Arifur Rahman | Machine Learning | Best Researcher Award

Published on by Network Awards

Arifur Rahman | Machine Learning | Best Researcher Award

Mr. Arifur Rahman, NAGAD Digital Financial Service, Bangladesh

Arifur Rahman ๐ŸŽ“ is a passionate researcher and software engineer from Bangladesh ๐Ÿ‡ง๐Ÿ‡ฉ, specializing in Machine Learning ๐Ÿค–, Deep Learning ๐Ÿง , NLP ๐Ÿ“š, and Bioinformatics ๐Ÿงฌ. A graduate of KUET in Computer Science and Engineering ๐Ÿ’ป, he has excelled in both academia and industry. Currently, he serves as a Full Stack Developer ๐Ÿง‘โ€๐Ÿ’ป at NAGAD Digital Financial Service, contributing to innovative supply chain projects. Arifur is also an active researcher with several IEEE and Elsevier publications ๐Ÿ“, and has earned recognition in programming contests ๐Ÿ†. His dedication to applied AI and system development showcases a unique blend of technical and research excellence ๐Ÿš€.

๐ŸŒย Professional Profile

Google Scholar

๐ŸŽ“ Education

  • ๐ŸŽ“ B.Sc. in Computer Science and Engineering, KUET (2018 โ€“ 2023)

    • ๐Ÿ“Š CGPA: 3.35/4.00; Final Two Years CGPA: 3.73/4.00

  • ๐Ÿซ Noakhali Govt. College (2015 โ€“ 2017)

    • ๐ŸŒŸ GPA: 5.00/5.00 (Cumilla Board Scholarship Winner)

๐Ÿ‘จโ€๐Ÿ’ผ Experience

  • ๐Ÿง‘โ€๐Ÿ’ป Software Engineer, NAGAD Digital Financial Service (Feb 2024 โ€“ Present)

    • ๐Ÿ’ผ Full Stack Developer in PRISM (Supply Chain Management) using Flutter, Java Spring Boot, PHP

  • ๐Ÿ”ฌ Research Engineer (NLP), AIMS Lab, United International University (Oct 2023 โ€“ Feb 2024)

    • ๐Ÿ“š Worked on Recommender Systems and published in IEEE Access

  • ๐Ÿ‘จโ€๐Ÿ’ป Software Engineer, Nazihar IT Solution Ltd. (May 2023 โ€“ Sep 2023)

    • ๐Ÿ’ป Developed subroutines using Temenos Java Framework for banking solutions

๐Ÿ† Suitability for Best Researcher Award

Mr. Arifur Rahman is an exceptional candidate for the Best Researcher Award, demonstrating strong potential and proven excellence in research and innovation across emerging domains such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Health Informatics, and Biomedical Engineering. His impactful research, hands-on development skills, and academic contributions distinguish him as a rising leader in computational science and applied AI.

๐Ÿ”น Professional Developmentย 

Arifur Rahman ๐Ÿš€ is actively involved in both industry-driven software engineering and cutting-edge academic research ๐Ÿ“–. His journey has been marked by continuous professional growth, serving in roles that merge development and innovation ๐Ÿ’ผ. At NAGAD, he contributes as a Full Stack Developer ๐ŸŒ, while his time at AIMS Lab sharpened his NLP and recommender system expertise ๐Ÿง . He has also contributed as a reviewer in IEEE conferences ๐Ÿ“‘, showcasing his engagement with the global research community. Arifurโ€™s hands-on experience with technologies like Flutter, Java Spring Boot, ReactJS, and blockchain ๐Ÿ”— highlights his dynamic skill set and commitment to excellence โญ.

๐Ÿ” Research Focus

Arifur Rahmanโ€™s research focuses on a diverse range of AI-powered technologies ๐Ÿง , with core interests in Machine Learning, Deep Learning, and Natural Language Processing ๐Ÿค–๐Ÿ“š. His work explores real-world applications such as health informatics ๐Ÿฅ, bioinformatics ๐Ÿงฌ, fake news detection, and blockchain security ๐Ÿ”. Through his IEEE and Elsevier publications, he has addressed critical problems in diabetic retinopathy diagnosis, DNA sequence classification, and higher education recommendation systems ๐ŸŽ“. His blend of theoretical innovation and practical solutions ensures his research contributes to both scientific progress and societal impact ๐ŸŒ.

