Yirga Munaye | Wireless Tech | Best Researcher Award

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Assoc. Prof. Dr. Yirga Munaye | Wireless Tech | Best Researcher Award

Associate Professor | College of Engineering and Technology | Ethiopia 

Assoc. Prof. Dr. Yirga Munaye is an accomplished Associate Professor and Postdoctoral Researcher specializing in Artificial Intelligence, Wireless Communication, and Cybersecurity. He holds a Ph.D. in Electrical Engineering and Computer Science from the National Taipei University of Technology, Taiwan, an M.Sc. in Information Science from Addis Ababa University, and a B.Sc. in Information Technology from Bahir Dar University. Assoc. Prof. Dr. Yirga Munaye has held key academic and administrative positions, including Director of the E-Learning Management Administration Unit and Postgraduate, Research, and Community Service Coordinator at Injibara University, where he has also served as an Assistant Professor and researcher. His work focuses on machine learning, deep learning, UAV-assisted communication systems, IoT security, and resource management in wireless networks. He has authored and co-authored numerous peer-reviewed journal and conference papers in international venues such as IEEE, IET, and MDPI. Beyond research, he is actively involved in mentoring postgraduate students, evaluating mega research projects, and contributing as a reviewer and chair for international conferences like ICT4DA and ICAST. Assoc. Prof. Dr. Yirga Munaye has received multiple recognitions for his academic and professional contributions, including excellence awards for teaching, research, and community engagement. His ongoing projects explore AI-driven solutions for smart cities, cyber threat intelligence, and sustainable network design, reflecting his dedication to advancing technology for societal impact and global innovation.

Profile:  Google Scholar | Orcid

Featured Publication

Tsegazewold Kinfu, Yirga Yayeh, Yechale Amogne, Emiyamrew Azmeraw, A. O. Salau (2025). Designing an Efficient Blockchain-Enabled Internet of Things (IoT) Framework for Smart Farming. 10.22060/eej.2025.24288.5673

Munaye, Y. Y., Workneh, A. B., Chekol, Y. B., & Mekonen, A. M. (2025). Effective Detection of Malicious URLs Using Deep Learning Techniques. Algorithms, 18, 355.

Munaye, Y. Y., Admass, W., Belayneh, Y., Molla, A., & Asmare, M. (2025). ChatGPT in Education: A Systematic Review on Opportunities, Challenges, and Future Directions. Algorithms, 18, 352.

Mekonnen, A. M., Munaye, Y. Y., & Chekol, Y. B. (2025). A Hybrid LSTM-CNN Approach Using Multilingual BERT for Sentiment Analysis of GERD Tweets. Buletin Ilmiah Sarjana Teknik Elektro, 7(2), 206–213.

Munaye, Y. Y., Addis, M., Belayneh, Y., Molla, A., & Admass, W. (2025). Hybrid Deep Learning Methods for Human Activity Recognition and Localization. Algorithms, 18, 235.

Mr. JeongHun Woo | Network Services | Excellence in Research

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Mr. JeongHun Woo | Network Services | Excellence in Research

Mr. JeongHun Woo, Changwon National University, South Korea

Mr. JeongHun Woo is a dedicated researcher specializing in Network Services, Wireless Networks, and Streaming Optimization. He completed his education at Changwon National University, South Korea, and has been actively involved in cutting-edge research projects, particularly in AI-based optimization and predictive analytics. His work on Yard Image AI Recognition for logistics optimization resulted in a technology patent, showcasing his innovative contributions to industrial applications. Additionally, his 2023 first-author publication on adaptive bitrate algorithms and bandwidth prediction has significantly enhanced video streaming quality. His ongoing research on CNC tool replacement cycle prediction highlights his expertise in applying machine learning to industrial automation. With a strong foundation in AI-driven network optimizations and industrial predictive modeling, Mr. Woo continues to push technological boundaries, contributing valuable insights to academia and industry. His research excellence makes him a key player in advancing intelligent network systems. 📡📶🔬

