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

Sherbaz Khan | Artificial Neural Networks | Best Researcher Award

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Sherbaz Khan | Artificial Neural Networks | Best Researcher Award

Dr. Sherbaz Khan, Jinnah University for Women, Pakistan.

Sherbaz Khan is a dedicated academician and researcher with over a decade of experience in teaching and research across prominent universities in Pakistan. He holds a Ph.D. in Management Sciences and specializes in research methods, marketing, and management. He is the Head of the Business Administration Department at Jinnah University for Women, where he teaches graduate and postgraduate students. His research interests span various qualitative and quantitative methods, including SEM, Artificial Neural Networks (ANN), and Fuzzy Inference Systems (FIS). Dr. Khan has a passion for fostering a research culture and has contributed significantly to student development. 📚🎓📊

Publication Profiles

Orcid
Scopus

Education and Experience

  • Ph.D. in Management Sciences, Greenwich University (Nov 2023) 🎓
  • MBA in Management Sciences (Marketing), Greenwich University (2013) 💼
  • BBA in Management Sciences (Marketing), Greenwich University (2010) 💼
  • Associate Professor & Head of Department, Jinnah University for Women (2024-Present) 🏫
  • Research Faculty/Managing Editor, CBM-IoBM (2023) 📝
  • Faculty & Supervisor, Jinnah University for Women (2019-2023) 🏫
  • Associate Editor/Research Supervisor, SZABIST (2015-2018) 📖
  • Research Coordinator, Greenwich University (2013-2015) 🔬

Suitability For The Award

Dr. Sherbaz Khan, a seasoned academician and researcher, has over a decade of experience in teaching and research at prestigious institutions. With a Ph.D. in Management Sciences, his expertise spans SEM, Fuzzy Inference Systems, Artificial Neural Networks, and Multi-Group Analysis. Currently serving as Head of the Department at Jinnah University for Women, he has supervised numerous research projects, advanced academic standards, and contributed significantly to research culture, making him an exceptional candidate for the Best Researcher Award.

Professional Development

Sherbaz Khan is committed to continuous professional development in the field of academic research and teaching. He regularly participates in workshops and research methodology seminars, which have helped enhance his teaching practices and research supervision skills. Khan’s development includes extensive experience in using advanced research tools such as SPSS, NVIVO, and Smart PLS, empowering students with quantitative and qualitative research skills. His role as a faculty member has enabled him to mentor students in research methods and thesis writing, significantly contributing to their academic success. Additionally, his leadership as Head of Department has nurtured a research-driven environment. 📈👨‍🏫📊

Research Focus

Publication Top Notes

  • The impact of the enablers of green supplier selection and procurement on supply chain performance (2024)
    International Journal of Procurement Management, 21(3), pp. 349–377 📈
  • The effect of religiosity, materialism and self-esteem on compulsive and impulsive buying behavior (2024)
    Journal of Islamic Marketing 💸
  • A grey decision-making trial and evaluation laboratory model for digital warehouse management in supply chain networks (2023)
    Decision Analytics Journal, 8, 100293 🔍 (19 citations)
  • Designing a knowledge-based system (KBS) to study consumer purchase intention: the impact of digital influencers in Pakistan (2023)
    Kybernetes, 52(5), pp. 1720–1744 📱
  • Supply Chain Resilience During Pandemic Disruption: Evidence from the Healthcare Sector of Pakistan: Evaluating Demand and Supply Chain Resilience (2023)
    Understanding Complex Systems, Part F1776, pp. 235–254 🌍
  • Phenomenological Study of Pharmaceutical Supply Chain in Pakistan: Innovative Approaches to Minimize Operational Inefficiencies (2023)
    Understanding Complex Systems, Part F1776, pp. 211–233 💊
  • Obstacles in Disruption and Adoption of Green Supply Chain Management (GSCM) Practices by Manufacturing Industries (2023)
    Understanding Complex Systems, Part F1776, pp. 153–179 🌱
  • The role communication, informativeness, and social presence play in the social media recruitment context of an emerging economy (2023)
    Cogent Business and Management, 10(3), 2251204 📢

Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

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Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools. 🌐📊🔬

Publication Profiles

Googlescholar

Education and Experience

Education

  • 🎓 Ph.D. in Information Technology, University of Nebraska, 2010
  • 🎓 M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • 🎓 B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • 📚 Tenured Associate Professor, Penn State Great Valley (2019–Present)
  • 📚 Assistant Professor, Penn State Great Valley (2013–2019)
  • 🔬 Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011–2013)
  • 💻 Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010–2011)
  • 🛠️ Project Assistant, IIT Kharagpur (2001–2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship. 🌟🔍

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work in data mining and machine learning aims to uncover patterns and develop predictive models for diverse applications. In bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends to cybersecurity, where he explores cryptographic techniques to enhance internet security, and distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridges artificial intelligence, predictive analytics, and software engineering to create impactful solutions. 🌐🔬📊

Awards and Honors

  • 🏆 Awarded research grants for innovative bioinformatics tools.
  • 📜 Recognized for contributions to cybersecurity and internet authentication.
  • 🌟 Acknowledged as a leading researcher in predictive analytics and machine learning.
  • 📊 Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detection  – Cited by 93, 2021 📊📚
  • LocSigDB: A database of protein localization signals  – Cited by 49, 2015 🧬📖
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genes– Cited by 46, 2020 🧪📊
  • Mining for class-specific motifs in protein sequence classification – Cited by 29, 2013 🔬📜
  • Web app security: A comparison and categorization of testing frameworks– Cited by 27, 2017 🔒🖥️
  • MetaID: A novel method for identification and quantification of metagenomic samples – Cited by 23, 2013 🌍🔍
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellers – Cited by 21, 2019 ✈️🧠
  • Cybersecurity for AI systems: A survey – Cited by 20, 2023 🤖🔐

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. Julius Olaniyan | Machine Learning Award |Best Researcher Award

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Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

Dr. Julius Olaniyan, Bowen University, Nigeria 

Olaniyan Julius in Odo-Owa, Kwara State, Nigeria. He is a Lecturer II in the Computer Science Department at Bowen University, Iwo, Osun State, Nigeria. Julius holds a Ph.D. in Computer Science (2023) and has extensive experience in software development, data analysis, and teaching. He has worked in several institutions, including Landmark University, Federal Polytechnic Auchi, and Feghas Solutions Ltd. Over his career, he has developed various applications using programming languages such as C, C++, Java, Python, and PHP. Julius specializes in Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation. A devoted husband and father of three, Julius is passionate about advancing AI and its application in healthcare and education. He has contributed to several innovative research papers in the field of computer science and AI.

Professional Profile:

Google Scholar

Summary of Suitability for Award:

Dr. Olaniyan has demonstrated outstanding proficiency and expertise in the fields of Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation, with a solid academic background in Computer Science. He holds a Ph.D. in Computer Science from Landmark University, and has published extensively in high-impact journals and conferences. His work on cataract detection using deep learning, as well as his innovative contributions in areas like speech refinement and emotion recognition, highlights his commitment to advancing technology for real-world applications. Furthermore, his ability to collaborate across interdisciplinary research teams and contribute to several peer-reviewed articles reflects his academic rigor and leadership.

🎓Education: 

Olaniyan Julius completed his Ph.D. in Computer Science at Landmark University (2023). He also holds a Master’s in Computer Science (M.Tech) from the Federal University of Technology, Akure (2019), where he also earned a Postgraduate Diploma (PGD) in 2012. Julius started his academic journey with a Bachelor’s in Computer Science from the Federal University of Oye Ekiti (2022). His earlier qualifications include a Higher National Diploma (HND) in Computer Science from Auchi Polytechnic (2006), and a National Diploma (ND) in the same field (2000). Julius completed his Secondary Education at Orota Community High School, Odo-Owa (1994) and his Primary Education at St. Thomas Catholic School (1988). His strong educational foundation in Computer Science has shaped his successful academic and professional career.

