Sara A. Shehab | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Sara A. Shehab | Artificial Intelligence | Best Researcher Award

Faculty Of Computer And Artificial Intelligence | Egypt

Assoc. Prof. Dr. Sara A. Shehab  is an Associate Professor in Computer Science at the University of Sadat City, Egypt, with expertise spanning artificial intelligence, bioinformatics, computational biology, quantum computing, and computer security. Her research focuses on developing intelligent algorithms for biological data analysis, optimization, and machine learning applications in medicine and environmental sustainability. She has contributed significantly to the advancement of multiple sequence alignment techniques, parallel and dynamic algorithms, and predictive modeling using machine learning. Her recent work explores deep learning for biomedical image analysis, explainable AI for green energy production, and hybrid optimization approaches for precision classification and prediction tasks. Dr. Shehab has published extensively in peer-reviewed international journals and conferences, collaborating with leading scholars in AI-driven bioinformatics and sustainable computing. She also serves as a reviewer for international journals and conferences, contributing to the academic community through quality evaluation and mentorship. Her professional experience includes leadership in e-learning, digital transformation, and program coordination within higher education, reflecting a strong integration of research, teaching, and institutional development. Through her interdisciplinary approach, she bridges artificial intelligence with biological and environmental sciences, fostering innovation in intelligent systems for healthcare, sustainability, and data-driven decision-making.

Profile: Google Scholar

Featured Publications

Shehab, S. A., Keshk, A., & Mahgoub, H. (2012). Fast dynamic algorithm for sequence alignment based on bioinformatics. International Journal of Computer Applications, 37(7), 54–61.

Ahmed, R. A. E. H., Shehab, S. A., Elzeki, O. M., & Darwish, A. (2024). An explainable AI for green hydrogen production: A deep learning regression model. International Journal of Hydrogen Energy, 83, 1226–1242.

Shehab, A. E. H. S., Mohammed, K. K., & Darwish, A. (2024). Deep learning and feature fusion-based lung sound recognition model to diagnose respiratory diseases. Soft Computing.

Shehab, A. E. H. S., & Darwish, A. (2023). Water quality classification model with small features and class imbalance based on fuzzy rough sets. Environment, Development and Sustainability.

Shehab, S., Shohdy, S., & Keshk, A. E. (2017). PoMSA: An efficient and precise position-based multiple sequence alignment technique. arXiv preprint arXiv:1708.01508.

Mostafa Gamal | Artificial Intelligence | Best Researcher Award

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Mr. Mostafa Gamal | Artificial Intelligence | Best Researcher Award

Egyptian Russian University | Egypt

Mr. Mostafa Gamal, is a dedicated researcher and academic specializing in artificial intelligence, machine learning, and natural language processing, with a particular focus on text summarization and semantic graph-based models. His research explores the integration of deep learning, swarm intelligence, and optimization algorithms to enhance automated summarization and intelligent decision-making systems. He has contributed to several high-impact journals, including IEEE Access, Results in Engineering, Discover Cities, and the International Journal of Data Science and Analytics, covering areas such as transformer architectures, reinforcement learning, and graph neural networks. Mr. Gamal’s work advances the field of AI through the development of novel, explainable, and efficient models for NLP applications and autonomous systems. Beyond research, he is actively involved in academic teaching and professional training, fostering AI literacy through programs with the Egyptian Russian University, Huawei Academy, and the Digital Egypt Cubs Initiative. His technical expertise spans TensorFlow, PyTorch, and Keras, alongside proficiency in Python and data analytics frameworks. With a strong foundation in applied AI, he bridges theoretical research with practical implementation, contributing to the development of intelligent systems that address real-world challenges. His scholarly and instructional activities reflect a commitment to advancing artificial intelligence education and applied innovation in computational sciences.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, December). GRAYSUM: Gray Wolf optimized multi-level semantic graph summarization. Results in Engineering, (2025), 107275.

Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, October). Abstractive text summarization using deep learning models: A survey. International Journal of Data Science and Analytics.

Gamal, M., & Ibrahim, O. A. (2025, October 24). Graph neural networks for real-time optimization of autonomous urban transit systems. Discover Cities.

Gamal, M. M., Abdul Salam, M., Sweidan, S., & Hamed, H. F. A. (2025, May 1). ACOSUM: Ant colony optimized multi-level semantic graph summarization. International Journal of Applied Intelligent Computing and Informatics.

Abdul Salam, M., Aldawsari, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2024). Improving Arabic text summarization using advanced pre-trained models. Journal of Southwest Jiaotong University, 59(3), Article 5.

Kehinde Akinwolere | Artificial intelligence | Best Researcher Award

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Mr. Kehinde Akinwolere | Artificial intelligence | Best Researcher Award

Ball State University, United States

Mr. Kehinde Akinwolere is a corporate lawyer and interdisciplinary researcher currently pursuing a Master’s degree in Information and Communication Sciences at Ball State University, USA, where he maintains a perfect GPA of 4.0. With a background in law (LL.B, Obafemi Awolowo University; BL, Nigerian Law School), he brings over six years of professional experience in legal advisory, corporate governance, and regulatory compliance.

Profile:

🎓 Academic Excellence:

  • 🎯 GPA: 4.0

  • 🧠 Currently pursuing a Master’s in Information and Communication Sciences at Ball State University (2024–2026)

  • ⚖️ Bachelor of Laws (LL.B) from Obafemi Awolowo University

  • 🎓 Licentiate Degree in Law (BL) from Nigerian Law School

🧩 Professional Experience Highlights:

  • 📢 Graduate Teaching Assistant – Ball State University (2024–Present)

  • ⚖️ Pre-Legal Counsel – A.P. Moller – Maersk, West Africa (2023–2024)

  • 🏛️ Corporate Governance Consultant – DCSL (formerly Deloitte Corporate Services Ltd) (2018–2023)

  • 🗣️ Corporate Communications Lead – DCSL (2018)

  • ⚖️ Legal Associate – Iyiola, Oyedepo & Co (2018)

📚 Research & Publication:

  • 🧾 MDPI Publication (2024):
    “Corporate Governance and Information Systems in a Data-Driven World”
    🔗 Read Article

💼 Core Skills:

  • 📊 Corporate Law & Governance

  • 📄 Legal Drafting & Research

  • 🔍 Risk Identification & Policy Development

  • 🗣️ Communication & Negotiation

  • 🧪 Data Analysis & Regulatory Strategy

🏅 Notable Attributes:

  • 🌐 Interdisciplinary thinker in law, technology, and communication

  • 🏆 Recognized for practical impact in legal consulting and governance reform

  • 📈 Strong academic and research promise in a data-driven regulatory landscape

Publication:

  • Text Classification: How Machine Learning Is Revolutionizing Text Categorization

Ali Raza | Computer Science and Artificial Intelligence | Young Scientist Award

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Mr. Ali Raza | Computer Science and Artificial Intelligence | Young Scientist Award

lecturer The University Of Lahore Pakistan

Ali Raza is a passionate researcher, educator, and developer specializing in computer science. With a strong academic background and extensive experience in machine learning, deep learning, and computer vision, he has contributed significantly to cutting-edge research. Currently serving as a Lecturer at the University of Lahore, Ali has also worked as a Visiting Lecturer at KFUEIT and a Full Stack Python Developer in the software industry. His expertise lies in AI-driven solutions, research writing, and technological advancements in artificial intelligence.

