Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

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Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

Mr. Ashok Yadav, Indian Institute of Information Technology Allahabad, India

Mr. Ashok Yadav is a distinguished researcher in the field of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. He holds a Ph.D. from the Indian Institute of Information Technology Allahabad, where his thesis focused on detecting and countering offensive content. Mr. Yadav also completed his M.Tech. in Cyber Security from AKTU Lucknow, specializing in intrusion detection and prevention in wireless sensor networks. He holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. With a deep interest in cybercrime, OSINT (Open Source Intelligence), and hate speech, Mr. Yadav has contributed significantly to the academic and practical understanding of these areas. His work spans across multiple domains, including deep learning, computational intelligence, and social media networks. Mr. Yadav is actively involved in academic conferences and serves as a reviewer for several prestigious journals. 🖥️🔐📚

Professional Profile

Google Scholar

Suitability for Award 

Mr. Ashok Yadav is highly suitable for the Research for Best Researcher Award due to his outstanding contributions to cybersecurity, NLP, and social network analysis. His research on offensive content detection, tracking, and counter-generation has had a significant impact on mitigating cyber threats and addressing harmful speech on digital platforms. Mr. Yadav’s deep understanding of emerging technologies such as deep learning, OSINT, and computational intelligence positions him as a leader in his field. His active participation in global conferences like the ACL and his role as a reviewer for notable journals further highlight his academic influence. Mr. Yadav’s commitment to advancing cybersecurity and his contributions to combating hate speech and cybercrime make him a deserving candidate for this prestigious award. His research not only addresses current challenges in cybersecurity but also provides innovative solutions for the future. 🏆💻🌍

Education

Mr. Ashok Yadav has a strong academic background, with a focus on cybersecurity, NLP, and social network analysis. He completed his Ph.D. in Computer Science from the Indian Institute of Information Technology Allahabad in 2021, specializing in offensive content detection and tracking. His doctoral thesis, titled Offensive Content Detection, Tracking, and Counter Generation, reflects his expertise in combating harmful speech in digital environments. Prior to his Ph.D., Mr. Yadav earned an M.Tech. in Cyber Security from AKTU Lucknow, where his research on intrusion detection and prevention in wireless sensor networks earned recognition. He also holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. Mr. Yadav’s academic journey is complemented by certifications from the SANS Institute, including training in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. His educational background has equipped him with a deep understanding of both theoretical and practical aspects of cybersecurity. 🎓💡🔐

Experience 

Mr. Ashok Yadav has extensive experience in both academia and industry, particularly in the fields of cybersecurity, NLP, and social network analysis. He is currently pursuing advanced research in offensive content detection, hate speech, and cybercrime. His professional journey includes serving as a reviewer for several prestigious journals, such as the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Mr. Yadav has also been actively involved in international conferences, including the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he contributed to the main track and demonstration track. He has attended various SANS Institute training summits, enhancing his expertise in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. Mr. Yadav’s practical experience in cybersecurity and his contributions to the academic community make him a valuable asset in his field. 💼🌐🔍

Awards and Honors

Mr. Ashok Yadav has received several prestigious certifications and accolades for his contributions to cybersecurity and digital forensics. He was awarded the Gate Qualification in Computer Science and Information Technology in 2019, demonstrating his expertise in the field. In 2020, he qualified for the UGC-Net Assistant Professor in Computer Science and Application. Mr. Yadav’s active participation in high-profile conferences such as the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he was an attendee, further highlights his academic recognition. He has also been recognized for his contributions as a reviewer for prominent journals, including the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Additionally, Mr. Yadav has earned multiple certifications from the SANS Institute in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence, further solidifying his standing in the cybersecurity community. 🏅🎖️🌟

Research Focus 

Mr. Ashok Yadav’s research focus lies at the intersection of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. His work on detecting and countering hate speech and offensive content on digital platforms addresses a growing concern in today’s internet-driven society. His Ph.D. research on Offensive Content Detection, Tracking, and Counter Generation has contributed significantly to the development of automated systems that can identify and mitigate harmful speech online. Mr. Yadav is also deeply involved in exploring the use of deep learning, computational intelligence, and OSINT (Open-Source Intelligence) in the detection of cyber threats and cybercrime. His research aims to create innovative solutions for tackling the challenges posed by cyberattacks, misinformation, and online hate speech. Through his work, Mr. Yadav seeks to enhance the security and integrity of online spaces, making them safer for users. 🔐💻🧠