🏢Work Experience:

Olaniyan Julius has a diverse career in academia and industry. He is currently a Lecturer II at Bowen University, Nigeria. Previously, he served as a Lecturer II at Landmark University (2023-2024) and as a Data Analyst at Federal Polytechnic Auchi (2013-2022). His industry experience includes working as a Software Developer/Business Developer at Feghas Solutions Ltd. (2009-2012) and a Tutor/Application Developer at Pesoka Systems Ltd. (2008). Julius also has teaching experience from his time as a Lecturer during his NYSC service at Maritime Academy of Nigeria (2007-2008). His early career included roles like Data Processing Officer at Ajaokuta Steel Company (2002-2004) and School Database Admin at Sani Bello Secondary School (2001). Julius’s experience spans academic teaching, research, software development, data analysis, and project management.

🏅Awards:

Olaniyan Julius has received numerous accolades throughout his academic and professional journey. His Ph.D. dissertation was highly recognized, contributing to his recognition as an emerging scholar in Computer Science. He was awarded a best student award during his time at Landmark University and has been recognized by the Federal Polytechnic Auchi for his outstanding performance as a Data Analyst. Julius’s commitment to education and research has earned him several institutional commendations for his efforts in developing AI-driven solutions in healthcare and education. His research in Artificial Intelligence and Machine Translation has garnered him recognition at international conferences. He is also an active member of several professional organizations in computer science and artificial intelligence. Julius’s leadership and contributions to academic and professional initiatives have cemented his reputation as a passionate educator and researcher.

🔬Research Focus:

Olaniyan Julius specializes in Artificial Intelligence (AI), with a focus on Computer Vision, Natural Language Processing (NLP), and Machine Translation. His work primarily involves using deep learning techniques to create solutions for healthcare (e.g., cataract detection) and education (e.g., student performance evaluation). Julius is dedicated to developing hybrid AI models that combine traditional methods with transformative learning approaches. His research in audio signal denoising and speech-to-speech translation aims to enhance communication and multilingual interaction. He is passionate about designing AI-powered systems that can automate and optimize processes, improving outcomes in health diagnostics and online learning environments. Julius’s work on emotion detection in virtual classrooms and the integration of CNN models for speech emotion recognition represents a significant contribution to the AI field. His interdisciplinary research approach holds promise for real-world AI applications in various domains.

Publication Top Notes: 

  • “Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media”
  • “Implementation of Audio Signals Denoising for Perfect Speech-to-Speech Translation Using Principal Component Analysis”
  • “Advancements in Accurate Speech Emotion Recognition Through the Integration of CNN-AM Model”
  • “Transformative Transparent Hybrid Deep Learning Framework for Accurate Cataract Detection”
  • “Parallel Attention Driven Model for Student Performance Evaluation”

 

 

 

 

Mr. Zushuang Liang | Salient Object Detection | Best Researcher Award

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Mr. Zushuang Liang | Salient Object Detection | Best Researcher Award

Mr. Zushuang Liang, Harbin Institute of Technology, China

Mr. Zushuang Liang is a graduate student at the Harbin Institute of Technology, specializing in Computer Vision with a focus on Salient Object Detection and Graph Neural Networks (GNNs). His innovative research, including the development of a multi-scale graph attention network for video detection, holds promising applications in areas such as autonomous driving and surveillance. Additionally, Mr. Liang explores interdisciplinary work by integrating machine learning with music technology through piano polyphonic transcription, showcasing his versatility and contribution to both fields.

