Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

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Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile 

Orcid

Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

Research on the Design and Application of Multi-Port Energy Routers

 

Inga Christina Miadowicz | Computer Science and Artificial Intelligence | Best Researcher Award

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Inga Christina Miadowicz | Computer Science and Artificial Intelligence | Best Researcher Award

Mrs Inga Christina Miadowicz, Deutsches Zentrum für Luft- und Raumfahrt, Germany

Dr. Inga Christina Miadowicz is a dedicated researcher specializing in IT management, industrial autonomy, and solar energy systems. She holds a Master’s in IT-Management from FOM Mannheim and a Bachelor’s in Applied Computer Science from DHBW Mannheim. Currently a Research Assistant at Deutsches Zentrum für Luft- und Raumfahrt (DLR), she leads projects in autonomous solar power plants and cyber-physical system infrastructures. Her expertise spans software engineering, distributed systems, and performance optimization. As a university lecturer at DHBW Mannheim, she teaches advanced software engineering and distributed systems. Her contributions to solar power plant digitization, industrial autonomy, and energy management have been published in renowned journals and conferences. She is an active participant in cutting-edge research on 5G communication for solar plants. With a strong foundation in IT architecture, cloud computing, and SAP technologies, she continues to drive innovation in the field of renewable energy and digital transformation. 🔬☀️🚀

Publication Profile

Orcid

Education

Dr. Inga Christina Miadowicz has a solid academic background in IT management and applied computer science. She earned her Master of Science in IT-Management (2018-2021) from Fachhochschule für Oekonomie und Management (FOM), Mannheim, where she specialized in enterprise IT strategies and digital transformation. Her Bachelor of Science in Applied Computer Science (2013-2016) from Duale Hochschule Baden-Württemberg (DHBW), Mannheim, provided her with hands-on experience in software development, system architecture, and distributed computing. She completed her Abitur (2004-2013) at Theodor-Fliedner-Gymnasium, Düsseldorf, establishing a strong foundation in STEM disciplines. Her commitment to continuous learning is reflected in multiple professional certifications, including Certified Business Professional and Certified Solution Professional (FICO), as well as specialized training in Apache Kafka, SAP HANA, SAPUI5, and OData services. Through her graduate program at DLR (since 2022), she continues to enhance her expertise in advanced IT solutions for industrial applications. 📚💡

Experience

Dr. Inga Christina Miadowicz has extensive experience in IT research, software development, and teaching. Since April 2022, she has been a Research Assistant at DLR (Cologne, Germany), leading projects on autonomous solar power plants and industrial autonomy. She has also served as a university lecturer at DHBW Mannheim (since 2018), teaching distributed systems and software engineering. Previously, she was a Lead Developer at FICO (2019-2022), where she developed anti-money laundering software and optimized performance engineering tools. As a Development Consultant at Slenderiser GmbH (2018-2019), she contributed to SAP S/4HANA transformations. Her tenure at SAP SE (2016-2018) focused on cloud and on-premise solutions for consumer industries. She also gained experience as a Dual Studies developer at ALDI SÜD (2013-2016), working on web and cloud computing solutions. Her diverse expertise in cyber-physical systems, SAP development, and IT architecture makes her a leading researcher in the field. 🚀🌞

Awards and Honors

Dr. Inga Christina Miadowicz has been recognized for her contributions to IT management, software engineering, and renewable energy research. She was awarded the Chinese Government Scholarship for her exceptional academic achievements. Her graduate program at DLR is a testament to her dedication to cutting-edge industrial research. She has received multiple professional certifications, including Certified Business Professional and Certified Solution Professional (FICO), as well as specialized SAP certifications like C_FIORIDEV_20. Her work on autonomous solar power plants and 5G communication for solar plants has been featured at prestigious conferences like SolarPACES. Her performance engineering contributions at FICO helped optimize anti-money laundering software, earning industry recognition. As a university lecturer, she has mentored numerous students in software development and distributed systems. Her commitment to research, education, and technological advancement positions her as a strong candidate for the Best Researcher Award. 🎖️📡☀️

