Osmani Tito Corrioso | Cryptanalysis | Best Researcher Award

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Prof. Dr. Osmani Tito Corrioso | Cryptanalysis | Best Researcher Award

Auxiliar Professor, Básico Department Head, CUM Cárdenas/University of Matanzas, Cuba

🎓 Osmani Tito-Corrioso is a dedicated researcher and professor from Cuba specializing in cryptography and advanced mathematical sciences. With a robust background in cryptanalysis and genetic algorithms, he explores intricate fields such as coding theory, Gröbner bases, and applied differential equations. His contributions have significant implications in cryptographic security and algorithmic applications. Currently, he teaches at the University of Matanzas in the Department of Applied Mathematics and Physics.

Publication Profile

ORCID

Education

🎓 Osmani earned his B.Sc. in Mathematics from the University of Oriente in 2017, where he was awarded a Gold Title of B.Sc. for academic excellence. He furthered his expertise with an M.Sc. in Mathematical Science, specializing in Cryptography, from the University of Havana’s Cryptography Institute in 2021.

Experience

👨‍🏫 Osmani has taught extensively in Cuba, beginning at the University of Guantánamo (2017-2022) and currently serving as a professor in the Department of Applied Mathematics and Physics at the University of Matanzas. His teaching and research focus on cryptographic systems, block ciphers, and genetic algorithms.

Research Focus

🔍 Osmani’s research interests center on the security and analysis of block ciphers, cryptanalysis, and the genetic algorithm’s application in cryptography. His work also spans coding theory, algebraic structures like Gröbner bases, and applied cryptographic methods, contributing to enhancing digital security frameworks.

Awards and Honors

🏅 Osmani’s academic achievements include a Scientific Merit Award and the prestigious Gold Title of B.Sc. from the University of Oriente in 2017. He is also a member of the Cuban Society of Mathematics and Computation, reflecting his commitment to advancing mathematical research in Cuba.

Publication Top Notes

Combined and General Methodologies of Key Space Partition for the Cryptanalysis of Block Ciphers

On the Fitness Functions Involved in Genetic Algorithms and the Cryptanalysis of Block Ciphers

ATTACK TO BLOCK CIPHERS BY CLASS ELIMINATION USING THE GENETIC ALGORITHM

Roseline Ogundokun | Information Security | Women Researcher Award

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Dr. Roseline Ogundokun | Information Security | Women Researcher Award

Lecturer, Landmark University Omu-Aran, Nigeria

🎓 Dr. Roseline Oluwaseun Ogundokun is a dedicated academic and researcher who is passionate about advancing knowledge in Computer Science and solving real-world problems through Artificial Intelligence (AI), Machine Learning (ML), and Medical Imaging. She has a strong focus on interdisciplinary research and is driven to make impactful contributions to society through her work. With her vast experience in teaching and research, Dr. Ogundokun is shaping the next generation of computer scientists and engineers.

Publication Profile

Strengths for the Award:

  • Diverse Research Focus: Dr. Roseline Oluwaseun Ogundokun’s extensive research interests in Artificial Intelligence, Computer Vision, Deep Learning, and Medical Imaging positions her as a key contributor in fields with high impact. Her work in Machine Learning, Data Science, and Information Security also addresses pressing global issues.
  • Academic Excellence: With two Ph.D. pursuits—one completed in Computer Science and another ongoing in Multimedia Engineering—she exemplifies academic dedication. This diverse educational background reflects her determination to explore interdisciplinary solutions to real-world challenges.
  • Teaching Expertise: She has taught a wide range of courses, including Software Engineering Process, System Analysis, and Operating Systems, highlighting her role in shaping the next generation of computer scientists. Her teaching portfolio showcases versatility and depth in both foundational and advanced computing concepts.
  • Award-Winning Contributions: Dr. Ogundokun has received numerous awards, including a Cash Award for Poster Presentation at Deep Learning Indaba 2024 and multiple recognitions as a Top Nigerian Author on Scopus. These accolades emphasize her impact in both research and the academic community.
  • Global Collaborations: Her recent publications demonstrate global collaboration with researchers across countries, contributing to cutting-edge AI models, including the PulmoNet detection model for pulmonary diseases and a novel smartphone application for early disease detection. These innovations have potential for widespread societal benefits.

Areas for Improvement:

  • Focused Research Output: While Dr. Ogundokun has made notable contributions across several research domains, focusing on a few critical areas—such as medical imaging and AI for healthcare—could help solidify her standing as an expert and further boost her international recognition.
  • International Exposure: Although her research spans multiple countries, increasing participation in global conferences, particularly as a keynote speaker or panel expert, could elevate her visibility in the international research community.
  • Industry Collaboration: Strengthening collaborations with industry partners, particularly in AI-driven medical applications, would further highlight her work’s real-world impact and relevance.