🌏 Professional Profile

Google Scholar

🏆 Suitability for Award 

Mr. JeongHun Woo’s outstanding contributions to network optimization, AI-driven prediction models, and wireless communication technologies make him a strong candidate for the Excellence in Research Award. His groundbreaking work in adaptive video streaming algorithms has significantly improved the Quality of Experience (QoE) in streaming services, addressing critical issues in network bandwidth prediction. His Smart Yard AI project, which optimizes industrial logistics through image recognition, showcases his ability to bridge academic research with real-world applications. The issuance of a technology patent from his research further validates the impact of his work. His ongoing research on predictive maintenance for CNC machine tools highlights his versatility in applying AI-driven methodologies to industrial automation and smart manufacturing. His ability to produce innovative, high-impact research across wireless networks, AI, and predictive analytics sets him apart as a leading researcher in his field. 🏆📡📊

🎓 Education 

Mr. JeongHun Woo pursued his education at Changwon National University, South Korea, where he developed a strong foundation in Network Services, Wireless Communication, and AI-Driven Optimization. His academic journey equipped him with expertise in machine learning applications, network bandwidth prediction, and industrial AI integration. Throughout his education, he focused on research-driven problem-solving, contributing to the development of streaming optimization algorithms and predictive analytics for industrial automation. His exposure to AI-powered logistics and wireless technologies has positioned him as an emerging expert in intelligent network solutions. His academic background not only fueled his passion for research but also enabled him to lead innovative projects such as AI-based yard logistics optimization and CNC machine tool lifecycle prediction. With a strong interdisciplinary approach, his education has played a crucial role in shaping his research excellence and industry-driven solutions. 🎓📚🔍

👨‍🔬 Experience

Mr. JeongHun Woo has been deeply engaged in research projects that integrate AI, wireless communication, and industrial automation. He played a key role in the Smart Yard Industry-Academic Cooperation Project (2022), where he developed an AI-based image recognition system to optimize logistics and process flow in industrial yards. This work led to the successful issuance of a technology patent, reinforcing his contributions to real-world AI applications.

In 2023, he authored a research paper focusing on adaptive bitrate algorithms and bandwidth prediction for enhanced video streaming experiences. His work in network bandwidth prediction using gated recurrent unit models demonstrated his expertise in machine learning-driven optimizations. Currently, he is working on predicting CNC machine tool replacement cycles, leveraging AI for predictive maintenance in smart manufacturing. His diverse experience across network systems, industrial AI applications, and streaming optimizations showcases his strong research acumen and technological impact. 🏭📡🤖

🏆 Awards and Honors 

Mr. JeongHun Woo has been recognized for his pioneering research in wireless networks, AI-driven optimization, and industrial analytics. His Smart Yard AI Recognition project led to the issuance of a technology patent, highlighting the innovative real-world impact of his research. His 2023 first-author publication on adaptive bitrate streaming and bandwidth prediction has been widely acknowledged in the field of wireless networks and multimedia communication.

He has been actively involved in industry-academic collaborative projects, leading groundbreaking research that merges AI with industrial automation. His contributions to predictive analytics for CNC machine tool maintenance have positioned him at the forefront of smart manufacturing and AI-driven optimization. Through his patented technology, high-impact publications, and ongoing research in predictive maintenance, Mr. Woo has demonstrated exceptional excellence in research, making him a deserving candidate for the Research for Excellence in Research Award. 🏆📜🚀

🔬 Research Focus 

Mr. JeongHun Woo’s research revolves around Network Services, Wireless Networks, Streaming Optimization, and AI-driven Industrial Automation. His work is at the intersection of machine learning, predictive analytics, and real-world network applications.

His key research areas include:

✅ Streaming Optimization: Developing buffer-based adaptive bitrate algorithms to improve the Quality of Experience (QoE) for video streaming.
✅ AI for Industrial Automation: Leading AI-driven logistics optimization through yard image recognition and predictive maintenance in smart manufacturing.
✅ Wireless Networks & Bandwidth Prediction: Utilizing deep learning (Gated Recurrent Unit models) for accurate network bandwidth forecasting.
✅ Predictive Maintenance: Researching CNC machine tool lifecycle prediction to enhance manufacturing efficiency and reduce downtime.