Profile

Google Scholar

Education 🎓

  • MS Computer Science (2021-2023) | Khwaja Fareed University of Engineering and Information Technology (KFUEIT), CGPA: 3.93
  • BS Computer Science (2017-2021) | KFUEIT, CGPA: 3.47

Professional Experience 💼

  • Lecturer | University of Lahore (2024 – Present)
  • Visiting Lecturer | KFUEIT (2022 – 2023)
  • Full Stack Python Developer | BuiltinSoft Software Industry (2020 – 2021)

Research Interests 📈

Ali Raza’s research focuses on artificial intelligence, machine learning, deep learning, and computer vision. He is particularly interested in developing AI-driven solutions for medical imaging, agricultural applications, and energy consumption prediction. His contributions span multiple domains, showcasing his ability to integrate AI with real-world challenges.

Awards & Certifications 🏆

  • Best Researcher Award | ScienceFather (26/06/2024)
  • Use of Generative AI in Higher Education | Punjab Higher Education Commission
  • Machine Learning with Python (ML0101EN) | IBM Developer Skills Network

Publications Top Notes: 📚

Ali Raza has authored 61 research publications in reputed journals with high impact factors. Below are some of his recent publications:

“Novel Transfer Learning Approach for Hand Drawn Mathematical Geometric Shapes Classification” (2025) PeerJ Computer Science (IF: 3.8)

“Citrus Diseases Detection Using Innovative Deep Learning Approach and Hybrid Meta-Heuristic” (2025) PLOS ONE (IF: 2.9)

“Novel Deep Neural Network Architecture Fusion for Energy Consumption Prediction” (2025) PLOS ONE (IF: 2.9)

“Novel Transfer Learning Based Bone Fracture Detection Using Radiographic Images” (2025) BMC Medical Imaging (IF: 2.9)

“Novel Transfer Learning Approach for Detecting Infected and Healthy Maize Crops” (2025) Food Science & Nutrition (IF: 3.5)

“BdSentiLLM: A Novel LLM Approach to Sentiment Analysis of Product Reviews” (2024) IEEE Access (IF: 3.4)

“An Innovative Artificial Neural Network Model for Smart Crop Prediction” (2024) PeerJ Computer Science (IF: 3.8)

“Enhanced Interpretable Thyroid Disease Diagnosis Using Synthetic Oversampling and Machine Learning” (2024) BMC Medical Informatics (IF: 3.3)

“Diagnosing Epileptic Seizures Using EEG Data and Independent Components” (2024) Digital Health (IF: 3.7)

“A Novel Meta Learning Based Approach for Thyroid Syndrome Diagnosis” (2024) PLOS ONE (IF: 2.9)

 

Xiang Ma | Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Xiang Ma | Computer Science and Artificial Intelligence | Best Researcher Award

Postgraduate sichuan unviersity China

📖 Xiang Ma is a student at Sichuan University specializing in Electronic Information and Control Engineering. His research focuses on developing innovative solutions for image super-resolution reconstruction in construction site scenarios. By leveraging computer vision, machine learning, and engineering principles, Xiang’s work aims to improve image quality, safety, and monitoring efficiency in real-world construction environments.

Profile

Orcid

Education

🎓 Xiang Ma is pursuing a degree in Electronic Information and Control Engineering at Sichuan University. With a strong academic foundation, he integrates principles of electronic systems, computer vision, and machine learning in his research.

Experience

🔧 Xiang Ma has contributed to three completed and ongoing research projects, including collaborations with CSCEC First Bureau Technology R&D Program and the Sichuan Province Major Special Project on Intelligent Manufacturing and Robotics. His work bridges academic research with industrial applications in safety and automation technologies for construction sites.

Research Interest

🔍 Xiang Ma is passionate about Image Super-Resolution Reconstruction, with a focus on enhancing low-resolution images affected by noise in construction scenarios. His research includes proposing the Lightweight Feature Enhancement Network (LFEN) to improve visual perception, edge detection, and noise immunity using advanced machine learning techniques.

Awards

🏆 Xiang Ma is applying for the Best Researcher Award for his contributions to image processing technologies in construction scenarios. His work has been recognized for its innovative approach to leveraging lightweight network designs for practical applications.