๐Ÿ… Awards and Honors

  • ๐ŸŽ–๏ธ Deanโ€™s List Award at KUET for outstanding academic performance (2019โ€“2020)

  • ๐Ÿฅ‡ Intra-KUET Programming Contest 2021 โ€“ 3rd Place ๐Ÿง ๐Ÿ’ก

  • ๐Ÿฅˆ Intra-KUET Programming Contest 2019 โ€“ 6th Place ๐Ÿง 

  • ๐Ÿฅ‰ Divine IT Qualification Round โ€“ Rank 10 (Nov 2023) ๐Ÿ’ป

  • ๐Ÿ† TechnoNext Technical Coding Test 2023 (Fresher) โ€“ Rank 7 ๐Ÿ”ข

๐Ÿ“Š Publication Top Notes

  1. Recommender system in academic choices of higher education โ€“ IEEE Access (2024) ๐Ÿ“š5 ๐ŸŽ“๐Ÿค–
  2. Advancements in breast cancer diagnosis… with PCA, VIF โ€“ 6th Int. Conf. on Electrical Engineering and Info (2024) ๐Ÿ“š2 ๐Ÿงฌ๐Ÿฉบ๐Ÿ“Š
  3. Optimizing SMS Spam Detection… Voting Ensembles & Bi-LSTM โ€“ 5th Int. Conf. on Data Intelligence and Cognitive (2024) ๐Ÿ“š1 ๐Ÿ“ฑ๐Ÿ“ฉ๐Ÿง 
  4. Cracking the Genetic Codes: DNA Sequence Classification… โ€“ Int. Conf. on Advances in Computing, Communication (2024) ๐Ÿ“š1 ๐Ÿงฌ๐Ÿงช๐Ÿง 
  5. Secure Land Purchasing using… Multi-Party Skyline Queries โ€“ 26th Int. Conf. on Computer and Info Tech (2023) ๐Ÿ“š1 ๐ŸŒ๐Ÿ ๐Ÿ”
  6. Fake News Detection… Soft and Hard Voting Ensemble โ€“ Procedia Computer Science (2025) ๐Ÿ“šโ€“ ๐Ÿ“ฐโŒ๐Ÿ—ณ๏ธ

Prof. Pinghui Wu | Technology | Best Researcher Award

Published on by Network Awards

Prof. Pinghui Wu | Technology | Best Researcher Award

Prof. Pinghui Wu | Technology – Division Chief of Scientific Research at Quanzhou Normal University, China

Prof. Wu Pinghui, a distinguished academic from Quanzhou Normal University, has made remarkable contributions to the fields of advanced optics, materials science, and thermal engineering. With a robust portfolio of research, Wuโ€™s work reflects a passion for innovation and scientific exploration, particularly in areas like metamaterials and solar energy technologies. Known for a collaborative approach, Wu has worked with numerous international researchers, driving forward impactful studies that influence both theoretical and applied sciences.

Profile:

Orcid | Scopus | Google Scholar

Education:

Prof. Wu Pinghui pursued advanced studies in materials science and optical engineering, laying a strong foundation for a career marked by academic excellence and groundbreaking research. The educational journey involved rigorous training in both theoretical principles and practical applications, fostering expertise in cutting-edge technologies. This academic background has been pivotal in shaping Wuโ€™s approach to complex scientific challenges and interdisciplinary collaborations. ๐ŸŽ“

Experience:

With years of dedicated academic service, Wu has held prominent research and teaching positions at Quanzhou Normal University. This experience includes mentoring graduate students, leading research projects, and contributing to curriculum development in scientific disciplines. Wuโ€™s role extends beyond academia, with active participation in international conferences and collaborative research initiatives that span across institutions and countries. ๐ŸŒ

Research Interests:

Wuโ€™s research interests are diverse, encompassing optical materials, thermal energy systems, and metamaterial-based devices. Key areas include the development of ultra-broadband solar absorbers, terahertz smart devices, and advanced optical reinforcement materials. Wuโ€™s work is characterized by a focus on sustainability, energy efficiency, and the application of novel materials to solve real-world technological problems. ๐Ÿ”ฌ

Awards:

While specific awards are not detailed, Wuโ€™s academic achievements, high citation count, and influential publications underscore a career recognized for excellence. The impact of Wuโ€™s research is reflected in the widespread adoption of scientific findings and contributions to the academic community. ๐Ÿ†

Selected Publications:

  1. “Highly Localized Linear Array of Optical Rings with Multiple Tunable Degrees of Freedom” (2025) – Optics Communications โœจ
  2. “Highly Efficient Color Tuning of Lithium Niobate Nanostructures on Flexible Substrate” (2025) – Materials ๐ŸŒˆ
  3. “Ultra-Broadband Solar Absorber and Near-Perfect Thermal Emitter Based on Columnar Titanium Micro-Structure” (2025) – Applied Thermal Engineering โ˜€๏ธ
  4. “Bi-Directional Metamaterial Perfect Absorber Based on Gold Grating and TiOโ‚‚-InAs Normal Hexagonal Pattern Film” (2025) – Solar Energy Materials and Solar Cells โšก
  5. “Thermal Radiation Analysis of a Broadband Solar Energy-Capturing Absorber Using Ti and GaAs” (2025) – Dalton Transactions ๐ŸŒž
  6. “Ultra-Broadband Absorber and Near-Perfect Thermal Emitter Based on Multi-Layered Grating Structure Design” (2025) – Energy ๐Ÿ”ฅ
  7. “Terahertz Smart Devices Based on Phase Change Material VOโ‚‚ and Metamaterial Graphene” (2025) – Optics and Laser Technology ๐ŸŒ

Cited By: Over 6,610 citations, reflecting the widespread influence and recognition of these works. ๐Ÿ“š

Conclusion:

Prof. Wu Pinghuiโ€™s academic journey exemplifies a commitment to scientific excellence and innovation. The combination of extensive research output, impactful publications, and interdisciplinary collaborations highlights a career dedicated to advancing knowledge and technology. Wuโ€™s contributions not only enrich the academic community but also inspire future generations of researchers. This nomination for the Best Researcher Award is a testament to the profound impact Wu has made in the scientific world. ๐ŸŒŸ

Dr. Ryszard ฤ†wiertniak | Artificial Intelligence | Best Researcher Award

Published on by Network Awards

Dr. Ryszard ฤ†wiertniak | Artificial Intelligence | Best Researcher Award

Dr. Ryszard ฤ†wiertniak, Krakow University of Economics, Poland

Dr. Ryszard ฤ†wiertniak is an accomplished expert in project management, specializing in agile methodologies, Design Thinking, and AI-driven innovation. He holds a PhD in Management and Quality Sciences from the University of Economics in Krakow and has a strong academic and professional background in administration, management, and electrical engineering. With extensive experience in research and teaching, he has contributed to the fields of digital transformation, e-learning, and Industry 4.0. As an IBM Design Thinking mentor and Early Warning Europe ambassador, he helps businesses implement cutting-edge solutions. His work spans academia, consulting, and applied research in AI and business process optimization.

๐ŸŒย Professional Profile:

Orcid

Google Scholar

๐Ÿ† Suitability for Best Researcher Awardย 

Dr. Ryszard ฤ†wiertniak’s pioneering research in AI-driven project management, digital transformation, and innovation management makes him an outstanding candidate for the Best Researcher Award. His involvement in Erasmus+ projects, contributions to Industry 4.0, and mentorship in agile methodologies showcase his impact on academia and industry. His expertise in AI-based decision-making, personalized education, and digital business models has transformed organizational processes. With numerous peer-reviewed publications, a book, and a grant-winning project, his research advances the future of smart business ecosystems. His leadership in AI-powered business solutions and educational innovations solidifies his reputation as a top researcher in the field.

๐ŸŽ“ Educationย 

Dr. Ryszard ฤ†wiertniak earned his PhD in Management and Quality Sciences from the University of Economics in Krakow (2019), focusing on innovation management. He also holds a Masterโ€™s degree in Administration and Management from the University of Warsaw (1994). In addition, he has a background in electrical engineering, equipping him with a multidisciplinary approach to research. His academic journey reflects a deep commitment to combining management principles with technology, particularly in AI applications, e-learning, and agile business strategies. His education has laid the foundation for his expertise in digital transformation, business innovation, and advanced project management methodologies.