Research Focus

Dr. Inga Christina Miadowicz focuses on industrial autonomy, digital transformation, and renewable energy optimization. At DLR, she leads research on autonomous solar power plants, developing cyber-physical systems and AI-driven automation for power plant operations. Her work integrates 5G communication networks with solar tower plants, enhancing real-time data processing and remote control capabilities. She specializes in distributed systems, software engineering, and cloud-based industrial solutions, particularly in SAP S/4HANA, Fiori applications, and performance engineering. Her research extends to data-driven hardware sizing tools, automation frameworks, and performance optimization for large-scale infrastructure. Her expertise in cybersecurity, IT architecture, and advanced analytics enables her to drive innovation in industrial digitalization. Through her publications in Solar Energy Advances and SolarPACES Conference Proceedings, she contributes to the advancement of solar energy integration and digital infrastructure for smart grids. Her work bridges the gap between IT, industrial automation, and sustainable energy solutions. 🌞📊💡

Publication Top Notes

📄 An Action Research Study on the Digital Transformation of Concentrated Solar Thermal Plants – Solar Energy Advances (2025)
📄 An Action Research Study on the Digital Transformation of Concentrated Solar Thermal Plants – Solar Energy Advances (2024-11-19)
📄 5G as Communication Platform for Solar Tower Plants – SolarPACES Conference Proceedings (2024-07-24)
📄 5G as Communication Platform for Solar Tower Plants – SolarPACES Conference Proceedings (2024-07-24, DOI: 10.52825/solarpaces.v2i.858)
📄 5G as Communication Platform for Solar Tower Plants – 29th International Conference on Concentrating Solar Power and Chemical Energy Systems, SolarPACES 2023

Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

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Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Kaimin Wei, Jinan University, China

Kaimin Wei is a full professor at the College of Information Science and Technology, Jinan University, China 🇨🇳. He earned his Ph.D. in Computer Science from Beihang University (2015), Master’s in Computer Application Technology from Zhengzhou University (2010), and Bachelor’s in Computer Science from Yuncheng University (2007) 🎓. A distinguished Young Pearl River Scholar 🌟, his research focuses on mobile computing, edge intelligence, and AI security 📱🤖🔒. Prof. Wei has published extensively in top journals and conferences, contributing to advancements in algorithm optimization and security techniques 📊📚.

Publication Profile

Orcid

Academic Background 

Prof. Kaimin Wei 🌟 holds a Ph.D. in Computer Science from Beihang University (2015) 🎓, a Master’s degree from Zhengzhou University (2010) 📚, and a Bachelor’s from Yuncheng University (2007) 🎯. His academic journey showcases dedication and excellence in the field of computer science 💻. Recognized for his outstanding achievements, he was honored as a Young Pearl River Scholar 🌊, reflecting his leadership potential and scholarly impact. Prof. Wei’s contributions to academia continue to inspire, highlighting his commitment to research, innovation, and education 🚀

Research Interests 

Prof. Kaimin Wei is a distinguished expert in Mobile Computing 📱, specializing in Edge Intelligence 🌐 and Artificial Intelligence Security 🔐. His research focuses on enhancing the efficiency and security of mobile technologies, leveraging cutting-edge edge intelligence to optimize data processing and real-time decision-making. Prof. Wei’s work in AI security ensures robust protection against emerging cyber threats, contributing to the development of safer, smarter digital ecosystems. His innovative approach bridges the gap between mobile computing and advanced AI applications, driving technological progress and shaping the future of secure, intelligent systems. 🚀🤖

Research Focus

Prof. Kaimin Wei’s research focuses on privacy-preserving technologies, federated learning, mobile crowdsensing, and cybersecurity 🔐📡. His work explores UAV crowdsensing with energy efficiency, gradient inversion attacks in federated learning without prior knowledge, and group task recommendations using neural collaborative approaches 🤖✨. He also investigates secure device pairing through acceleration-based methods with visual tracking and develops robust defense mechanisms against adversarial attacks using feature purification networks 🛡️📊. Prof. Wei’s interdisciplinary research blends Internet of Things (IoT), machine learning, and security protocols to enhance data privacy and system resilience 🌍🔍.

