Anas Abdelrahman | Engineering and Technology | Best Researcher Award

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Dr. Anas Abdelrahman | Engineering and Technology | Best Researcher Award

Dr. Anas Abdelrahman | Engineering and Technology | Assistant Professor of Mechanical Engineering | Egypt

Dr. Anas Mohamed Abdelrahman is an accomplished Assistant Professor of Mechanical Engineering at Future University in Egypt and a Post-Doctoral Fellow at Zhejiang University China. He holds a PhD in Thermal Power Engineering from Huazhong University of Science and Technology, and his research spans advanced topics such as hydrogen energy, cryogenics, thermal management, machine learning applications, and renewable energy systems. With over 20 publications in prestigious international journals, Dr. Abdelrahman has made significant contributions to intelligent modeling and optimization in energy systems. He has been recognized with multiple academic excellence awards and serves as a peer reviewer for top-tier journals, reflecting his academic influence. His international academic engagements and mentorship of engineering students demonstrate a commitment to both research and education, positioning him as a forward-looking and impactful researcher in the global mechanical and energy engineering community.

Professional Profile 

Education  

Dr. Anas Mohamed Abdelrahman has a strong academic foundation in mechanical and thermal engineering. He is currently a post-doctoral fellow at both Zhejiang University (ZJU) and Hangzhou City University (HZCU) in China, focusing on energy and cryogenic research. He earned his PhD in Thermal Power Engineering from the Department of Refrigeration and Cryogenics at Huazhong University of Science and Technology (HUST), Wuhan, China, where his research emphasized artificial intelligence modeling and scaling analysis for thermoacoustic systems. Prior to that, he completed his MSc in Design and Production Engineering at Ain Shams University, Cairo, Egypt, with a thesis centered on intelligent techniques in the wire EDM process. He also holds a BSc in Mechanical Power Engineering from Ain Shams University, graduating with a “Very Good” grade and an “Excellent” graduation project on central air conditioning system design. His academic journey reflects a continuous pursuit of interdisciplinary innovation in energy and thermal systems.

Professional Experience

Dr. Anas Mohamed Abdelrahman has amassed extensive professional experience in both academia and industry. He has been a faculty member in the Mechanical Engineering Department at Future University in Egypt (FUE), where he currently serves as an Assistant Professor. In parallel, he is a post-doctoral research fellow at Zhejiang University (ZJU) and Hangzhou City University (HZCU) in China, contributing to advanced research in cryogenics and hydrogen energy. He also held a short-term instructional position at the Public Authority for Applied Education and Training (PAAET) . Earlier in his career, he worked as a Production Planning Engineer at Elsewedy Cables Company in Cairo, Egypt. Dr. Abdelrahman’s career demonstrates a solid blend of teaching, research, and industrial expertise, with a focus on applying advanced thermal and energy systems research to real-world engineering challenges.

Research Interest

Dr. Anas Mohamed Abdelrahman’s research interests are deeply rooted in the fields of energy, thermal sciences, and intelligent engineering systems. His work spans a wide range of topics, including refrigeration and cryogenics, hydrogen energy, energy storage systems, and multilayer insulation materials. He is particularly focused on the application of artificial intelligence and machine learning for intelligent modeling and optimization in thermal and fluid systems. His research also explores thermoacoustics, pulsating heat pipes, heat transfer enhancement, waste heat recovery, and fluid-solid interactions. Additionally, he is actively involved in renewable energy applications such as solar energy management, solar chimney systems, and thermal management of electronic devices. Through this multidisciplinary approach, Dr. Abdelrahman aims to develop innovative, energy-efficient, and sustainable engineering solutions for emerging global challenges.