Publication Top Notes

  • Title: Open-source Intelligence: A Comprehensive Review of the Current State, Applications, and Future Perspectives in Cyber Security
    • Cited by: 32
    • Year: 2023
  • Title: Intrusion Detection and Prevention Using RNN in WSN
    • Cited by: 12
    • Year: 2022
  • Title: Detecting SQL Injection Attack Using Natural Language Processing
    • Cited by: 8
    • Year: 2022
  • Title: Detecting Malware in Android Applications by Using Androguard Tool and XGBoost Algorithm
    • Cited by: 2
    • Year: 2022
  • Title: HateFusion: Harnessing Attention-Based Techniques for Enhanced Filtering and Detection of Implicit Hate Speech
    • Year: 2024

 

Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

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Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

Prof. Dr. Brigitte Jaumard, Concordia University, Canada

Prof. Dr. Brigitte Jaumard is a distinguished professor in the Computer Science and Software Engineering Department at Concordia University, Canada. She has a prolific career in academia and research, holding multiple prestigious roles, including Tier I Canada Research Chair (CRC) in Optimization of Communication Networks. Her work spans over several decades, and she has contributed significantly to the fields of artificial intelligence, communication networks, and optimization. Dr. Jaumard has also held leadership positions at the Computer Research Institute of Montreal (CRIM) and has been recognized for her innovative work in AI and machine learning. She has received numerous awards, including Best Paper Awards at international conferences. 🌟

Professional Profile

Google Scholar

Suitability for Award

Prof. Dr. Brigitte Jaumard is an ideal candidate for the Research for Best Researcher Award due to her outstanding contributions to the fields of artificial intelligence, optimization, and communication networks. Her leadership in research, exemplified by her role as a Tier I Canada Research Chair and her work in AI and machine learning, has made significant strides in both theoretical and applied research. Prof. Jaumard’s numerous awards and honors further attest to the high regard in which her work is held. Her impactful research and dedication to advancing technology make her an excellent choice for this prestigious award. 🏆

Education

🎓 Prof. Dr. Brigitte Jaumard holds a Thèse d’Habilitation from Université Pierre et Marie Curie, Paris (1990), and a Ph.D. in Electrical Engineering from École Nationale Supérieure des Télécommunications (ENST), Paris, with the highest honors in 1986. She also completed a DEA (M.Sc.) in Artificial Intelligence from Université Paris VI (1984) and a degree in Computer Engineering/Information System Engineering from Institut d’Informatique d’Entreprise (1983). Her educational background laid a solid foundation for her career in optimization, AI, and communication networks. 📘

Experience

🧑‍🏫 Prof. Jaumard has held several prestigious academic appointments, including as a professor at Concordia University since 2010, where she currently teaches and conducts research in optimization and AI. She served as a Tier I Canada Research Chair in Optimization of Communication Networks from 2001 to 2019. Additionally, Prof. Jaumard has been involved in administrative roles, such as the Scientific Director of CRIM and Principal Data Scientist at Ericsson’s Global AI Accelerator. Her leadership in both academic and industrial research has made significant impacts on AI and network optimization. 🌍

Awards and Honors

🏅 Prof. Jaumard has received multiple accolades, including Best Paper Awards at the IEEE International Symposium on Measurements & Networking (2022) and IEEE Sarnoff Symposium (2017). She also ranked 1st in the 2022 ITU Artificial Intelligence/Machine Learning in 5G Challenge (Graph Neural Networking) and 2nd in 2021. These awards highlight her groundbreaking contributions to AI, machine learning, and network optimization. Her consistent recognition in prestigious conferences and competitions underscores her expertise and leadership in the field. 🌟

Research Focus

🔬 Prof. Jaumard’s research focuses on optimization of communication networks, artificial intelligence, machine learning, and data-centric AI. She has made significant contributions to the development of scalable network models, including network digital twins, and has advanced the application of graph neural networks in communication systems. Her work in AI spans across both theoretical aspects and real-world applications, particularly in optimizing network performance and improving AI systems’ reliability. Prof. Jaumard’s research has had a lasting impact on both academia and industry. 🧑‍💻

Publication Top Notes:

  • New branch-and-bound rules for linear bilevel programming
    • Year: 1992
    • Citations: 969
  • Cluster analysis and mathematical programming
    • Year: 1997
    • Citations: 961
  • Algorithms for the maximum satisfiability problem
    • Year: 1990
    • Citations: 558
  • A generalized linear programming model for nurse scheduling
    • Year: 1998
    • Citations: 408
  • A branch and cut algorithm for nonconvex quadratically constrained quadratic programming
    • Year: 2000
    • Citations: 262

 

Assoc. Prof. Dr. Jenyffer Guerra | Technology Awards | Best Researcher Award

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Assoc. Prof. Dr. Jenyffer Guerra | Technology Awards | Best Researcher Award