๐Ÿ’ผ Professional Experienceย 

Dr. ฤ†wiertniak currently serves as an academic teacher at Krakow University of Economics, specializing in technology and product ecology. Previously, he was the Rectorโ€™s Representative for Quality of Education and E-learning at the College of Economics and Computer Science (2020โ€“2024). His role in the Early Warning Europe initiative highlights his expertise in digital business transformation. He also contributes to the Erasmus+ program, working on AI-powered educational solutions. As an IBM Design Thinking mentor, he facilitates agile project implementation. His professional engagements bridge academia and industry, driving innovation, AI adoption, and digital business strategies in various sectors.

๐Ÿ… Awards and Honorsย 

๐Ÿ”น Early Warning Europe Ambassador (2021โ€“Present) โ€“ Recognized for supporting digital business transformation.
๐Ÿ”น Erasmus+ Research Grant Recipient โ€“ Contributed to AI-driven education models.
๐Ÿ”น Ministerial Research Grant Winner (2021) โ€“ Awarded funding for advancing e-learning and digital education techniques.
๐Ÿ”น IBM Design Thinking Mentor โ€“ Certified expert in guiding agile and innovative project execution.
๐Ÿ”น Industry 4.0 & AI Innovation Contributor โ€“ Acknowledged for pioneering work in integrating AI with project management and digital marketing.
๐Ÿ”น Invited Researcher at THWS Business School (2024) โ€“ Recognized for leadership in AI-based digital transformation.

His contributions to AI, project management, and education technology have earned him national and international acclaim.

๐Ÿ”ฌ Research Focus

Dr. ฤ†wiertniak’s research spans AI-driven project management, innovation strategies, digital transformation, and e-learning technologies. He explores Industry 4.0 applications, AI-based decision-making, and agile methodologies to optimize business processes. His focus on digital business models, social media analytics, and e-commerce strategies has redefined marketing and management practices. Through Design Thinking and AI integration, he enhances project execution efficiency. His research also covers personalized education using AI, ensuring smarter, data-driven learning environments. As an expert in AI-powered business solutions, he contributes to making organizations more adaptable and efficient in an era of rapid technological advancements.

๐Ÿ“Šย Publication Top Notes:

  1. Rola potencjaล‚u innowacyjnego w modelach biznesowych nowoczesnych organizacji โ€“ prรณba oceny

    • Citations: 11
    • Year: 2015

  2. Zarzฤ…dzanie portfelem projektรณw w organizacji: Koncepcje i kierunki badaล„

    • Citations: 4
    • Year: 2018

  1. Addressing students’ perceived value with the virtual university concept

    • Citations: 3
    • Year: 2022

  2. Ksztaล‚towanie portfela projektรณw w zarzฤ…dzaniu innowacjami

    • Citations: 2
    • Year: 2018

  1. The concept of project evaluation in the implementation of innovation

    • Citations: 1
    • Year: 2020

 

 

Dr. Yingbin Wang | Artificial Intelligence | Best Researcher Award

Published on by Network Awards

Dr. Yingbin Wang | Artificial Intelligence | Best Researcher Award

Dr. Yingbin Wang, Xi’an Institute of Space Radio Technolog, China

Dr. Yingbin Wang is a leading researcher in space microwave communication, detection, and AI-driven signal processing. He earned his Ph.D. in Electronic Science and Technology from Xidian University in 2022 and currently serves as a Senior Engineer at the National Key Laboratory of Science and Technology on Space Microwave at the Xiโ€™an Institute of Space Radio Technology. His research spans Integrated Sensing and Communication (ISAC), deep learning, and anti-jamming satellite systems. With over ten high-impact publications and contributions to national-level R&D projects, Dr. Wang is shaping the future of space-based communication and intelligent sensing. ๐Ÿš€๐Ÿ“ก

๐ŸŒย Professional Profile:

Google Scholar

๐Ÿ† Suitability for the Best Researcher Award

Dr. Yingbin Wang is a highly qualified candidate for the Best Researcher Award, given his significant contributions to space microwave communication and AI-powered signal processing. His expertise in satellite-terrestrial integration, space-based radar target detection, and anti-jamming satellite systems plays a crucial role in advancing global space technology. With publications in top-tier IEEE journals, participation in national R&D projects, and contributions to cutting-edge ISAC applications, Dr. Wang is at the forefront of next-generation communication research. His work in AI-driven remote sensing is revolutionizing the field, making him a distinguished and deserving nominee. ๐Ÿ†๐Ÿš€