Education

📚 Dr. Ogundokun holds multiple prestigious degrees, including a PhD in Computer Science from the University of Ilorin, Nigeria (2015-2022), and is currently pursuing another PhD in Multimedia Engineering from Kaunas University of Technology, Lithuania (2021-2025). She also earned an MSc in Computer Science from the University of Ilorin (2010-2013) and a BSc in Management Information System from Covenant University, Nigeria (2004-2008). Her academic journey reflects her continuous quest for excellence and specialization.

Experience

👩‍🏫 Dr. Ogundokun has taught numerous courses across computer science and software engineering, including topics such as Computer Programming, Software Engineering, Data Communication, and Medical Imaging. Her extensive teaching portfolio includes courses like System Analysis and Design, Operating Systems, and Data Management, showcasing her versatility in the field of computing and technology.

Research Focus

🔍 Dr. Ogundokun’s research interests span Artificial Intelligence, Computer Vision, Deep Learning, Medical Imaging, Machine Learning, Data Science, and Information Security. She is particularly focused on solving health-related problems through AI-driven models and systems, including pulmonary disease detection and sarcasm detection in social media through LSTM models.

Awards and Honours

🏅 Throughout her career, Dr. Ogundokun has received numerous awards, including a $250 Cash Award for Poster Presentation at the Deep Learning Indaba in Senegal (2024) and an Award of Recognition for her contributions as an SGD 4 Champion (2024). She has also been recognized multiple times as one of the top 500 Nigerian authors on Scopus and has been celebrated for her selfless service as a departmental exam officer.

Publication Top Notes

📝 Dr. Ogundokun has contributed significantly to the scientific community through her impactful publications. Notable works include research on deep learning for pulmonary disease detection, attention-based models for detecting sarcasm in social media, and the development of innovative AI-driven applications for healthcare.

“A Novel Insertion Solution for the Travelling Salesman Problem.” Computers, Materials & Continua. DOI: 10.32604/cmc.2024.047898
Cited by 12 articles.

“PulmoNet: A Novel Deep Learning Based Pulmonary Diseases Detection Model.” BMC Medical Imaging, 24(1), 51. Link
Cited by 8 articles.

“A Novel Smartphone Application for Early Detection of Habanero Disease.” Scientific Reports, 14(1), 1423. Link
Cited by 5 articles.

“Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media.” Computers, 12(11), 231. Link
Cited by 10 articles.

“Dark and Light Triad: A Cross-Cultural Comparison of Network Analysis in 5 Countries.” Personality and Individual Differences, 215, 112377. Link

Conclusion:

Dr. Roseline Oluwaseun Ogundokun is an outstanding candidate for the Research for Women Researcher Award. Her research, which addresses societal challenges through AI, machine learning, and medical technologies, aligns perfectly with the award’s goals. Her academic accomplishments, global research contributions, and numerous accolades underscore her potential to inspire future generations and drive meaningful change in technology and healthcare. Strengthening her international and industry engagements could further enhance her profile as a leading researcher.

 

Muhammad Asfand Hafeez | Information Security | Best Researcher Award

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Mr. Muhammad Asfand Hafeez | Information Security | Best Researcher Award

Research Assistant, Florida Atlantic University, United States

Muhammad holds a B.Sc. in Electrical Engineering from the University of Management and Technology, Lahore, Pakistan, with a CGPA of 3.89/4.00. He completed his M.Sc. in IT Convergence Engineering at Gachon University, South Korea, with a CGPA of 4.38/4.50, where he focused on GPU-based PQC implementations. He is now pursuing his Ph.D. at Florida Atlantic University with a perfect CGPA of 4.0/4.0. 🎓📚

Publication Profile

Strengths for the Award:

  1. Outstanding Academic Record: Muhammad Asfand Hafeez has demonstrated exceptional academic performance, with a CGPA of 4.0/4.0 in his PhD program and a CGPA of 4.38/4.50 in his Master’s program, showcasing his dedication and excellence in his studies.
  2. Innovative Research Contributions: His research in GPU-based implementations of Post-Quantum Cryptography (PQC) algorithms for IoT applications and side-channel analysis exhibits a strong focus on cutting-edge technologies and practical applications. This includes significant contributions to improving security protocols in emerging technologies.
  3. High-Impact Publications: Hafeez has a robust publication record in reputable journals and conferences, including IEEE Internet of Things Journal and IEEE Access. His work on GPU acceleration and cryptographic methods is relevant to current and future research in security and optimization.
  4. Awards and Recognition: He has received multiple awards such as the Rector Innovation Award, Patron’s Medal, and Best Paper Award, indicating recognition from academic and industry peers for his innovative work and contributions.
  5. Diverse Experience: His experience spans research assistant roles in various prestigious institutions and internships, providing him with a broad perspective and expertise in different aspects of electrical engineering and computer science.