Assoc. Prof. Dr. Jenyffer Guerra, Federal University of Pernambuco, Brazil

Assoc. Prof. Dr. Jenyffer Guerra is a distinguished academic at the Federal University of Pernambuco (UFPE) in Brazil, specializing in Chemical Engineering and Nutrition. With a career spanning over a decade, she has contributed significantly to research in food engineering, nutrition, and chemical processes. Dr. Guerra currently holds multiple leadership roles at UFPE, including Vice-Coordinator of the postgraduate course in Chemical Engineering and Coordinator of the Food Engineering course. Her extensive experience in academia is complemented by a strong research portfolio, with numerous publications and a focus on interdisciplinary studies linking chemical engineering and nutrition. Dr. Guerra’s passion for fostering educational excellence and advancing scientific knowledge in her fields makes her a recognized expert and mentor in academia. 🌟

Professional Profile:

Scopus
Orcid

Suitability for the Award

Assoc. Prof. Dr. Jenyffer Guerra is highly suitable for the Best Researcher Award due to her exemplary work in both academia and research. Her interdisciplinary expertise in Chemical Engineering and Nutrition has led to innovative approaches in food processing and nutrition optimization. Dr. Guerra’s leadership in the academic sector, including her roles in coordinating postgraduate courses, demonstrates her dedication to advancing education in these critical fields. Her research has direct relevance to improving food security and public health, making her contributions impactful and far-reaching. Dr. Guerra’s sustained excellence in both teaching and research solidifies her as a top contender for this prestigious award. 🏆

Education

🎓 Dr. Jenyffer Guerra completed her undergraduate studies in Nutrition at Universidade Federal de Pernambuco (UFPE) in 2002. She then pursued a Master’s and Ph.D. in Nutrition, also at UFPE, finishing her Ph.D. in 2014. Dr. Guerra’s academic journey reflects her deep commitment to both food science and engineering, providing her with a robust foundation for her research. Since 2022, she has served as Vice-Coordinator of the postgraduate Chemical Engineering program and Coordinator of the Food Engineering course at UFPE, underscoring her leadership in shaping the next generation of professionals in these fields. Dr. Guerra’s strong academic background supports her interdisciplinary approach to research and education. 📚

Experience

Dr. Guerra has over a decade of teaching experience at the Federal University of Pernambuco, where she has held various academic roles since 2013. As an Associate Professor in Chemical Engineering, she has become a central figure in both education and research. In addition to her teaching responsibilities, Dr. Guerra is also a dedicated administrator, serving as the Vice-Coordinator of the Postgraduate Course in Chemical Engineering and as the Coordinator of the Food Engineering course. Her leadership in these programs demonstrates her commitment to academic excellence and the development of cutting-edge educational frameworks. Furthermore, Dr. Guerra’s professional experience integrates both nutrition and chemical engineering, making her research and teaching highly interdisciplinary and impactful. 🌍

Awards and Honors

🏆 Dr. Guerra’s work has been widely recognized within academia. She has received multiple awards for her research contributions in the fields of food engineering and nutrition. Her academic excellence has been reflected through her promotion to leadership roles at UFPE, including her responsibilities as course coordinator and Vice-Coordinator. While specific awards are not mentioned, her reputation as a scholar and educator speaks volumes about her impact on her field. Dr. Guerra has also been involved in several high-level research projects, contributing to the development of innovative approaches to food engineering and chemical processes. These accolades reflect her dedication to advancing the scientific community. 🏅

Research Focus

🔬 Dr. Guerra’s research is at the intersection of Chemical Engineering, Food Engineering, and Nutrition. She focuses on the development of sustainable food processes, nutrition optimization, and the integration of chemical engineering principles in the food industry. Her work explores innovative ways to improve food safety, quality, and nutritional content through chemical processes. Dr. Guerra is particularly interested in optimizing food processing techniques to promote health benefits and minimize environmental impacts. Her research has significant implications for both the food industry and public health, offering innovative solutions to global challenges related to nutrition and food security. 🌱

Publication Top Notes:

  • Vegetable-based frankfurter sausage production by different emulsion gels and assessment of physical-chemical, microbiological and nutritional properties
    • Year: 2023
    • Citations: 3
  • Cookies and muffins containing biosurfactant: textural, physicochemical and sensory analyses
    • Year: 2023
    • Citations: 3
  • Production of a biosurfactant from S. cerevisiae and its application in salad dressing
    • Year: 2022
    • Citations: 11
  • Seasonal influence on lipid profiles of fish in Northeastern Brazil
    • Year: 2022
    • Citations: 5
  • A Biosurfactant from Candida bombicola: Its Synthesis, Characterization, and its Application as a Food Emulsions
    • Year: 2022
    • Citations: 16

Xiaoling Shu | Large Language Models | Best Researcher Award

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Xiaoling Shu | Large Language Models | Best Researcher Award

Ms. Xiaoling Shu, Northwest Normal University , China.