His interdisciplinary approach combining network optimizations, AI, and industrial analytics makes him a key contributor to next-generation intelligent systems. 🌍📶📊

📚 Publication Top Notes:

Title: Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction
Published Year: 2024

 

 

Dr. Mikhajlo K. Zubko | Novel Protocols | Best Researcher Award

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Dr. Mikhajlo K. Zubko | Novel Protocols | Best Researcher Award

Dr. Mikhajlo K. Zubko, Manchester Metropolitan University, United Kingdom

Dr. Mikhajlo K. Zubko is a distinguished researcher in the field of genetics, specializing in the genetic mechanisms of biodiversity, genomic integrity, and telomere maintenance. He has made significant contributions to the understanding of checkpoint control under DNA damage, the interactions between nuclear and cytoplasmic genomes, and the impact of these interactions on genome stability and adaptation to stress factors. Dr. Zubko’s research has provided valuable insights into the role of telomere length in drug discovery and antifungal resistance. His work on yeast cells and mitochondrial DNA recombination has advanced the field of genetic variation and inheritance. Dr. Zubko’s academic journey spans prestigious institutions, with a Ph.D. in Genetics and a rich history of teaching and research. His ambitious idea to establish inter-compartmental genetics has further enriched our understanding of genetic variation. 🌿🧬🔬

Professional Profile

Orcid

Suitability for Award

Dr. Mikhajlo K. Zubko is an ideal candidate for the Research for Best Researcher Award due to his groundbreaking contributions to the fields of genetics and molecular biology. His pioneering research on telomere maintenance, mitochondrial DNA recombination, and the genetic mechanisms of stress adaptation has provided valuable insights into genome stability. Dr. Zubko’s innovative work on antifungal resistance in yeast and his development of advanced protocols for telomere length analysis have had a profound impact on genetic research. His ambitious concept of inter-compartmental genetics further highlights his visionary approach to understanding genetic variation and inheritance. His academic achievements, including numerous publications and invited lectures, demonstrate his leadership in advancing genetic research. Dr. Zubko’s dedication to exploring the intersections of genetics, evolution, and development makes him a highly deserving candidate for this prestigious award. 🏅🔬🌍

Education 

Dr. Mikhajlo K. Zubko holds a Ph.D. in Genetics from the Institute of Molecular Biology and Genetics, Kiev, awarded in 1987. He completed his undergraduate studies at Kiev State University, earning an MSci Hons. in Genetics and a BA Hons. in Biology, with a focus on genetics, biochemistry, molecular biology, and microbiology. His academic journey also includes a Diploma in Public Faculty (Journalism) from Kiev State University in 1976. Dr. Zubko further enhanced his academic expertise with a Postgraduate Certificate in Academic Practice from Bridgewater Hall, Manchester, in 2010. This diverse educational background, combining both scientific and communication disciplines, has equipped Dr. Zubko with a unique perspective on genetic research and teaching. His qualifications have supported his extensive research career, where he has developed novel protocols and methodologies for studying genetic mechanisms and genome stability. 🎓🧬📚

Experience

Dr. Mikhajlo K. Zubko has a wealth of experience in both research and teaching. He has held academic positions at various universities, where he has taught undergraduate and postgraduate courses in genetics, molecular biology, and biochemistry. Dr. Zubko has also led international training courses on cell and genetic engineering in higher plants, sharing his expertise with the next generation of scientists. His research experience spans several decades, with notable contributions to the study of genetic mechanisms of biodiversity, genomic integrity, and the role of telomere maintenance in drug discovery. Dr. Zubko has supervised numerous undergraduate and postgraduate students, guiding them in their research projects and fostering academic growth. He has also been an invited speaker at universities and research institutes, delivering talks at international and national conferences. His extensive teaching and research experience make him a highly respected figure in the field of genetics. 🏫🔬🌍

Awards and Honors 

Dr. Mikhajlo K. Zubko’s career has been marked by numerous awards and honors, recognizing his outstanding contributions to the field of genetics. He has been recognized for his work in the development of novel protocols for studying telomere length and antifungal resistance. Dr. Zubko’s research on the integration of genetic information and metabolic activities during growth and development has also garnered significant attention in the scientific community. His work on mitochondrial DNA recombination and the resilience of yeast cells to antifungals has provided important tools for genetic research. Dr. Zubko’s dedication to advancing the field of genetics has been acknowledged through invitations to speak at prestigious international conferences and universities. His ability to bridge the gap between basic research and practical applications has made him a highly respected figure in his field. 🏆🔬🌍