Award and Honor

Dr. Anas Mohamed Abdelrahman has received numerous awards and honors in recognition of his academic excellence and research contributions. He was honored with the Post-Doctoral Talent Recognition Certificate by Zhejiang University in China and received several Outstanding Academic Achievement Awards during his MSc, PhD, and undergraduate studies from institutions including Future University in Egypt and Huazhong University of Science and Technology (HUST), China. His PhD work also earned him the Outstanding Academic Excellence Award in Scientific Research at HUST, along with an honorary recognition for international PhD graduates. Additionally, Dr. Abdelrahman has been acknowledged for his service as a peer reviewer for leading international journals such as Applied Energy, International Journal of Hydrogen Energy, Energy, The Journal of the Acoustical Society of America, and Thermal Science and Engineering Progress, receiving honorary certificates . These accolades reflect his dedication to advancing engineering science and his standing in the global research community.

Publications Top Noted

Prediction of output power with artificial neural network using extended datasets for Stirling engines
Year: 2020 | Cited by: 61

Prediction of oscillatory heat transfer coefficient for a thermoacoustic heat exchanger through artificial neural network technique
Year: 2018 | Cited by: 59

Single-objective optimization for stack unit of standing wave thermoacoustic refrigerator through fruit fly optimization algorithm
Year: 2019 | Cited by: 27

Prediction of acoustic wave parameters of thermoacoustic prime mover through artificial neural network technique: Practical approach for thermoacoustics
Year: 2018 | Cited by: 15

Prediction of cooling load for a standing wave thermoacoustic refrigerator through artificial neural network technique
Year: 2017 | Cited by: 15

Prediction of pressure evolution in non-venting self-pressurized liquid hydrogen tanks using artificial neural network approach
Year: 2024 | Cited by: 10

Single-objective Optimization for Stack Unit of Standing Wave Thermoacoustic Refrigerator through Particle Swarm Optimization Method
Year: 2019 | Cited by: 10

Experimental and theoretical study on the optimal placement of reflective shield in multilayer insulation systems
Year: 2025 | Cited by: 3

IMPROVED PREDICTIONS OF ONSET TEMPERATURE IN TWIN THERMOACOUSTIC HEAT ENGINE BY NEURAL NETWORK BASED CALIBRATED THERMOACOUSTIC MODEL
Year: 2019 | Cited by: 3

Solar Chimney Power Plants: A Mini Review
Year: 2022 | Cited by: 2

Conclusion

Dr. Anas Mohamed Abdelrahman is highly suitable for the Best Researcher Award, particularly in fields related to mechanical engineering, energy systems, cryogenics, and intelligent modeling.

Anuradha Choudhury | Computer Science and Artificial Intelligence | Women Researcher Award

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Ms. Anuradha Choudhury | Computer Science and Artificial Intelligence | Women Researcher Award

Student at OUTR, india

Anuradha Rani Choudhury is a dedicated and aspiring researcher currently pursuing her Master of Technology at OUTR, Bhubaneswar, with an impressive CGPA of 9.20. She holds a Bachelor’s degree in Technology from ITER, Bhubaneswar, and has demonstrated strong technical acumen through impactful projects in machine learning, including sentiment analysis and disease prediction models, both achieving high accuracy. With certifications in machine learning, web development, and Android development, she exhibits a strong foundation in diverse technological domains. Anuradha has actively participated in seminars and workshops, showcasing her commitment to continuous learning. Her proficiency in programming languages such as Python, Java, and C, along with web technologies, complements her research skills. Additionally, her involvement in extracurricular activities like sports, NCC, and student leadership reflects a well-rounded personality. While she is at an early stage in her research journey, Anuradha shows promising potential for future contributions to the field of technology and applied sciences.

Professional Profile 

🎓 Education of Anuradha Rani Choudhury

Anuradha Rani Choudhury has built a strong academic foundation in the field of technology and engineering. She is currently pursuing her Master of Technology (M.Tech) at Odisha University of Technology and Research (OUTR), Bhubaneswar, maintaining an excellent CGPA of 9.20 (2023–2025). She previously earned her Bachelor of Technology (B.Tech) from ITER, Bhubaneswar, graduating with a CGPA of 7.73 in 2022. Her earlier academic journey includes completing 12th grade (Science) from Stewart Science College, Cuttack under the CHSE Board, scoring 57.5%, and her 10th grade from D.A.V. Public School, Berhampur under the CBSE Board, where she achieved a commendable 83.6%. Her academic progression highlights her consistent dedication and growth in technical education.