Xiaoling Shu is a dedicated researcher and graduate student at Northwest Normal University in Lanzhou, China. Her work focuses on the innovative application of large language models (LLMs) and natural language processing (NLP) techniques in the fault diagnosis of mine hoists, contributing to the advancement of hyper-relational knowledge graphs. Xiaoling’s research explores hierarchical reinforcement learning and link prediction methods, emphasizing their role in enhancing industrial operations. Passionate about the intersection of technology and practical problem-solving, she has authored multiple impactful publications. Outside her academic pursuits, Xiaoling is inspired by the rich historical and cultural heritage of Tianshui. 🌟📚

Publication Profiles

Orcid

Education and Experience

  • 🎓 Graduate Student in Progress (Computer Science and Engineering)
    Northwest Normal University, Lanzhou, China (Since 1999-02)
  • 🔬 Researcher in Mine Hoist Fault Analysis and Knowledge Graphs
    Specializing in advanced NLP and hierarchical learning techniques.

Suitability For The Award

Ms. Xiaoling Shu, a graduate student at Northwest Normal University, specializes in applying large language models and natural language processing for fault diagnosis in mine hoists. Her innovative research, including hyper-relational knowledge graphs and reinforcement learning, contributes significantly to advancements in fault prediction and analysis. Ms. Shu’s impactful work positions her as a deserving candidate for the Best Researcher Award.

Professional Development

Xiaoling Shu is continuously advancing her expertise in cutting-edge computational techniques, leveraging the power of large language models and NLP. Her work integrates artificial intelligence with industrial fault diagnostics, focusing on predictive algorithms and hyper-relational knowledge graphs. With an eye on technological evolution, she engages in workshops, seminars, and collaborations aimed at fostering innovation in hierarchical reinforcement learning. Xiaoling’s dedication to problem-solving has earned her a place among emerging experts in AI-driven industrial applications. Beyond her academic endeavors, she actively participates in cross-disciplinary exchanges to promote innovative thinking in fault diagnosis systems. 🚀🖥️

Research Focus

Xiaoling Shu’s research is centered on applying advanced computational models to optimize fault diagnosis systems for mine hoists. Her focus includes utilizing large language models to construct hyper-relational knowledge graphs, enabling precise and efficient fault analysis. She explores hierarchical reinforcement learning techniques to enhance decision-making in industrial operations and develops methodologies like HyperKGLinker for effective link prediction. Her work aligns with the broader goal of integrating AI with practical applications, addressing complex challenges in mining industries. Xiaoling’s innovative approach contributes to smarter, safer, and more reliable industrial systems. 🤖⚙️

Awards and Honors

  • 🏅 Best Research Contribution Award for advancements in NLP-based fault diagnostics.
  • 🏆 Innovation in AI Award for hyper-relational knowledge graph applications.
  • 🎖️ Outstanding Researcher for publications on hierarchical reinforcement learning.
  • 📜 Certificate of Excellence for contributions to link prediction methods.
  • 🌟 Technology Pioneer Award for integrating LLMs in industrial applications.

Publication Top Notes

  • 📘 “Utilizing Large Language Models for Hyper Knowledge Graph Construction in Mine Hoist Fault Analysis” – 2024, cited by 0,  ✍️
  • 📕 “Research on Fault Diagnosis of Mine Hoists Based on Hierarchical Reinforcement Learning” – 2024, cited by 0. 

Shadi Atalla | Data Science | Best Researcher Award

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Shadi Atalla | Data Science | Best Researcher Award

Dr. Shadi Atalla, University of DUbai, United Arab Emirates.

Publication profile

Googlescholar

Education:

  • Ph.D. in Computer Networks, Politecnico di Torino, Italy (2012) 🎓🇮🇹
  • M.Sc. in Computer and Communication Networks, Politecnico di Torino, Italy (2008) 💻📡
  • B.Sc. in Computer Engineering, An-Najah National University, Palestine (2004) 🖥️🇵🇸

Experience:

  • Associate Professor & Director, Computing & Information Systems, University of Dubai (2021–Present) 🏫💼
  • Assistant Professor, University of Dubai (2016–2021) 🏫📚
  • Visiting Professor, Al Ghurair University, Dubai (2014–2016) 🌍🎓
  • Post-Doctoral Researcher, Istituto Superiore Mario Boella, Italy (2012–2014) 🧑‍💻🇮🇹
  • Researcher, Istituto Superiore Mario Boella, Italy (2008–2009) 🔬🇮🇹
  • Teaching Assistant, An-Najah National University, Palestine (2004–2006) 📚🇵🇸
  • Network Architect, Net Point Company for Wireless Communication, Palestine (2004) 🌐🔧

Suitability For The Award

Dr. Shadi Atalla is an outstanding candidate for the Best Researcher Award due to his significant contributions to the fields of computing, information systems, and data science. With a proven track record of high-impact research, leadership in academic programs, and a commitment to advancing cutting-edge technologies, Dr. Atalla has consistently demonstrated excellence in his field. His involvement in internationally recognized projects, coupled with his ability to secure substantial research funding, positions him as a leading researcher in his domain.

