechanical Engineering  from the same institution. This academic progression illustrates his transition from software to hardware systems, laying a solid foundation for his future in automotive and advanced manufacturing research.

🏢 Professional Endeavors

Currently serving as Associate Dean and Associate Professor at the School of Advanced Manufacturing, Nanchang University, Dr. Cao has held numerous academic positions over the years. His career began as an Assistant Lecturer, then Lecturer , and advanced to his current role in 2023. Simultaneously, he is enriching his research profile as a Postdoctoral Researcher at the prestigious Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences . Notably, he also gained international exposure as a Visiting Scholar at the University of Kansas.

🔬 Contributions and Research Focus

Prof. Cao's research sits at the intersection of mechanical engineering, microfluidics, bio-manufacturing, and artificial intelligence. His recent works focus on high-throughput digital microfluidic systems, YOLOv8-based object detection, automated inkjet printing, and cryogenic extrusion technologies. His innovative approaches are evident in impactful publications like:

  •  ➤ YOLOv8-Seg-based evaluation for bioprinting

  •  ➤ AI-enhanced microfluidic systems

  •  ➤ Smart composite hydrogels for flexible strain sensors
    These contributions aim to transform precision manufacturing, sensor development, and biomedical applications.

🏆 Accolades and Recognition

While explicit awards are not listed, Prof. Cao's continuous progression within Nanchang University, international collaborations, and his prolific publication record in Micromachines, ACS Applied Polymer Materials, and Fibers and Polymers underscore the academic community’s recognition of his innovative work and leadership in research. His appointment as Associate Dean further reflects his respected status in academic and administrative circles.

🌍 Impact and Influence

Dr. Cao's work is bridging the gap between academia and real-world manufacturing challenges. His research on smart sensors and AI-integrated fabrication methods is pushing the frontiers of intelligent manufacturing and sustainable biomedical device development. Moreover, by mentoring students and contributing to global research dialogue, he is shaping the next generation of engineers and innovators.

🔮 Legacy and Future Contributions

Looking ahead, Prof. Dr. Ming Cao is poised to make landmark contributions in precision bio-manufacturing, AI-integrated engineering, and smart materials. His leadership at Nanchang University and collaboration with CAS suggest continued influence in shaping China's advanced manufacturing roadmap. As technology rapidly evolves, his work will likely be instrumental in crafting more sustainable, intelligent, and adaptable production systems.

Publications

📄 Uniformity evaluation of bio-printer products based on an improved YOLOv8-Seg model
Authors: Cao Ming, Duan Wufeng, Ma Mengxiao, et al.
Journal: Journal of Zhejiang University (Engineering Science)
Year: 2025

📄 Design and Implementation of a High-Throughput Digital Microfluidic System Based on Optimized YOLOv8 Object Detection
Authors: Cao M, Duan W, Huang Z, Liang H, Ai F, Liu X
Journal: Micromachines
Year: 2025

📄 An automated digital microfluidic system based on inkjet printing
Authors: Wansheng Hu, Ming Cao, Lingni Liao, Yuanhong Liao, Yuhan He, Mengxiao Ma, Simao Wang, Yimin Guan*
Journal: Micromachines
Year: 2024

📄 Self-Adhesive, Antifreezing, and Antidrying Conductive Glycerin/Polyacrylamide/Chitosan Quaternary Ammonium Salt Composite Hydrogel as a Flexible Strain Sensor
Authors: Liu S, Wan L, Hu FF, Wen ZW, Cao M., Ai FR
Journal: ACS Applied Polymer Materials
Year: 2023

📄 Cryogenic Extrusion Printing of PCL-HAW Scaffolds and Self-induced Crystalline Surface Modification
Authors: Zhou K., Chen H., Xu Z., Zeng J., Cao M
Journal: Fibers and Polymers
Year: 2024

Ji Changpeng | Engineering | Best Researcher Award

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Prof. Ji Changpeng | Engineering | Best Researcher Award

Liaoning Technical University | China

Author Profile

Orcid

Early Academic Pursuits 🎓

Prof. Ji Changpeng began his academic journey with a Master’s degree in Computer Application Technology from Liaoning Technical University, which he completed in 2005. His strong foundation in computer applications laid the groundwork for his illustrious career in academia and research. With a keen interest in technological innovation and problem-solving, Prof. Ji's early academic endeavors marked the beginning of his contributions to the field of computer science.