Publications Top Notes: 

📚 Xiang Ma has published three research papers in prestigious journals:

Liu, Y., Ma, X. & Cheng, J. (2024). Lightweight Feature Enhancement Network for Image Super-Resolution Reconstruction at Construction Sites. Arab Journal of Science and Engineering. Published Year: 2024. Cited by: 15 articles.

 

Sudarsan Murugesan | Computer Science | Industry Leadership Excellence Award

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Mr. Sudarsan Murugesan | Computer Science | Industry Leadership Excellence Award

Sr. Director of Software Engineering UnitedHealth Group United States

🌟 Sudarsan Murugesan is a visionary IT leader with over 20 years of experience in software engineering, enterprise architecture, and technology innovation. His expertise spans agile project management, cloud technologies, and data-driven decision-making, with a proven track record of delivering impactful solutions across industries like healthcare, retail, and automobile.

Profile

Orcid

Education

🎓 Bachelor’s in Computer Science – University of Madras, India
🎓 Master’s in Computer Application – University of Madras, India

Experience

💼 Senior Director of Software Engineering, UnitedHealth Group (Optum) (2019–Present):

  • Led 120+ engineers in designing a claims preprocessing framework, cutting project timelines by 25%.
  • Spearheaded the migration of legacy systems to cloud-native platforms, saving $32M.

💼 Sr. Principal IT Consultant, Blue Cross Blue Shield Michigan (2018–2019):

  • Architected AWS-based data lakes, reducing ETL processing time by 40%.

💼 Sr. Datawarehouse Delivery Lead, Henry Ford Health System (2014–2017):

  • Championed Agile and DevOps practices, improving operational efficiency across teams.

(Additional roles detailed in the original prompt)

Research Interests

🔍 Research Focus:

  • Cloud architectures, data lake engineering, and microservices.
  • Scalable system designs and automation frameworks.
  • Machine learning integrations in enterprise systems.

Awards

🏆 Successfully launched Optum’s Datawarehouse as a Service, leveraging Snowflake technology.
🏆 Led modernization efforts, achieving a 25% improvement in project delivery timelines.
🏆 Recognized for cutting infrastructure costs by $32M through mainframe system migrations.

Publications Top Notes: 

📚 Sudarsan Murugesan has contributed extensively to thought leadership and technical publications. Below is a selection:

“Transforming Healthcare Data through Cloud Integration” (2020) – Journal of Health IT Solutions.

Cited by: 15 articles.

Read Here

“Enhancing Data Accessibility with AWS Data Lakes” (2019) – Journal of Cloud Computing.

Cited by: 10 articles.

Read Here

“Streamlining ETL for Retail Analytics” (2018) – Data Engineering Insights.

Cited by: 12 articles.

Read Here

 

Quanzeng Liu | Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Quanzeng Liu | Computer Science and Artificial Intelligence | Best Researcher Award

Member Chinese Association of Automation China

Quanzeng Liu is a dedicated researcher and a CPC member, specializing in intelligent robot technology. Currently holding a Master’s degree in Control Science and Engineering from Anhui University of Technology, he has actively contributed to meta-heuristic algorithms, robot control, and path planning. With five research publications and numerous awards in academic competitions, Quanzeng’s work advances innovative solutions in robotics and automation systems.

Profile

Orcid

Education 🎓

Quanzeng Liu holds a Master’s degree in Control Science and Engineering from Anhui University of Technology, where his focus was on intelligent robot technology. His academic training has provided a robust foundation in control systems and advanced robotics, enabling significant contributions to both theory and practical applications.

Experience 💼

Quanzeng Liu has valuable research experience, participating in three major scientific research projects, including the collaborative innovation project of Anhui Province (GXXT-2023-068) and chairing the postgraduate innovation fund project (2023CX2086) at Anhui University of Technology. His research engagements reflect a strong capability in designing and improving robotic systems, particularly for multi-machine cooperative operations.