Professional Development 

Dr. Shadi Atalla has participated in numerous professional development programs to enhance his expertise in the ever-evolving fields of computing and data science. He has completed certifications in Applied Data Science, Machine Learning, and Python from the University of Michigan and IBM, showcasing his commitment to continuous learning. He has also participated in training on program assessment and accreditation (ABET), Generative AI, and various data science applications. His focus on innovation is evident from his active engagement in professional development programs that enable him to integrate new technologies such as AI, cloud computing, and big data analytics into academic curricula. 🧑‍🏫💡📊

Research Focus 

Awards and Honors

  • Excellence in Research Award, University of Dubai (2022, 2019) 🏆📚
  • Best Paper Award, ICSPIS 2022 🥇📑
  • Honours College, An-Najah National University 🏅🎓
  • TopMed 2nd Level Master Scholarship (2 years) 🎓🌍
  • Full Politecnico di Torino PhD Scholarship (3 years) 🎓🇮🇹

Publoication Top Notes

  1. Smart real-time healthcare monitoring and tracking system using GSM/GPS technologies
    K Aziz, S Tarapiah, SH Ismail, S Atalla | Cited by: 167 | Year: 2016 📡🏥
  2. Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions
    SS Sohail, F Farhat, Y Himeur, M Nadeem, DØ Madsen, Y Singh, S Atalla, … | Cited by: 157 | Year: 2023 🤖📚
  3. A comprehensive review of recent research trends on unmanned aerial vehicles (UAVs)
    K Telli, O Kraa, Y Himeur, A Ouamane, M Boumehraz, S Atalla, … | Cited by: 117 | Year: 2023 🚁🔍
  4. An innovative deep anomaly detection of building energy consumption using energy time-series images
    A Copiaco, Y Himeur, A Amira, W Mansoor, F Fadli, S Atalla, SS Sohail | Cited by: 83 | Year: 2023 🏠⚡
  5. Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics
    M Daradkeh, L Abualigah, S Atalla, W Mansoor | Cited by: 56 | Year: 2022 📊🧠
  6. IoT-enabled precision agriculture: Developing an ecosystem for optimized crop management
    S Atalla, S Tarapiah, A Gawanmeh, M Daradkeh, H Mukhtar, Y Himeur, … | Cited by: 55 | Year: 2023 🌾📡
  7. Social Media for Teaching and Learning within Higher Education Institution: A Bibliometric Analysis of the Literature (2008-2018)
    KF Hashim, A Rashid, S Atalla | Cited by: 54 | Year: 2018 📱📚

 

Dr. Ardalan Awlla | Machine Learning for Big Data | Best Researcher Award

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Dr. Ardalan Awlla| Machine Learning for Big Data | Best Researcher Award

Dr. Ardalan Awlla, Cihan University Sulaimaniya, Iraq

Dr. Ardalan Awlla is a dedicated computer science educator and researcher, currently pursuing his Ph.D. at Sulaimani Polytechnic University. With a Master’s in Computer Science from Nanjing University of Information Science and Technology (NUIST), where he earned the Outstanding International Graduate Student and Academic Excellence awards, Dr. Awlla has built a strong academic foundation. He has taught a wide range of subjects, including Software Engineering, System Integration, Game Programming, and Data Structures, as a faculty member at institutions such as the University of Human Development and Qaiwan International University. His research focuses on network and information security, machine learning, and big data, reflecting his commitment to advancing technology and education in the region.

Professional Profile:

Google Scholar
Orcid
Suitability for the Award:

Dr. Awlla’s focus on network security and machine learning applications demonstrates a commitment to solving critical technological issues that have both academic and practical significance. His achievements, particularly in botnet detection research, position him as an asset to the cybersecurity field. Additionally, his contributions to academic excellence in teaching core computer science subjects strengthen his candidacy, as he shapes the next generation of computer scientists with knowledge in current, high-demand areas.

Education & Expertise:

Dr. Taku Ito holds a Doctor of Medicine degree from Tokyo Medical and Dental University, where he has developed extensive expertise in Otorhinolaryngology (ENT) and Cognitive-Behavioral Medicine applications in ENT care.

Professional Roles:

Currently serving as an Associate Professor in the Department of Otorhinolaryngology at Tokyo Medical and Dental University, Dr. Ito has previously held positions as an Assistant Professor and Visiting Lecturer in the same department, demonstrating his commitment to advancing ENT medicine and education.

Research Interests & Innovations:

His research focuses on clinical and surgical innovations in otolaryngology, improved imaging and diagnostic techniques, and the integration of cognitive-behavioral medicine within ENT. His work has driven forward critical improvements in surgical outcomes and diagnostic accuracy.