Professional Profile:

Orcid

Suitability for the Best Researcher Award:

Mr. Liang’s work is not only technically innovative but also highly impactful. His contributions to video salient object detection with applications that extend to fields like autonomous driving, surveillance, and multimedia retrieval make him a deserving candidate for the Best Researcher Award. His interdisciplinary approach, combining machine learning with music technology, further distinguishes him as a forward-thinking researcher.

Educational Background:

He earned his Bachelor’s Degree from the Harbin Institute of Technology and is currently pursuing a Master’s degree at the same institution, within the School of Electronics and Information Engineering.

Area of Specialization:

Mr. Zushuang Liang specializes in Computer Vision with a focus on Salient Object Detection and Graph Neural Networks (GNNs). His work revolves around enhancing video detection accuracy by applying innovative techniques in multi-scale graph attention networks.

Research & Contributions:

His pioneering research includes developing the multi-scale graph attention network for video salient object detection, with potential applications in autonomous driving and surveillance. Additionally, he bridges disciplines by working on piano polyphonic transcription, integrating machine learning with music technology.

Publication Top Notes:

Title: DAFE-MSGAT: Dual-Attention Feature Extraction and Multi-Scale Graph Attention Network for Polyphonic Piano Transcription
  • Year: 2024

 

 

Dr. Roseline Ogundokun | Intrusion Detection System | Best Researcher Award

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Dr. Roseline Ogundokun | Intrusion Detection System | Best Researcher Award

Dr. Roseline Ogundokun, Landmark University Omu-Aran, Nigeria

Roseline Oluwaseun Ogundokun is a distinguished academic and researcher in computer science, born in Zaria, Nigeria. Currently serving as a lecturer and researcher at Landmark University, she specializes in machine learning, artificial intelligence, and computer vision. With a strong commitment to education and innovative research, Roseline has made significant contributions to advancing sustainable development goals through technology. She is also involved in mentoring students in STEM fields and has a passion for fostering future generations of scientists.

Professional Profile

Google Scholar

Researcher Suitability Summary for the Best Researcher Award: Roseline Oluwaseun Ogundokun

Based on her extensive research output, significant contributions to academia, and commitment to mentoring and inclusive practices, Dr. Roseline Oluwaseun Ogundokun is an exemplary candidate for the Best Researcher Award. Her work not only advances the field of Computer Science but also positively impacts society through innovative solutions. Recognizing her achievements with this award would honor her contributions and inspire further excellence in research and education.

🎓 Education

Roseline’s academic journey began with a Bachelor’s degree in Management Information Systems from Covenant University, followed by a Master’s in Computer Science from the University of Ilorin. She is currently pursuing dual PhDs in Computer Science and Multimedia Engineering, expected to be completed in 2022 and 2025, respectively. Her diverse educational background has equipped her with a strong foundation in both theoretical and practical aspects of technology, enabling her to contribute effectively to her field.

 💼 Experience

Roseline has extensive experience in academia, having worked at Landmark University since 2015 as a researcher, lecturer, and administrator. She has taught various courses, including Computer Programming and Software Engineering, while also supervising numerous undergraduate and postgraduate students in innovative research projects. Additionally, she has served as a visiting lecturer at Thomas Adewumi University and the Nigerian Army College of Education, contributing to the development of future tech leaders through her teaching and mentorship.

🏅 Awards and Honors

Roseline’s commitment to research and education has earned her multiple accolades. She has been recognized for her contributions to machine learning and sustainable development, receiving awards from various educational institutions. Her research publications have garnered significant attention, leading to an impressive citation record, reflecting her influence in the academic community. She is also actively involved in mentorship programs, advocating for women’s participation in STEM fields.

🌍 Research Focus

Roseline’s research interests are centered on artificial intelligence, computer vision, and deep learning. She is particularly focused on employing machine learning models to solve real-world problems across various sectors, including healthcare and telecommunications. Her work aims to advance the integration of technology in achieving sustainable development goals, particularly those related to industry, innovation, and infrastructure.