Professional Endeavors 🏢

Currently a full professor and Master supervisor at Liaoning Technical University, Prof. Ji holds several prestigious roles. He is a recognized Codesys Senior Application Engineer and a Senior Artificial Intelligence Designer. As the Academic Leader of Information and Communication Engineering, he has played a pivotal role in shaping the department's vision. Additionally, his influence extends to academic leadership as a key member of the Outstanding Young Teacher initiative in Liaoning Province (2006). He also serves as an expert in discipline assessment and dissertation evaluations for the Ministry of Education, showcasing his authority in the field.

Contributions and Research Focus 🔬

Prof. Ji’s research contributions are vast and impactful. Having presided over more than 60 research projects, his work has significantly advanced the fields of artificial intelligence, information engineering, and communication systems. He has published over 160 academic papers and authored three academic works, contributing valuable insights and innovation to the global research community. His patents, numbering more than 40, highlight his practical approach to solving complex technological problems. Prof. Ji’s expertise as an editor and reviewer for esteemed journals such as Journal of Computers and IJConvC further solidifies his influence in academia.

Accolades and Recognition 🏆

Prof. Ji has received six prestigious science and technology advancement medals for his groundbreaking contributions. His role as an editorial board member and specialist reviewer for several reputed journals speaks volumes about his standing in the academic world. These accolades reflect his dedication to excellence and his commitment to pushing the boundaries of technology and innovation.

Impact and Influence 🌟

Through his extensive research, patents, and academic leadership, Prof. Ji has profoundly influenced the fields of artificial intelligence and communication engineering. His role in mentoring future researchers and supervising Master’s students ensures that his knowledge and vision continue to inspire the next generation. His work has not only shaped his university but has also had a far-reaching impact on the global research community.

Legacy and Future Contributions 🌍

Prof. Ji Changpeng’s contributions have left an indelible mark on the academic and technological landscape. His ability to blend research with practical application has set a benchmark for innovation. As he continues to explore new frontiers in artificial intelligence and communication engineering, his legacy will undoubtedly pave the way for groundbreaking advancements and a brighter future for technology and education.

 

Publications

📄 Design of Shared-Aperture Base Station Antenna with a Conformal Radiation Pattern
Journal: Electronics
Year: 2025
Authors: Ji Changpeng, Xin Ning, Wei Dai

📄 A Lightweight Safety Helmet Detection Algorithm Based on Receptive Field Enhancement
Journal: Processes
Year:2024
 Authors: Ji Changpeng, Zhibo Hou, Wei Dai

 

Alice Cervellieri | Engineering | Best Researcher Award

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Dr. Alice Cervellieri | Engineering | Best Researcher Award

Politecnico di Torino | Italy

Author Profile

Scopus

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Early Academic Pursuits 🎓

Dr. Alice Cervellieri began her academic journey with a Bachelor’s degree in Civil and Environmental Engineering from the University of Engineering, Bologna, in 2005, achieving a perfect score of 110/110 laude. Her pursuit of excellence continued with a Master’s degree in Civil Engineering from the same institution in 2011. Notably, she expanded her intellectual horizons by earning a Bachelor’s degree in Linguistic Mediation Sciences from the School of Advanced Linguistic Mediation in 2019, graduating with an outstanding average of 29. Her educational endeavors were further enriched by certifications and specialized training. She participated in the ERASMUS Virtual Exchange program in 2020, focusing on dialogue facilitation, and completed the “Certificatore Energetico” course by Assform in 2016, gaining qualifications as an energy certifier. Dr. Cervellieri also acquired advanced knowledge in digital transformation technologies through a prestigious course at the Massachusetts Institute of Technology (MIT) in 2021.