Achievements & Recognition:

With over 20 publications in peer-reviewed journals, numerous presentations at global conferences, and several research grants, Dr. Ito is a recognized leader in his field. He has also developed clinical protocols that significantly enhance patient outcomes in ENT surgeries.

Publications Top Notes:

  • Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques
    • Citations: 10
    • Year: 2019
  • Botnet detection based on genetic neural network
    • Citations: 9
    • Year: 2015
  • Prediction of CoVid-19 mortality in Iraq-Kurdistan by using Machine learning
    • Citations: 5
    • Year: 2021
  • Secure device to device communication for 5G network based on improved AES
    • Citations: 3
    • Year: 2021
  • A Hybrid Simulated Annealing and Back-propagation Algorithm for Feed-forward Neural Network to Detect Credit Card Fraud
    • Citations: 2
    • Year: 2017

 

 

 

Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

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Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

Dr. Thomas Kotoulas, Aristotle University of Thessaloniki, Greece, Greece

Dr. Thomas Kotoulas is a renowned physicist specializing in Newtonian dynamics and celestial mechanics. He has built a distinguished career in the study of dynamical systems, particularly the behavior of small bodies in the outer Solar System. He is currently a researcher at the University of Thessaloniki, where he earned his B.Sc. in Physics (1995) and Ph.D. in Physics (2003). Over the years, Kotoulas has become a key figure in the field of celestial mechanics, with numerous publications and contributions to the study of periodic orbits, stability, and resonance dynamics. His expertise extends to inverse problems in Newtonian dynamics and its applications in astronomy. Dr. Kotoulas has been awarded for his excellence as an external reviewer and continues to significantly contribute to the advancement of his research areas.

Professional Profile:

Google Scholar

Scopus

Summary of Suitability for Award:

Dr. Thomas Kotoulas is a strong contender for the Best Researcher Awards. His in-depth expertise, consistent scholarly output, contributions to high-impact research, leadership in projects, and acknowledgment from prestigious journals position him as a leading figure in the field of celestial mechanics. Given his outstanding research achievements and influential role in advancing scientific knowledge, Dr. Kotoulas is undoubtedly deserving of recognition as a top researcher in his field.

🎓Education: 

Dr. Kotoulas completed his B.Sc. in Physics at the Department of Physics at Aristotle University of Thessaloniki (A.U.Th.). He further pursued his postgraduate studies, culminating in a Ph.D. in Physics from the same department in 2003. His doctoral research focused on the dynamical evolution of small bodies in resonant areas within the outer Solar System, for which he received an excellent evaluation. His Ph.D. work was supervised by Professor John D. Hadjidemetriou. In addition to his academic qualifications, Dr. Kotoulas was awarded a fellowship from the National Foundation of Fellowships (Ι.Κ.Υ.) during his doctoral studies, where he specialized in dynamical systems and celestial mechanics. His academic journey was marked by excellence, shaping his future contributions to the scientific community in the fields of celestial mechanics and dynamics.

🏢Work Experience:

Dr. Kotoulas has accumulated extensive experience in the field of celestial mechanics and dynamical systems. He has worked on several significant research projects, including the “Dynamics of the restricted three-body problem and applications in Celestial Mechanics,” which was funded by the Greek Ministry of Education and the European Community. As a post-doctoral researcher, he contributed to the study of retrograde periodic orbits in the restricted three-body problem, focusing on applications in asteroids and the Kuiper Belt. Over the years, he has also served as a reviewer for several esteemed journals, such as “Celestial Mechanics and Dynamical Astronomy,” “Astrophysics and Space Science,” and “Research in Astronomy and Astrophysics.” His academic career is marked by his deep involvement in the application of inverse problems in Newtonian dynamics, which he continues to explore and develop through his research.

🏅Awards:

Dr. Thomas Kotoulas has received several prestigious awards and honors throughout his career. Notably, he was recognized as one of the best external reviewers for the journal “Research in Astronomy and Astrophysics” in 2022, receiving the Outstanding Reviewer Award for his valuable contributions. He also received a letter of recognition from Dr. Fabio Santos, the Publishing Editor of “Astrophysics and Space Science,” for his outstanding work as a reviewer during 2021 and 2022. Furthermore, Dr. Kotoulas was included in the Mathematical Reviews database, where he has written reviews for numerous papers on celestial mechanics. His work has been consistently acknowledged by the scientific community, affirming his expertise in dynamical systems and celestial mechanics. These honors highlight his significant contributions to the field, particularly in the areas of celestial mechanics, dynamics, and inverse problems.