๐ŸŽ“ Education

Dr. Yingbin Wang pursued his entire higher education at Xidian University, China, a prestigious institution in electronic engineering and space communication. He obtained his Ph.D. in Electronic Science and Technology in June 2022, focusing on advanced space microwave systems and AI-enhanced signal processing. His doctoral research contributed to improving satellite communication resilience, radar detection, and deep learning applications in space technologies. Throughout his academic journey, he combined hardware engineering with AI-driven software models, enabling breakthroughs in integrated satellite-terrestrial communication. His strong foundation in electromagnetic waves, remote sensing, and computational intelligence defines his research excellence. ๐ŸŽ“๐Ÿ“ก๐Ÿ”ฌ

๐Ÿ’ผ Experienceย 

Dr. Yingbin Wang is a Senior Engineer at the National Key Laboratory of Science and Technology on Space Microwave, Xiโ€™an Institute of Space Radio Technology. His role involves leading research in space microwave communication, detection, and AI-driven signal optimization. He has contributed to major national R&D projects, including space-based radar target detection, anti-jamming satellite communication, and integrated sensing for satellite-terrestrial networks. His work on AI-based signal processing and deep learning models has significantly enhanced real-time space communication efficiency. His expertise in high-frequency electromagnetic applications and AI-powered satellite technology is instrumental in shaping the future of space communications. ๐Ÿš€๐Ÿ“ถ

๐Ÿ… Awards & Honorsย 

Dr. Yingbin Wang has received multiple recognitions for his contributions to space communication and AI-driven signal processing. His research in anti-jamming satellite networks has been awarded national-level research funding. He has received Best Paper Awards at leading IEEE conferences on signal processing and remote sensing. Additionally, his contributions to integrated satellite-terrestrial communication have been recognized by the National Science and Technology Innovation Program. As a reviewer for top IEEE journals, he actively contributes to the scientific community. His pioneering work in AI-enhanced space sensing continues to push the boundaries of satellite communication technologies. ๐Ÿ†๐Ÿ“ก

๐Ÿ”ฌ Research Focusย 

Dr. Yingbin Wangโ€™s research spans Artificial Intelligence, communication, deep learning, and signal processing, with a strong emphasis on space microwave communication and detection. His work explores AI-driven radar target detection, anti-jamming satellite communication, and integrated sensing and communication (ISAC) systems. He develops machine learning models for real-time adaptive signal processing, enhancing satellite-terrestrial connectivity. His studies in neural network-driven space communication systems optimize data transmission efficiency in complex space environments. His research is critical for next-generation deep-space exploration, smart communication networks, and high-performance microwave technology, ensuring global connectivity and security in aerospace applications. ๐Ÿš€๐Ÿ“ก๐Ÿ›ฐ๏ธ

๐Ÿ“–ย Publication Top Notes

  1. SPB-Net: A Deep Network for SAR Imaging and Despeckling with Downsampled Data
    • Journal: IEEE Transactions on Geoscience and Remote Sensing
    • Publication Year: 2020
    • Citations: 27
  2. Lq-SPB-Net: A Real-Time Deep Network for SAR Imaging and Despeckling
    • Journal: IEEE Transactions on Geoscience and Remote Sensing
    • Publication Year: 2021
    • Citations: 8
  1. Multi-Scale and Single-Scale Fully Convolutional Networks for Sound Event Detection
    • Journal: Neurocomputing
    • Publication Year: 2021
    • Citations: 18
  2. MSFF-Net: Multi-Scale Feature Fusing Networks with Dilated Mixed Convolution and Cascaded Parallel Framework for Sound Event Detection
    • Journal: Digital Signal Processing
    • Publication Year: 2022
    • Citations: 12
  1. A Convex Optimization Algorithm for Compressed Sensing in a Complex Domain: The Complex-Valued Split Bregman Method
    • Journal: Sensors
    • Publication Year: 2019
    • Citations: 13

 

Prof. Dr. Xin Wang | Distributed AI | Best Researcher Award

Published on by Network Awards

Prof. Dr. Xin Wang | Distributed AI | Best Researcher Award

Prof. Dr. Xin Wang, Qilu University of Technology, China

Prof. Dr. Xin Wang is a distinguished scholar in Distributed AIย and Federated Learning, currently serving as a Professor at Shandong Computer Science Center, Qilu University of Technology. With a Ph.D. in Control Science and Engineering from Zhejiang University, he has contributed significantly to AI Security, Privacy, and LLM Security. Dr. Wang has led multiple national research projects and received prestigious honors, including the Taishan Scholars Award and the Shandong Provincial Science and Technology Progress Award. His work integrates AI with secure computing, enhancing privacy protection and optimization in collaborative learning systems.