Research Focus 

Dr. Mikhajlo K. Zubko’s research focuses on the genetic mechanisms of biodiversity, genomic integrity, and telomere maintenance. He has developed advanced methods for studying the impact of DNA damage and checkpoint control in yeast and other organisms. His work on mitochondrial DNA recombination has provided insights into the basic genetic mechanisms of recombination and inheritance. Dr. Zubko’s research also explores the interactions between nuclear and cytoplasmic genomes, examining how these interactions influence genome stability, development, and stress adaptation. He has pioneered the use of telomere length analysis as a tool for drug discovery, offering new opportunities for therapeutic interventions. Additionally, Dr. Zubko’s research delves into the links between evolution and development, shedding light on how genetic variation contributes to adaptation and resilience. His work on antimicrobial resistance from natural resources further emphasizes his commitment to understanding and solving critical biological challenges. 🌱🧬🔬

Publication Top Notes

  • Title: Enhanced Tolerance to Antifungals as a General Feature of Rho− Mutants in Yeast Species: Implications to Positive Selection of Respiratory Deficiency
    • Date: 2025
  • Title: Short mre11Δ Telomeres of Saccharomyces Cerevisiae Do Not Shorten Further Under Thermal Stress, in Contrast to Long pif1Δ Telomeres: A Few Aspects of Implications
    • Date: 2024
  • Title: Antimicrobial Potential of Pomegranate and Lemon Extracts Alone or in Combination with Antibiotics Against Pathogens
    • Date: 2024
  • Title: Towards Sustainable Antimicrobials from Plants: Some Ways to Abridge Current Methodological Approaches
    • Date: 2024
  • Title: Phloroglucinol-Enhanced Whey Protein Isolate Hydrogels with Antimicrobial Activity for Tissue Engineering
    • Date: 2021

 

 

Prof. Yiyang Ni | Next-Gen Comms | Best Researcher Award

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Prof. Yiyang Ni | Next-Gen Comms | Best Researcher Award

Prof. Yiyang Ni, Jiangsu Second Normal University, China

Prof.  Ni Yiyang is the Vice Dean of the School of Computer Engineering at Jiangsu Second Normal University. A member of the Communist Party of China, she completed her Ph.D. in Communication and Information Systems at Nanjing University of Posts and Telecommunications in April 2016. Yiyang is recognized for her contributions to intelligent communication and resource allocation in the Internet of Vehicles. With extensive academic involvement, she has also served as a postdoctoral researcher and lecturer, making significant strides in her field through various research projects and publications.

Professional Profile

Google Scholar

Suitability of Prof. Yiyang Ni for the Research for Best Researcher Award

Prof. Yiyang Ni is a distinguished female researcher in the field of communication engineering, whose contributions significantly align with the objectives of the Research for Best Researcher Awards. Her academic background, robust research agenda, and leadership roles position her as an exemplary candidate for this honor.

Education 

Prof. Yiyang Ni’s academic journey began at Nanjing University of Posts and Telecommunications, where she earned her Bachelor’s Degree in Communication Engineering in June 2008. She continued her studies at the same institution, pursuing a Master-Doctoral Program in Communication and Information Systems. Under the mentorship of Advisor Zhang Naitong, she successfully obtained her Ph.D. in April 2016. Her education laid a robust foundation for her future research endeavors, particularly in intelligent communication technologies.

Experience 

Prof. Yiyang Ni has accumulated diverse teaching and research experiences since 2008. She started as a Teaching Assistant at Nanjing University, progressing to Lecturer and Associate Professor roles at Jiangsu Second Normal University from April 2016 to May 2022. Currently, as Vice Dean, she plays a pivotal role in the School of Computer Engineering. Additionally, since January 2019, she has been involved in postdoctoral research, focusing on innovative communication systems and leading several significant research projects in her field.