Publication Top Notes

PD-DRL: Towards privacy-preserving and energy-sustainable UAV crowdsensing

GI-SMN: Gradient Inversion Attack Against Federated Learning Without Prior Knowledge

Group Task Recommendation in Mobile Crowdsensing: An Attention-Based Neural Collaborative Approach

Attacks on Acceleration-Based Secure Device Pairing With Automatic Visual Tracking

FePN: A robust feature purification network to defend against adversarial examples

A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities

Automatic Tagging by Leveraging Visual and Annotated Features in Social Media

Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

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Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

Prof. Dr Bhanu Shrestha, Kwangwoon University, South Korea

Prof. Dr. Bhanu Shrestha is a distinguished academic in Electronic Engineering, with a Ph.D. from Kwangwoon University, Seoul, Korea. He has been active in various leadership roles, including Chairman of ICT-AES and Editor-in-Chief of the International Journal of Advanced Engineering. Dr. Shrestha has contributed extensively to research, with notable book publications and multiple awards, including the “Achievement Award” from IIBC Korea and “Best Paper Award” at ISSAC 214. His work spans various international conferences, focusing on advanced engineering, nanotechnology, and biosensor applications. 🌍📚🏅💻🧑‍🔬

Publication Profile

Scopus

Education

Prof. Dr. Bhanu Shrestha has an extensive academic background in Electronic Engineering. He completed his Ph.D. in Electronic Engineering at Kwangwoon University, Seoul, Korea (2004-2008), after earning his M.S. in the same field at the same institution (2002-2004). Dr. Shrestha’s journey in engineering began with a B.S. in Electronic Engineering from Kwangwoon University (1994-1998). His years of dedication to education and research have contributed significantly to advancements in the field of electronics. ⚙️🎓📡

Experience

Prof. Dr. Bhanu Shrestha is a distinguished leader in engineering, serving as Chairman of ICT-AES from 2022 to 2024. With a long tenure as the Editor-in-Chief of the International Journal of Advanced Engineering, he has shaped academic discourse in the field. His active involvement with the Nepal Engineering Council (NEC) and Nepal Engineers’ Association (NEA) further cements his influence in Nepal’s engineering community. Prof. Shrestha’s commitment to advancing engineering practices is evident through his leadership roles and active contributions to both national and international engineering platforms. 🛠️📚🔧🌍

Honor & Awards

Prof. Dr. Bhanu Shrestha has received numerous prestigious awards throughout his career. Notably, he was honored with the “Achievement Award” from IIBC Korea (2015) 🏆 and multiple “Best Paper Awards” from ISSAC 214 and ICACT (2014) 📄. He also earned the “Excellent Paper Award” from the Korea Institute of Information Technology (2012) 🏅 and the “Certificate of Honorary Citizenship” from the Mayor of Seong-buk, Seoul (2012) 🏙️. His accolades extend to Nepal, where he received the presidential “Nepal Vidhyabhusan Padak ‘Ka’” Gold Medal (2009) 🥇, and several honors for his contributions to Taekwondo and Hapkido 🥋.

Research Focus

Prof. Dr. Bhanu Shrestha’s research focuses on advanced computational techniques, particularly in the intersection of artificial intelligence (AI) and engineering. He explores areas such as machine learning, metaheuristics, and optimization methods applied to real-world challenges in fields like medical imaging (e.g., SPECT-MPI cardiovascular disease classification), traffic accident prediction, and network security. His work also extends to customer churn prediction in telecom industries and network security improvements. Shrestha’s contributions aim to enhance system efficiency, prediction accuracy, and security across diverse technological and engineering domains. 🧠💻⚙️🩺📡

Editorial and Conference

Prof. Dr. Bhanu Shrestha has made significant contributions to the field of engineering through his active involvement in international conferences like ISGMA 2015 and the International Conference on ICT & Digital Convergence (2018) 🌍📡. His dedication to global collaboration is evident in his participation in these events. Additionally, his editorial roles highlight his commitment to maintaining high-quality research output 📚📝. Prof. Dr. Shrestha continues to play a crucial role in advancing engineering through his global outreach, fostering innovation, and contributing to the growth of academic knowledge in his field. 🌟💡