๐ŸŒย Professional Profile:

Google Scholar

๐Ÿ† Suitability for Awardย 

Dr. Xin Wangโ€™s outstanding contributions to Distributed AI, Federated Learning, and AI Security make him a strong candidate for the Best Researcher Award. As a leader in AI-driven security frameworks, he has spearheaded national-level projects focusing on privacy-preserving AI and secure learning models. His research bridges theory with practical applications, enhancing security in multi-agent and industrial IoT systems. Recognized for his high-impact publications and award-winning research, Dr. Wangโ€™s innovations in cryptographic function identification and UAV data collection optimization demonstrate exceptional originality and real-world relevance, solidifying his place as a leader in computational intelligence and AI security.

๐ŸŽ“ Educationย 

  • Ph.D. in Control Science and Engineering (2015-2020) โ€“ Zhejiang University, supervised by Prof. Peng Cheng & Prof. Jiming Chen, specializing in AI Security and Distributed Intelligence.
  • Visiting Scholar in Information Security (2018-2019) โ€“ Tokyo Institute of Technology, mentored by Prof. Hideaki Ishii, focusing on cryptographic vulnerabilities and federated learning security.

His multidisciplinary training across AI, security, and automation has positioned him at the forefront of cutting-edge computational research.

๐Ÿ’ผ Experienceย 

  • Professor (2024โ€“Present) โ€“ Shandong Computer Science Center, Qilu University of Technology.
  • Associate Professor (2020โ€“2024) โ€“ Shandong Computer Science Center, leading research on privacy protection in collaborative AI.
  • Project PI in National Natural Science Foundation of China (2025-2027) โ€“ Developing privacy-preserving defense mechanisms for federated learning.
  • Project PI in National Key Research and Development Program (2021-2024) โ€“ Developing AI-driven meta-services for cloud-based industrial manufacturing.
  • Visiting Scholar (2018-2019) โ€“ Tokyo Institute of Technology, conducting security research on cryptographic vulnerabilities in multi-agent IoT systems.

๐Ÿ… Awards and Honorsย 

  • Taishan Scholars Award (2024) ๐Ÿ… โ€“ Recognized for research excellence in AI security and distributed systems.
  • Leader of Youth Innovation Team (2022) ๐Ÿš€ โ€“ Acknowledged for driving innovation in Shandong Higher Education Institutions.
  • Second Prize, Shandong Provincial Science and Technology Progress Award (2022) ๐Ÿ† โ€“ Contributions to federated learning and privacy-preserving AI.
  • Best Paper Award, CCSICCโ€™21 ๐Ÿ“„ โ€“ Vulnerability Analysis for IoT Devices in Multi-Agent Systems.
  • Best Paper Award, ICAUSโ€™24 โœˆ๏ธ โ€“ Optimized Data Collection for UAVs in Industrial IoT Environments.

๐Ÿ”ฌ Research Focusย 

Dr. Wang specializes in Distributed AI, Federated Learning, and AI Security & Privacy. His research integrates cryptographic techniques, optimization algorithms, and adversarial defenses to improve the security of collaborative learning models. He has pioneered LLM security frameworks to safeguard against data leakage and adversarial attacks. His work extends into privacy-preserving AI for multi-agent IoT systems and UAV data collection efficiency. Through national projects, he has developed secure meta-services for cloud computing, advancing the field of intelligent automation and resilient AI architectures for real-world deployment in cyber-physical systems and industrial environments.