Awards and Honors 

Prof. Yiyang Ni has received numerous accolades throughout her career, reflecting her exceptional contributions to the field of communication. Notable awards include the Second Prize for her IoT Intelligent Management System at the China Communication Society’s Science and Technology Award (2021) and the First Prize at the Jiangsu Information and Communication Industry Science and Technology Award (2021). Her innovative projects have garnered recognition, including the Second Prize for Key Technologies in Edge Networks from the China Institute of Electronics in 2021.

Research Focus 

Prof. Yiyang Ni’s research interests lie at the intersection of intelligent communication, wireless communication, and resource allocation within the Internet of Vehicles. She leads various ongoing projects aimed at developing cutting-edge communication technologies, including the integration of industrial Internet systems and the study of intelligent wireless communication theories for future networks. Her contributions to terahertz communication and device-to-device technologies are particularly noteworthy, advancing the understanding and application of these crucial areas in modern communication systems.

Publiaction Top Notes

  1. Title: Blockchain for the IoT and industrial IoT: A review
    Citation: 415
  2. Title: Beamforming and interference cancellation for D2D communication underlaying cellular networks
    Citation: 56
  3. Title: Performance Analysis for RIS-Assisted D2D Communication Under Nakagami-Fading
    Citation: 44
  4. Title: Energy efficiency and spectrum efficiency in underlay device-to-device communications enabled cellular networks
    Citation: 40
  5. Title: Weighted adaptive KNN algorithm with historical information fusion for fingerprint positioning
    Citation: 31

 

Mr. Md Jobair Hossain Faruk | Blockchain in Comms Award | Best Researcher Award

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Mr. Md Jobair Hossain Faruk | Blockchain in Comms | Best Researcher Award

Mr. Md Jobair Hossain Faruk, New York Institute of Technology, United States

🎓 Mr. Md Jobair Hossain Faruk is a driven Ph.D. student at the New York Institute of Technology 🏙️, where he maintains a stellar 4.0 CGPA while delving into the realms of software engineering, health informatics, and cybersecurity 🛡️. His passion lies in harnessing the power of machine learning 🤖 and blockchain technology ⛓️ to tackle complex challenges. With a rich academic background 📚 spanning across institutions like Kennesaw State University and Sultan Idris Education University, Jobair’s journey is marked by excellence, earning him accolades such as the Graduate Scholar Award 🏆 and Best Paper Award 📝. As a dedicated researcher, he explores diverse domains, from speech emotion recognition to innovative machine learning applications in health informatics 🧠. His commitment to professional development shines through his active involvement in ACM SIGCHI and other scientific societies 🌟, showcasing his leadership in shaping the future of technology and sustainable development 🌍.

🌐 Professional Profile:

Google Scholar

🎓 Education

Md Jobair Hossain Faruk is a dedicated Ph.D. student in the Department of Computer Science at the New York Institute of Technology, maintaining a perfect 4.0 CGPA. His research focuses on software engineering, health informatics, and cybersecurity, particularly leveraging machine learning and blockchain technology. He previously studied at Kennesaw State University and earned a Master’s in Software Engineering with a perfect CGPA and a Bachelor’s in Computing from Sultan Idris Education University in Malaysia, where he received multiple accolades, including the Dean’s Award with Distinction.

💼 Professional Experience

Currently, Jobair is a Graduate Research Assistant at NYIT, working on speech emotion recognition and health informatics under Dr. Jerry Cheng’s guidance. He also serves as a Graduate Teaching Assistant, assisting with courses on algorithms. His past roles include a postdoctoral fellowship at the University of Illinois Urbana-Champaign, an intern at the United Nations, and a research assistant at Kennesaw State University. His projects span various domains, from cybersecurity and blockchain to machine learning applications in health informatics.

🧠 Research Interests and Skills

Jobair’s research expertise includes software engineering, machine learning, deep learning, NLP, blockchain, and computer vision, with applications in health informatics and cybersecurity. He is proficient in multiple programming languages such as Python, Java, and JavaScript, and skilled in libraries and tools including OpenCV, TensorFlow, AWS, and Google Cloud. He has contributed significantly to research, publishing papers and leading innovative projects.