Publication Top Notes

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation

CorrectionSpecial Issue on Data Analysis and Artificial Intelligence for IoT

Correction to: A Proposed Waiting Time Algorithm for a Prediction and Prevention System of Traffic Accidents Using Smart Sensors (Electronics, (2022), 11, 11, (1765), 10.3390/electronics11111765)

Levy Flight-Based Improved Grey Wolf Optimization: A Solution for Various Engineering Problems

Leveraging metaheuristics with artificial intelligence for customer churn prediction in telecom industries

A Study on Improving M2M Network Security through Abnormal Traffic Control

Generative Adversarial Networks with Quantum Optimization Model for Mobile Edge Computing in IoT Big Data

 

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

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Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Ali Othman Albaji, Libyan Authority for Scientific Research, Libya

With a Bachelor’s in Electrical Engineering and a Master’s in Electronics & Telecommunications from Universiti Teknologi Malaysia, this accomplished professional has extensive experience in academia and industry. Currently an Assistant Professor at the Higher College of Science and Technology in Libya, they also lead CR Technology System in the MENA region. Their research interests include optical wireless technologies and machine learning applications in environmental monitoring. Fluent in Arabic and English, with a diploma in Italian, they are also the President of the Postgraduate Student Society at UTM. 📡🎓🌍✍️

Publication profile

google scholar

Academic Background 

With a diverse academic journey, the individual holds a Master’s in Public Management and Leadership from the London School of Economics (LSE), UK, completed in 2010. They further pursued a Master in Electronics and Telecommunications at the University Technology Malaysia from 2019 to 2023. Their foundational education includes a Bachelor’s degree in Electrical Engineering, specializing in General Communications, from the Civil Aviation Higher College in Tripoli, Libya, earned in 2007. Additionally, they completed a Diploma in the Italian language during the 2011/2012 academic year. 🎓📡

Experience

Dr. Ali Othman Albaji boasts a diverse work history across reputable organizations. He started as a Sales Advisor at Akida Company (LG) and ZTE/Telecom China, honing his expertise in the telecommunications field. His academic journey includes significant roles as an Assistant Professor and lecturer in Electronics and Telecommunications. In addition to his teaching, he has demonstrated leadership as the Chairman of CR Technology System (CRTS Group) and the President of the Postgraduate Student Society at Universiti Teknologi Malaysia. Dr. Albaji’s commitment to both academia and industry underscores his dedication to advancing technology and education. 📡🎓💼🌟

Main Hard Skills 

Dr. Albaji possesses a robust set of technical skills, including proficiency in CAD Design, MATLAB Simulation Analysis, Python, and data visualization tools like Tableau. His capabilities extend to qualitative and quantitative analysis, SCADA systems, and programming languages like Verilog and HTML. These skills enable him to tackle complex research problems and contribute innovatively to his field. 

Languages 

Fluent in Arabic and English, with an IELTS Band Score of 8.5, Dr. Albaji also has a very good command of Italian. This linguistic proficiency allows him to collaborate with international researchers and disseminate his work to a broader audience. 

Research focus

Ali Othman Albaji’s research focus centers on machine learning applications in environmental noise classification, emphasizing smart cities and mobile communications. His work includes developing algorithms for monitoring and classifying noise pollution using MATLAB, contributing to urban planning and public health. He has also explored traffic noise impacts on residential areas and mobile telecommunications in Libya. His diverse research interests extend to the design and implementation of communication systems, highlighting the integration of technology in environmental studies. Through these contributions, Albaji aims to enhance noise management and promote sustainable urban environments. 🌍📊🔊📡

Publication top notes

Investigation on Machine Learning Approaches for Environmental Noise Classifications

A Machine Learning for Environmental Noise Monitoring and Classification Using Matlab

Machine Learning for Environmental Noise Classification in Smart Cities

Designing the Global System for Mobile Communications GSM-900 Cellular Network up to the Nominal Cell Plan in Tripoli, Libya

Conclusion and Recommendations

A Review of Traffic Highway Noise Towards Residential Area

NOISE POLLUTION DATA REPORTING AND WAREHOUSING USING TABLEAU SOFTWARE

Designing and Implementing a Signed Multiplier Radix-2 Using Booth’s Algorithm