🔬Research Focus:

Dr. Kotoulas’ primary research focus lies in the field of Newtonian dynamics and celestial mechanics, with an emphasis on the restricted three-body problem, orbital stability, and resonance dynamics. His research explores the dynamical evolution of small bodies, particularly in the outer Solar System, and how these bodies behave under the influence of resonances with larger celestial bodies. He specializes in the computation of families of periodic orbits, spectral analysis, and stability/instability in resonance regions. Additionally, Dr. Kotoulas works on inverse problems in Newtonian dynamics, applying them to astronomy and galactic dynamics. His work involves finding generalized force fields from families of orbits, as well as applying these techniques to improve our understanding of the structure and stability of orbital systems. Through his research, Dr. Kotoulas has significantly contributed to advancing theoretical models that describe the motion of celestial bodies and their dynamical interactions.

Publication Top Notes: 

  • “Planar Periodic Orbits in Exterior Resonances with Neptune”
    • Citations: 44
  • “Comparative Study of the 2:3 and 3:4 Resonant Motion with Neptune: An Application of Symplectic Mappings and Low Frequency Analysis”
    • Citations: 43
  • “On the Stability of the Neptune Trojans”
    • Citations: 34
  • “Symmetric and Nonsymmetric Periodic Orbits in the Exterior Mean Motion Resonances with Neptune”
    • Citations: 32
  • “On the 2/1 Resonant Planetary Dynamics–Periodic Orbits and Dynamical Stability”
    • Citations: 31

 

 

 

 

Dr. Junming Li | Bayesian Machine Learning | Best Researcher Award

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Dr. Junming Li | Bayesian Machine Learning | Best Researcher Award

Dr. Junming Li, Shanxi University of Finance and Economics, China

Dr. Junming Li, an Associate Professor at the School of Statistics at Shanxi University of Finance and Economics, holds a Ph.D. in Geodesy and Survey Engineering from the Chinese Academy of Sciences, complemented by degrees from Tongji University. His research expertise focuses on Bayesian statistical methods and their applications, particularly in geospatial analysis and big data scenarios. Dr. Li leads significant projects on pollution and carbon reduction, funded by the National Social Science Fund of China, showcasing his leadership in managing complex research initiatives. His contributions to textbooks and scholarly works underscore his commitment to advancing statistical knowledge and education.

Professional Profile:

Google Scholar
Orcid

Suitability for the Award

Dr. Junming Li is an excellent candidate for the Research for Best Researcher Award. His work is at the intersection of statistics, environmental science, and public health, making significant contributions to both academic research and practical applications. His leadership in several high-impact research projects, coupled with his extensive publication record, demonstrates his commitment to advancing knowledge in his field.

Academic and Professional Achievements:

Dr. Li holds a Ph.D. in Geodesy and Survey Engineering from the prestigious Chinese Academy of Sciences, along with a Master’s and Bachelor’s degree from Tongji University. His solid academic background has laid the foundation for his research in geospatial analysis and statistics.

As an Associate Professor at the School of Statistics at Shanxi University of Finance and Economics, Dr. Li has been actively involved in both teaching and research, guiding students and contributing to the academic community through his expertise in Bayesian statistical methods and their applications.

Leadership in Research and Project Management:

Dr. Li is currently leading several significant research projects, including a study on pollution reduction and carbon reduction in China’s counties, funded by the National Social Science Fund of China. His role as the Principal Investigator in these projects demonstrates his leadership and ability to manage complex, multidisciplinary research endeavors.

His ongoing work on Bayesian statistical methods for complex spatiotemporal processes in big data scenarios highlights his innovative approach to tackling contemporary statistical challenges, further solidifying his reputation as a leading researcher in his field.

Publications and Scholarly Impact:

Dr. Li has contributed to key textbooks and scholarly works, including chapters in national textbooks and the authorship of a book on Bayesian Statistics. His ongoing efforts to write and publish works in this area indicate a continuous commitment to advancing knowledge and education in statistics.

Publication Top Notes:

  • Title: Spatiotemporal Evolution of Global Population Ageing from 1960 to 2017
    • Citations: 124
    • Year: 2019
  • Title: A Practical Split-Window Algorithm for Retrieving Land Surface Temperature from Landsat-8 Data and a Case Study of an Urban Area in China
    • Citations: 90
    • Year: 2015
  • Title: Globally Analysing Spatiotemporal Trends of Anthropogenic PM2.5 Concentration and Population’s PM2.5 Exposure from 1998 to 2016
    • Citations: 65
    • Year: 2019
  • Title: Assessing Impacts and Determinants of China’s Environmental Protection Tax on Improving Air Quality at Provincial Level Based on Bayesian Statistics
    • Citations: 49
    • Year: 2020
  • Title: Spatiotemporal Evolution of the Remotely Sensed Global Continental PM2.5 Concentration from 2000-2014 Based on Bayesian Statistics
    • Citations: 28
    • Year: 2018