💼 Professional Experience of Anuradha Rani Choudhury

Anuradha Rani Choudhury has gained valuable hands-on experience through academic projects and certified training programs in the fields of machine learning, data science, and software development. She successfully led a Sentiment Analysis project in 2024, where she implemented advanced models such as Naïve Bayes, Logistic Regression, SVM, and Neural Networks, achieving an outstanding . In 2023, she developed a Disease Prediction Model using patient physiological data, which delivered an impressive . Additionally, Anuradha has completed certification-based training in Machine Learning (Project Mantra), Web Development (Verzeo), and Android Development (Pixaflip Technologies). Her participation in workshops and seminars, along with her technical proficiency in languages like Python, Java, and SQL, further reflects her readiness for research and real-world problem-solving in the tech industry.

🔬 Research Interest of Anuradha Rani Choudhury

Anuradha Rani Choudhury’s research interests lie primarily in the dynamic fields of Machine Learning, Artificial Intelligence, and Data Science, with a strong inclination toward applying these technologies in healthcare and human-centered applications. She is passionate about exploring predictive modeling, sentiment analysis, and disease diagnosis systems that leverage advanced algorithms to generate actionable insights from complex data. Her academic projects reflect her enthusiasm for building intelligent systems capable of improving decision-making and automation. Anuradha is also interested in the integration of deep learning and neural networks to enhance model accuracy and efficiency. As she progresses in her academic and professional journey, she aims to contribute to impactful, real-world solutions through innovative and ethically grounded research in intelligent technologies.

🏅 Awards and Honors of Anuradha Rani Choudhury

Anuradha Rani Choudhury has been recognized for her diverse talents and active participation in both academic and extracurricular arenas. She earned the 2nd prize in poem writing at the Ganjam Kalaparishad in 2017, showcasing her creative expression and literary flair. In the same year, she also secured the 2nd prize in athletics at D.A.V. Public School, reflecting her athletic spirit and commitment to physical excellence. Additionally, she holds the prestigious NCC “A” Certificate (2013–2015), highlighting her discipline, leadership, and dedication to national service. These honors demonstrate her well-rounded personality, balancing academic rigor with artistic and physical achievements.

Conclusion

Anuradha Rani Choudhury is a promising emerging researcher with a solid academic background, project experience in machine learning, and proactive engagement in technical skill development. However, to be highly competitive for the Best Researcher Award, particularly at national or international levels, she would benefit from Publishing research papers. Involving in long-term, original research with measurable impact. Demonstrating broader research influence and leadership.

📚 Publications Top Noted

  1. Title: Real-time Face Mask Detection in Nuclear Power Plants: A Deep Learning Framework Using Hybrid CNN-MobileNetV2 Architecture
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra, S. Mohanty, S. Mishra
    Year: 2025
    Citation: 0
    Published In: Intelligent Computing Techniques and Applications, pp. 87–91

  2. Title: A Comparative Analysis of Deep Learning Techniques for Face Mask Detection System in Nuclear Power Plant
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
    Year: 2025
    Citation: 0
    Published In: 2025 10th International Conference on Signal Processing and Communication

  3. Title: Enhancing Lung Cancer Detection by Leveraging Machine Learning Algorithms
    Authors: A.R. Choudhury, S.R. Panda, A.K. Mishra, J. Routray
    Year: 2025
    Citation: 0
    Published In: 2025 10th International Conference on Signal Processing and Communication

  4. Title: Deep Learning Based Automated Lung Cancer Detection from CT Scan Leveraging Transfer Learning
    Authors: A.R. Choudhury, J. Rautray, P. Mishra, M. Kandpal, S.S. Dalai
    Year: 2025
    Citation: 0
    Published In: Procedia Computer Science, Volume 258, Pages 2748–2759

  5. Title: Face Mask Detection System for Safety Assurance in Nuclear Power Facilities from Harmful and Hazardous Substance Using Convolutional Neural Network and Image Processing
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
    Year: 2025
    Citation: 0
    Published In: International Journal of Computer Applications 975, 8887

 

 

 

 

 

 

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

 

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