๐Ÿ“Š Publication Top notes:

  • Title: Privacy-Preserving Distributed Machine Learning via Local Randomization and ADMM Perturbation
    • Year: 2020
    • Citations: 61
  • Title: Privacy-Preserving Collaborative Computing: Heterogeneous Privacy Guarantee and Efficient Incentive Mechanism
    • Year: 2018
    • Citations: 49
  • Title: Differentially Private Maximum Consensus: Design, Analysis and Impossibility Result
    • Year: 2018
    • Citations: 26
  • Title: Dynamic Privacy-Aware Collaborative Schemes for Average Computation: A Multi-Time Reporting Case
    • Year: 2021
    • Citations: 18
  • Title: Leveraging UAV-RIS Reflects to Improve the Security Performance of Wireless Network Systems
    • Year: 2023
    • Citations: 17

 

Dr. Mohamed Elhamahmy | AI – Machine Learning | Best Researcher Award

Published on by Network Awards

Dr. Mohamed Elhamahmy | AI – Machine Learning | Best Researcher Award

Dr. Mohamed Elhamahmy, National Telecommunications Regulatory Authority, Egypt,

Dr. Mohamed Ezzat Elhamahmy is a Senior Expert in Cybersecurity at the National Telecommunications Regulatory Authority in Cairo and serves on the advisory board at the College of Computers and Information Technology, Arab Academy for Science, Technology and Maritime Transport. He holds a Bachelor’s in Electrical Engineering from the Military Technical College, a Masterโ€™s in Systems and Computer Engineering from Al-Azhar University, a Ph.D. in Information Technology from Cairo University, and a Professional Masterโ€™s in Political Studies and Security. Dr. Elhamahmy has extensive experience in IT and cybersecurity, having managed the Information Systems Department of the Armed Forces and established a dedicated cybersecurity unit. His expertise includes incident handling, network security, and strategic planning, supported by certifications such as CEH and CISSP. His notable contributions include advancing cybersecurity practices and education in the region.

Professional Profile๐ŸŒ

Orcid
Scopus

Educational Background ๐ŸŽ“

Dr. Mohamed Ezzat Elhamahmy graduated from the Military Technical College in 1989 with a Bachelor’s degree in Electrical Engineering. He earned a Masterโ€™s degree in Systems and Computer Engineering from Al-Azhar University in 2001, a Ph.D. in Information Technology from Cairo University in 2011, and a Professional Masterโ€™s degree in Political Studies and Security from the Faculty of Economics and Political Science.

Professional Experience ๐Ÿ’ผ

Dr. Elhamahmy has an extensive career in information technology and cybersecurity. From 1990 to 2015, he worked with the Information Systems Department of the Armed Forces, holding roles such as Systems Manager, Network Manager, and IT Manager. He specialized in cybersecurity from 2009 to 2014 and established a dedicated cybersecurity unit in 2015. He led the unit until 2019, overseeing its development, training programs, and strategic planning.

Current Roles ๐Ÿข

Since 2019, Dr. Elhamahmy has been serving as a Senior Expert in Cybersecurity at the National Telecommunications Regulatory Authority, Cairo. He is also a member of the advisory board at the College of Computers and Information Technology, Arab Academy for Science, Technology and Maritime Transport, where he lectures and supervises academic programs.

Skills and Expertise ๐Ÿ› ๏ธ

Dr. Elhamahmy is skilled in incident handling, research and development in network security, and strategic cybersecurity planning. His expertise includes advanced knowledge of various technologies and applications, with strong communication, problem-solving, and leadership abilities.

Certifications and Training ๐Ÿ…

He has obtained numerous certifications, including Certified Ethical Hacker (CEH), Certified Information Systems Security Professional (CISSP), and CCNA. He has also completed specialized training in Oracle, Microsoft Windows Server, and various cybersecurity tools.

Contributions and Achievements ๐ŸŒŸ

Dr. Elhamahmy is known for his significant contributions to cybersecurity, including establishing successful cybersecurity units and leading strategic initiatives. His work has greatly impacted the development of cybersecurity practices and education in the region.

Publication Top Notes:

  • Improving Intrusion Detection Using LSTM-RNN to Protect Dronesโ€™ Networks
    • Year: 2024
  • Internet of Drones Intrusion Detection Using Deep Learning
    • Year: 2021
  • A Real-Time Firewall Policy Rule Set Anomaly-Free Mechanism
    • Year: 2019
  • A Proposed Approach for Management of Multiple Firewalls Using REST API Architecture
    • Year: 2019
  • Towards a Practical Real-Time Applications of Face Verification
    • Year: 2019