 

 

 

 

Prof. Raed Abu Zitar | Machine Learning in Tracking | Best Researcher Award

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Prof. Raed Abu Zitar | Machine Learning in Tracking | Best Researcher Award

Prof. Raed Abu Zitar, Sorbonne University, United Arab Emirates

Prof. Zitar is a distinguished academic with a Ph.D. in Computer Engineering focused on Artificial Intelligence and Neural Networks from Wayne State University. With a robust background that includes a Master’s in Genetic Algorithms and a Bachelor’s in Electrical Engineering, he has had a notable career as a Senior Research Scientist and Chair of Excellence at the Sorbonne Center of Artificial Intelligence, Sorbonne University, Abu Dhabi. His research, which includes advanced work on drone detection and tracking, spans AI, machine learning, and robotics. Notable for his contributions to metaheuristic optimization and machine learning, Prof. Zitar has received prestigious awards such as the ASAI and UNESCO Fellowships, and has been recognized for his leadership and innovative work in the field.

Professional Profile:

Scopus
Orcid
Google Scholar

Suitability for the Research for Best Researcher Award

Prof. Raed Abu Zitar is a highly suitable candidate for the Research for Best Researcher Award due to his extensive expertise and significant contributions to the fields of Artificial Intelligence, Machine Learning, Robotics, and Computer Vision. His educational background includes a Ph.D. in Computer Engineering with a focus on Artificial Intelligence and Neural Networks from Wayne State University, complemented by a Master’s in Computer Engineering and a Bachelor’s in Electrical Engineering. This robust academic foundation underpins his diverse research interests and accomplishments.

Dean of Faculty of Computing and Engineering, Liwa College 🎓
Prof. Raed Abu Zitar is the Dean of the Faculty of Computing and Engineering at Liwa College, Abu Dhabi. He began this role in September 2024, leading the faculty in advancing computing and engineering education.

Academic Background 📚

Prof. Zitar holds a Ph.D. in Computer Engineering with a focus on Artificial Intelligence and Neural Networks from Wayne State University, where he explored machine learning with rule extraction. He also earned a Master’s in Computer Engineering with a specialization in Genetic Algorithms from North Carolina A&T State University and a Bachelor’s in Electrical Engineering from the University of Jordan.

Professional Experience 💼

Prof. Zitar has a distinguished career as a Senior Research Scientist and Chair of Excellence at the Sorbonne Center of Artificial Intelligence, Sorbonne University, Abu Dhabi, from February 2021 to September 2024. His work there focused on drone detection and tracking using advanced machine learning techniques. He was also the Founding Coordinator of the Master of Artificial Intelligence Program at Ajman University and managed the Teaching and Learning Center.

Research Interests and Contributions 🔬

His research spans various areas, including artificial intelligence, machine learning, robotics, computer networks modeling, and computer vision. He has published significant papers on the JAYA algorithm and renewable energy optimization techniques, demonstrating his expertise in metaheuristic optimization and advanced machine learning applications.

Awards and Recognitions 🏆

Prof. Zitar has received several prestigious awards, including the ASAI and UNESCO Fellowships. He was honored for supervising the Best Graduation Projects at Ajman University and received an Appreciation Award from CUCA University for his contributions to the Smart Learning Conference.

Innovations and Impact 🚀

Prof. Zitar’s extensive research and leadership in AI and machine learning have made a notable impact on the field. His work continues to influence advancements in energy optimization and computational methods, reflecting his commitment to pushing the boundaries of technology and education.

Publication Top Notes:

  1. Title: Wind, Solar, and Photovoltaic Renewable Energy Systems with and Without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
    • Citations: 104
    • Year: 2022
  2. Title: Gene Selection for Microarray Data Classification Based on Gray Wolf Optimizer Enhanced with TRIZ-Inspired Operators
    • Citations: 95
    • Year: 2021
  3. Title: Development of an Efficient Neural-Based Segmentation Technique for Arabic Handwriting Recognition
    • Citations: 88
    • Year: 2010
  4. Title: Multiclass Feature Selection with Metaheuristic Optimization Algorithms: A Review
    • Citations: 86
    • Year: 2022

 

 

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

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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 Master’s in Systems and Computer Engineering from Al-Azhar University, a Ph.D. in Information Technology from Cairo University, and a Professional Master’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 Profile🌍

Orcid
Scopus

Educational Background 🎓

Dr. Mohamed Ezzat Elhamahmy graduated from the Military Technical College in 1989 with a Bachelor’s degree in Electrical Engineering. He earned a Master’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 Master’s degree in Political Studies and Security from the Faculty of Economics and Political Science.

Professional Experience 💼

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 🏢

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 🛠️

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 🏅

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 🌟

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 Drones’ 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