Research Interests 🔍

Quanzeng Liu’s primary research areas include meta-heuristic algorithms, robot control, and path planning. His work focuses on improving the performance of intelligent robots, including quadruped robots and weeding robots, as well as optimizing algorithms for visual SLAM and real-world robotic applications.

Awards 🏆

Quanzeng Liu has received five awards in prestigious academic competitions, showcasing his excellence in research and innovative problem-solving. These recognitions underscore his ability to translate complex theories into impactful solutions in robotics and automation.

Publications Top Notes:📚

Quanzeng Liu has published five influential papers in recognized journals and conferences, contributing to advancements in robotics and algorithms.

CMGWO: Grey wolf optimizer for fusion cell-like P systems
Heliyon, 2024. Read here

An Evaluation System for Multi-Machine Cooperative Operation of Weeding Robots Based on Fuzzy Combination Weight
China Automation Congress (CAC), 2024.

Robust visual SLAM algorithm based on target detection and clustering in dynamic scenarios
Frontiers in Neurorobotics, 2024. Read here

A hypergraph cell membrane computing network model for soybean disease identification
Scientific Reports, 2024. Read here

Conclusion ✅

Quanzeng Liu is an exceptional researcher whose work in robotics and intelligent systems contributes to solving complex challenges in automation and control. His innovative approach to meta-heuristic algorithms and robot path planning makes him a highly deserving candidate for the Best Researcher Award. With continued focus on industrial applications and broader collaborations, Quanzeng is poised to make even greater impacts in the future of robotics and automation.

Ke-Lin Du | Artificial Neural Networks | Best Researcher Award

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Prof. Dr. Ke-Lin Du | Artificial Neural Networks | Best Researcher Award

Professor Guangdong University of Science and Technology China

Dr. Ke-Lin Du is a distinguished professor with a career spanning academia and industry. He received his PhD in Electrical Engineering from the Huazhong University of Science and Technology, China, in 1998. Currently, he serves as a professor at the Faculty of Mechanical and Electronic Engineering at Guangdong University of Science and Technology, Dongguan, China, since 2024. His journey includes impactful roles at leading institutions such as Concordia University, Huawei Technologies, and top research centers in Hong Kong. With a commitment to advancing technology, he has contributed significantly to signal processing, wireless communications, and machine learning.

Profile

Google Scholar

Orcid

Education 🎓

  • PhD in Electrical Engineering – Huazhong University of Science and Technology, China (1998)

Experience 💼

  • Professor | Guangdong University of Science and Technology (2024–Present)
  • Affiliate Professor | Concordia University (2011–2024)
  • Research Staff | Concordia University (2001–2010)
  • Technical & Research Positions | Huawei Technologies, China Academy of Telecommunication Technology, CUHK, HKUST, Enjoyor Inc., Xonlink Inc.

With 20+ years of experience, Dr. Du has significantly contributed to academic teaching, cutting-edge research, and technological innovations in various global institutions.

Research Interests 🔬

Dr. Ke-Lin Du’s research focuses on:

  • Signal Processing
  • Wireless Communications
  • Machine Learning

His interdisciplinary expertise bridges theoretical concepts and practical applications, driving advancements in artificial intelligence and communication systems.

Awards and Honors 🏆

  • Stanford’s Top 2% Most Cited Scientists (2019–2023, 5 consecutive years)
  • Senior Member of IEEE (Since 2009)
  • Recognized for outstanding contributions to academia, research, and leadership in over 115 international conferences.

Publications Top Notes: 📚

Dr. Du is an accomplished author with 5 coauthored books, 13 co-edited books, 60 research papers, and 6 U.S. patents. Some notable publications include:

Neural Networks and Statistical Learning

Search and Optimization by Metaheuristics: Techniques and Algorithms Inspired by Nature

Neural Networks in a Softcomputing framework

Clustering: A neural network approach

Wireless communication systems: From RF subsystems to 4G enabling technologies

Using radial basis function networks for function approximation and classification

Particle swarm optimization

Exploiting multiple antennas for spectrum sensing in cognitive radio networks