Professional Endeavors 🌍

Dr. Cervellieri has played significant roles in academia and professional training. She served as a visiting professor at the Catholic University of Manizales, Colombia, in November 2020. Her teaching contributions also include assignments for the Emilia Romagna Region’s “Energy Certifier” course and tutoring roles for EUSAIR Week. Since 2021, she has been a mentor for Harvard University’s Mentorship Project, showcasing her dedication to fostering the next generation of scholars. Her formal qualifications to practice civil engineering were solidified by passing the state examination at the Polytechnic University of Marche in 2016. These accomplishments underscore her dual commitment to practical engineering applications and academic mentorship.

Contributions and Research Focus 🔄

Dr. Cervellieri’s research lies at the intersection of energy analysis and comfort optimization in residential and rural buildings. Her studies delve into established metrics such as PMV (Predicted Mean Vote) and PPD (Percentage of People Dissatisfied), as well as the development of novel indices like OTE and OEE. These indices, drawn from the manufacturing sector, have been innovatively adapted to enhance energy efficiency and occupant comfort. Her international collaborations have facilitated the development of groundbreaking algorithms, as evidenced by her impressive publication record. Dr. Cervellieri’s contributions include six publications in international scientific journals, ten conference proceedings, six books, two posters, and a national journal article.

Accolades and Recognition 🏆

Dr. Cervellieri’s academic achievements have been consistently recognized. Her selection as a mentor for prestigious projects like the Harvard Mentorship Program underscores her global standing as an educator and researcher.

Impact and Influence 💡

Dr. Cervellieri has significantly influenced the field of sustainable engineering through her participation in international projects. She contributed to the EU H2020 Project "ENCORE," which focused on energy-aware BIM Cloud Platforms for efficient building renovation. Additionally, her work in the EFRE-FESR Project "Brotweg" explored innovative mechanized solutions for high-altitude cereal production in alpine environments. These projects reflect her commitment to sustainable development and technological advancement. Her participation in the Erasmus+ Virtual Exchange project (2018-2020) exemplifies her dedication to fostering intercultural learning and virtual collaboration, providing young minds with transformative educational experiences.

Legacy and Future Contributions 🌱

Dr. Alice Cervellieri’s legacy is one of interdisciplinary excellence and global collaboration. Her contributions to energy-efficient building systems and educational mentorship are poised to leave a lasting impact on the fields of civil engineering and sustainable development. With her commitment to innovation and fostering cross-cultural dialogue, she is well-positioned to continue influencing academia and industry for years to come. As she advances her career, Dr. Cervellieri’s work will undoubtedly inspire future engineers and researchers to embrace sustainability and technological innovation as integral components of their practice.

 

Publications

📄 A Feed-Forward Back-Propagation Neural Network Approach for Integration of Electric Vehicles into Vehicle-to-Grid (V2G) to Predict State of Charge for Lithium-Ion Batteries
Authors: Alice Cervellieri
Journal: Energies
Year: 2024

📄 On the Synthesis of Holonic Management Trees
Authors: Pirani, M., Bonci, A., Cervellieri, A., Longhi, S.
Journal: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Year: 2021

📄 Innovative Approach in Cyber-Physical System for Smart Building Efficiency Monitoring
Authors: Bonci, A., Cervellieri, A., Longhi, S., Pirani, M.
Journal: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Year: 2021

📄 The Double Propeller Ducted-Fan, an UAV for Safe Infrastructure Inspection and Human-Interaction
Authors: Bonci, A., Cervellieri, A., Longhi, S., Nabissi, G., Antonio Scala, G.
Journal: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Year: 2020

📚 Brotweg—A Path of Bread in an Alpine Environment: New Mechanical Solutions for Grain Processing in Steep Mountain Slopes
Authors: Mayr, S., Brozzi, R., Cervellieri, A., Sacco, P., Mazzetto, F.
Journal: Lecture Notes in Civil Engineering
Year: 2020