🏆 Awards and Honors

Jobair’s academic excellence and research prowess have earned him numerous awards, including the Graduate Scholar Award at NYIT, the Best Paper Award at IEEE ICHI 2022, and the SciAuth Fellowship at the University of Illinois Urbana-Champaign. He has also been recognized with travel grants and special paper awards from prestigious conferences and institutions.

🌟 Professional Activities and Memberships

Actively involved in professional communities, Jobair is a member of ACM SIGCHI and other scientific societies. He has organized and participated in workshops and hackathons, contributing to the academic and professional development of his peers and the broader community. His leadership and commitment to sustainable development were also recognized through his fellowship with the United Nations SDGs Future Fellowship Program.

Publication Top Notes:

  1. Ransomware classification and detection with machine learning algorithms
    • Conference: 2022 IEEE 12th Annual Computing and Communication Workshop and Conference
    • Citations: 66 (2022)
  2. Towards Blockchain-Based Secure Data Management for Remote Patient Monitoring
    • Conference: 2021 IEEE International Conference on Digital Health (ICDH)
    • Citations: 42 (2021)
  3. Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection
    • Conference: Proceedings – 2021 IEEE International Conference on Big Data, Big Data 2021
    • Citations: 42 (2021)
  4. A Review of Quantum Cybersecurity: Threats, Risks and Opportunities
    • Conference: 1st International Conference on AI in Cybersecurity (ICAIC)
    • Citations: 38 (2022)
  5. Evolution of quantum computing: A systematic survey on the use of quantum computing tools
    • Conference: 2022 IEEE 46th Annual Computers, Software, and Applications Conference
    • Citations: 33 (2022)

 

 

 

 

 

Prof. Rabil Ayazoglu | Communication Technology Award | Best Researcher Award

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Prof. Rabil Ayazoglu | Communication Technology Award | Best Researcher Award

Prof. Rabil Ayazoglu, Bayburt University, Turkey

Prof. Rabil Ayazoglu, currently a Professor at Bayburt University, Turkey, boasts an impressive academic journey in Mathematics. 🎓 He earned his Ph.D. (1984-1988) and Master’s (1981-1984) from Azerbaijan University of Architecture and Construction under the mentorship of Allahveren Cebrayılov, focusing on Integral Representations of Functions. 📚 Prof. Ayazoglu’s career spans numerous prestigious roles, including professorships at Bayburt University (2013-present) and Dicle University (2007-2011), and earlier positions at the Azerbaijan University of Architecture and Construction and Azerbaijan Technical University. 📖 He also contributes to the academic community as an editor for Probe – Mathematics Mathematical Sciences and Transactions Issue Mathematics at the National Academy of Sciences of Azerbaijan.

Professional Profile:

Google scholar

🎓 Education:

  • Ph.D. in Mathematics, Azerbaijan University of Architecture and Construction (1984-1988)
    • Thesis: Integral Representations of Functions and Embedding Theorems in Function Spaces
    • Advisor: Allahveren Cebrayılov
  • Master’s Degree in Mathematics, Azerbaijan University of Architecture and Construction (1981-1984)
    • Thesis: Integral Representations of Functions
    • Advisor: Allahveren Cebrayılov

🎓 Academic Titles:

  • Professor, Bayburt University, Faculty of Education (2013-present)
  • Professor, Dicle University, Faculty of Science, Department of Mathematics (2007-2011)
  • Associate Professor, Dicle University, Faculty of Science, Department of Mathematics (2003-2007)
  • Associate Professor, Azerbaijan University of Architecture and Construction, Department of Mathematics (1998-2003)
  • Assistant Professor, Azerbaijan University of Architecture and Construction, Department of Mathematics (1990-1998)
  • Research Assistant, Azerbaijan University of Architecture and Construction, Department of Mathematics (1984-1990)
  • Specialist, Azerbaijan Technical University (1979-1981)

📚 Editorial Positions:

  • Editor, Probe – Mathematics Mathematical Sciences, Universe Scientific Publishing
  • Editor, Transactions Issue Mathematics, Institute of Mathematics and Mechanics, National Academy of Sciences of Azerbaijan (since 2022)

Publication Top Notes:

  1. Title: Existence and multiplicity of the solutions of the p (x)–Kirchhoff type equation via genus theory
    Cited by: 67
  2. Title: Hardy’s inequality in power-type weighted Lp (⋅)(0,∞) spaces
    Cited by: 58
  3. Title: Existence of solutions of the parabolic variational inequality with variable exponent of nonlinearity
    Cited by: 56
  4. Title: Existence and multiplicity of weak solutions for nonuniformly elliptic equations with nonstandard growth condition
    Cited by: 53
  5. Title: The Nehari manifold approach for Dirichlet problem involving the p (x)-Laplacian equation
    Cited by: 46

 

 

 

 

Dr. Haider Ali | Network Communication Awards | Excellence in Research

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Dr. Haider Ali | Network Communication Awards | Excellence in Research

Dr. Haider Ali, University of Derby, United Kingdom

Haider Ali is a seasoned professional with over a decade of experience in research and teaching across esteemed institutions such as the University of Derby (UK), Qatar University (Qatar), and COMSATS University (Pakistan). Holding a Ph.D. in Computing, his expertise spans areas including computing systems, networks, cybersecurity, embedded systems, and algorithms design. He has authored numerous research papers and secured two best paper awards. As a lecturer at the University of Derby, Haider actively contributes to curriculum development, supervises undergraduate and postgraduate projects, and engages in research collaborations both locally and internationally. Additionally, he has held various teaching and research positions, further enriching his academic and professional portfolio.

Professional Profile:

Google Scholar

📚 Education:

Haider Ali’s academic journey encompasses a Ph.D. in Computing from the University of Derby, UK, completed between 2017 and 2020. Prior to this, he pursued a Master of Science degree in Electronic Systems Design Engineering at Manchester Metropolitan University, UK, from 2009 to 2010. His educational foundation was laid with a Bachelor of Science in Electronics Engineering attained at the University of Engineering and Technology, Pakistan, spanning from 2004 to 2008. Haider further augmented his academic credentials with a Postgraduate Certificate in Advanced Higher Education from the University of Derby, UK, acquired between 2022 and 2023. This diverse educational background equipped him with a comprehensive understanding of computing and electronic systems, positioning him as a versatile professional capable of making significant contributions in academia and research.

💼 Experience:

Haider Ali’s career in academia has been marked by a series of impactful roles across prestigious institutions. Beginning as a Lecturer at the College of Science and Engineering, University of Derby, UK, since September 2020, he has been instrumental in delivering undergraduate and postgraduate courses, covering a wide array of subjects such as Programming Fundamentals, Embedded Systems, and Network Security. Alongside teaching responsibilities, Haider actively supervises BSc, MSc, and Ph.D. projects, playing a key role in curriculum development and fostering research collaborations. His dedication to academic leadership is further evidenced by his service as the Derby College Group Program Leader, where he ensures effective communication and collaboration among stakeholders.

🏆 Awards and Achievements:

During his time at the University of Derby, UK, Haider Ali earned recognition for his scholarly achievements, receiving the PGTA/REF Scholarship from 2017 to 2020. His research prowess was further underscored by winning Best Paper Awards at esteemed IEEE conferences, including DSS-2018 and BDCloud-2020, highlighting the significance of his contributions to the academic community. Haider’s academic journey has been characterized by a global outlook, as evidenced by his extensive research collaborations with institutions worldwide. His commitment to advancing knowledge extends to his membership in prestigious journal review committees and technical program committees, where he plays a pivotal role in shaping the discourse and direction of cutting-edge research in his field.

Publication Top Notes:

1. Novel approach to non-invasive blood glucose monitoring based on transmittance and refraction of visible laser light
Cited By: 85
Year: 2017
Journal: IEEE Access

2.ARSH-FATI: A novel metaheuristic for cluster head selection in wireless sensor networks
Cited By: 74
Year: 2020
Journal: IEEE Systems Journal

3. Human-centric cyber social computing model for hot-event detection and propagation
Cited By: 43
Year: 2019
Journal: IEEE Transactions on Computational Social Systems

4. Energy-efficient static task scheduling on VFI-based NoC-HMPSoCs for intelligent edge devices in cyber-physical systems
Cited By: 40
Year: 2019
Journal: ACM Transactions on Intelligent Systems and Technology