 📖 Publication Tob Notes

Predictive modelling of COVID-19 confirmed cases in Nigeria
Citation Count: 132
IoMT-based wearable body sensors network healthcare monitoring system
Citation Count: 99
Medical internet-of-things based breast cancer diagnosis using hyperparameter-optimized neural networks
Citation Count: 84
Application of big data with fintech in financial services
Citation Count: 78
An enhanced intrusion detection system using particle swarm optimization feature extraction technique
Citation Count: 62

Prof. Orken Mamyrbayev | Computing Awards | Outstanding Scientist Award

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Prof. Orken Mamyrbayev | Computing Awards | Outstanding Scientist Award

Prof. Orken Mamyrbayev, Institute of Information and Computational Technologies, Kazakhstan

Orken Zhumazhanovich Mamyrbayev  in the Almaty region, is an Associate Professor and Ph.D. in Information Systems. He graduated from Abay Kazakh National Pedagogical University in 2001 with a degree in Computer Science. With over 18 years of experience in scientific and pedagogical work, he currently serves as Deputy Director for Science at the Institute of Information and Computational Technologies under the Ministry of Education and Science of Kazakhstan. He is a specialist in speech recognition, digital signal processing, and natural language processing, and has supervised numerous Ph.D. and master’s theses. Mamyrbayev has authored over 100 scientific papers, holds 2 patents, and has completed advanced training in several countries, including Japan, Azerbaijan, and Malaysia. He is an active member of various scientific councils and an academician of the International Academy of Informatization.

Professional Profile:

Orcid

Suitability of Mamyrbayev Orken Zhumazhanovich for the Research for Outstanding Scientist Award

Summary of Suitability:

Mamyrbayev Orken Zhumazhanovich is a highly suitable candidate for the Research for Outstanding Scientist Award due to his extensive contributions to computer science, his leadership in research projects with real-world applications, and his international recognition. His innovative work in speech recognition, natural language processing, and digital signal processing showcases his potential as a leader in scientific advancements. Additionally, his contributions to education and the mentorship of upcoming researchers further strengthen his candidacy for this prestigious award.

🎓Education:

Orken Zhumazhanovich Mamyrbayev graduated from Abay Kazakh National Pedagogical University in 2001 with a degree in Computer Science and Computerization Management. In 2014, he earned his Ph.D. in Information Systems, successfully defending his dissertation on the topic “Kazakh Speech Recognition Modal System.”

🏢Work Experience:

From 2002 to 2011, Orken Zhumazhanovich Mamyrbayev worked as a Senior Lecturer at the Department of Computer Science and Applied Mathematics at Abay Kazakh National Pedagogical University. From 2012 to 2015, he served as a Researcher at the Laboratory of “Analysis and Modeling of Information Processes.” Since 2015, he has held the position of Deputy Director for Science at the Institute of Information and Computational Technologies under the Ministry of Education and Science of Kazakhstan. Additionally, since 2017, he has been leading the Laboratory of Computer Engineering of Intelligent Systems at the same institute.

🏅Awards:

Orken Zhumazhanovich Mamyrbayev has been recognized for his contributions to science and education, receiving the prestigious Certificate of Honor from the Ministry of Education and Science of Kazakhstan. In addition, he has been awarded letters of gratitude from the Institute of Information and Computational Technologies, CS MES RK, for his valuable work and dedication.

Publication Top Notes:

  • A Study of Kazakh Speech Recognition in Hiformer Model
  • An Innovative Technology for Overloading Microshoots in Vitro
  • Enhancing Emoji-Based Sentiment Classification in Urdu Tweets: Fusion Strategies with Multilingual BERT and Emoji Embeddings
  • High Accuracy Microcalcifications Detection of Breast Cancer Using Wiener LTI Tophat Model
  • Infrared Laser Irradiation for Pre-Sowing Seed Treatment: Advancing Germination and Crop Productivity