 

Luis Cavique | Computer Science | Best Research Award

Published on by Book of Award

Prof. Luis Cavique | Computer Science | Best Research Award

Universidade Aberta | Portugal

Author Profile

Scopus

Orcid

Early Academic Pursuits 🎓

Prof. Luís Cavique began his academic journey with a strong foundation in Computer Science, earning a degree in Computer Science Engineering in 1988 from the Faculty of Science and Technology at the New University of Lisbon. His pursuit of advanced knowledge continued with a Master’s in Operational Research and Systems Engineering in 1994 from the Instituto Superior Técnico, Technical University of Lisbon, where he focused on complex problems like crew scheduling. His academic commitment culminated in 2002 with a PhD in Engineering Systems, where he explored meta-heuristics for the Maximum Clique Problem, emphasizing applications in market basket analysis. This robust educational background set the stage for a career marked by analytical depth and academic rigor.

Professional Endeavors 👨‍🏫

Prof. Cavique’s teaching career spans several decades, beginning in 1991 in the Polytechnic Education System in Portugal, where he held adjunct positions at Setúbal and Lisbon Polytechnic Institutes until 2008. Since then, he has served as an Assistant Professor with tenure at the Universidade Aberta, focusing on computer science within the Department of Sciences and Technology. His dedication to fostering knowledge extends to graduate and doctoral levels, where he teaches courses such as Data Mining, Social Network Analysis, and Optimization. Beyond academia, Prof. Cavique also gained hands-on experience in the banking sector as a Systems Engineer at Banco Pinto & Sotto Mayor and through internships at prominent institutions like Banco Espírito Santo and the National Laboratory of Civil Engineering.

Contributions and Research Focus 🔍

With a strong interdisciplinary approach, Prof. Cavique’s research bridges Computer Science and Engineering Systems, focusing primarily on heuristic optimization and data mining. His work has addressed three core data mining challenges: classification, association, and segmentation. Notable publications include groundbreaking algorithms and tools, such as the LAID algorithm for classification, Ramex for association in financial product analysis, and ComDetection for community detection in social networks. These contributions have positioned Prof. Cavique at the forefront of data-driven research, and his methods are applied widely in sectors requiring complex data analysis.

Accolades and Recognition 🏆

Prof. Cavique's scholarly work has been recognized internationally, with several of his papers published in prestigious journals. His 1999 paper on crew scheduling received the IFORS-Lisbon Prize in 2000 from the Association of Operational Research in Portugal (APDIO). Many of his publications are highly cited, with articles featured in Q1-ranked journals, illustrating the high impact and quality of his research. His dedication to advancing data mining and optimization has earned him both peer recognition and a strong citation record, showcasing his influence in these fields.

Impact and Influence 🌍

Throughout his career, Prof. Cavique has made a lasting impact on the fields of data mining and heuristic optimization. His research has influenced approaches in financial analytics, community detection in social networks, and data reduction techniques, providing foundational tools and algorithms that are utilized in academia and industry alike. His methodologies have empowered researchers and practitioners in various domains to make informed, data-driven decisions, underscoring his role as a pioneer in computational research.

Legacy and Future Contributions 🌟

As a leading academic and researcher, Prof. Cavique’s legacy is defined by his contributions to both knowledge and education in computer science. His focus on heuristic optimization and data mining continues to inspire new research, particularly in emerging fields such as bioinformatics and social network analysis. His commitment to teaching and mentoring the next generation of scientists ensures that his impact will extend well into the future, enriching the scientific community and driving innovation in computational methods.

 

Publications

  • 📝 Mitigating false negatives in imbalanced datasets: An ensemble approach
    Authors: Marcelo Vasconcelos; Luís Cavique
    Journal: Expert Systems with Applications
    Year: 2024
  • 📝 Assessment in Collaborative Learning
    Authors: Luis Cavique; M. Rosário Ramos
    Journal: Revista de Educación a Distancia (RED)
    Year: 2024