Areas for Improvement:

  1. Broader Research Impact: While his research is highly specialized, expanding his work to address a wider range of practical problems and applications could further enhance its impact and relevance to diverse fields.
  2. Collaborative and Interdisciplinary Work: Increasing collaboration with researchers from other disciplines or institutions could lead to more comprehensive research outcomes and foster interdisciplinary innovations.
  3. Public Engagement and Dissemination: Greater emphasis on public outreach and dissemination of his research findings through non-academic channels could raise awareness and highlight the societal impacts of his work.

 

Experience

Muhammad has gained substantial research experience through his roles as a Research Assistant at various esteemed institutions, including ISCAAS Lab at Florida Atlantic University, Kansas State University, and Information Security & Machine Learning Lab at Gachon University. His internships and assistant roles have provided him with practical insights into electrical engineering and information security. 🧪💼

Research Focus

Muhammad’s research interests include GPU computing, Post-Quantum Cryptography (PQC), cryptographic protocols, and secure multi-party computation. He is dedicated to enhancing the efficiency and security of cryptographic systems and optimizing deep learning models. His work also encompasses side-channel analysis and applications of PQC in IoT. 💻🔒

Awards and Honors

Muhammad has been honored with several prestigious awards, including the Rector and Dean Merit Awards, the Rector Innovation Award, and the Patron’s (Gold) Medal Award. He has also achieved notable positions in competitions such as IEEE Xtreme Programming and Mechnofest. His recognition includes the Best Paper Award by BK21 FAST Intelligence Convergence Center and accolades from the Pakistan International Auto Show. 🏅🎖️

Publications Top Notes

Efficient TMVP-Based Polynomial Convolution on GPU for Post-Quantum Cryptography Targeting IoT Applications (2024) – IEEE Internet of Things Journal

GPU-Accelerated Deep Learning-based Correlation Attack on Tor Networks (2023) – IEEE Access

High Throughput Acceleration of Scabbard Key Exchange and Key Encapsulation Mechanism Using Tensor Core on GPU for IoT Applications (2023) – IEEE Internet of Things Journal

H-QNN: A Hybrid Quantum–Classical Neural Network for Improved Binary Image Classification (2024) – AI

A Low-Overhead Countermeasure Against Differential Power Analysis for AES Block Cipher (2021) – Applied Sciences

Performance Improvement of Decision Tree: A Robust Classifier Using Tabu Search Algorithm (2021) – Applied Sciences

A Hybrid Linear Quadratic Regulator Controller for Unmanned Free-Swimming Submersible (2021) – Applied Sciences

Conclusion:

Muhammad Asfand Hafeez is a highly promising candidate for the Best Researcher Award due to his exemplary academic achievements, innovative research contributions, and significant awards and recognitions. His work in GPU-based implementations of Post-Quantum Cryptography and other advanced areas reflects a deep understanding of and commitment to his field. Addressing areas for improvement, such as broadening the scope of his research impact and increasing public engagement, could further enhance his candidacy and contributions to the field.

GAN XU | Computer Science | Best Researcher Award

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Mr. GAN XU | Computer Science | Best Researcher Award

PhD. candidate, capital university of economics and business, China

Xu Gan is a Doctoral student at Capital University of Economics and Business, Beijing, specializing in Rural Finance, Financial Theory and Policy, and Supply Chain Finance. With a solid academic background and practical experience, Xu has contributed significantly to research in financial services and blockchain technology. 🏛️📚

Profile

Scopus

 

Education

Xu Gan completed a Master of Finance from Capital University of Economics and Business in Beijing (2018-2021) and a Bachelor of Biotechnology from Beijing Union University (2006-2010). Xu also has an extensive academic background in these fields, providing a strong foundation for research and analysis. 🎓📈

Experience

Xu has actively participated in several high-profile research projects, including the National Social Science Foundation of China’s research on rural financial services and the China Mobile Communication Federation’s blockchain technology applications in finance. Xu was responsible for designing research sub-topics and writing research reports. 📊🔬

Research Interests

Xu Gan’s research interests include Rural Finance, Financial Theory and Policy, and Supply Chain Finance. Xu is focused on improving rural financial services and exploring innovative financial technologies such as blockchain. 🌾💡

Awards

Xu has been recognized for academic excellence with several honors: Beijing Outstanding Graduates (2020), Outstanding Graduate of Beijing Union University (2020), and several awards for excellent papers at various financial and rural finance forums. 🏅📜

Publications

Yang, GZ., Xu, G., Zhang, Y., et al. Financial density of village banks and income growth of rural residents. Economic Issues, 2021, 504(08): 89-94.

Zhang, F., Xu, G., Zhang, XY, Cheng, X. Knowledge mapping analysis of seven decades of rural finance research in China. Rural Finance Research, 2020(01): 10-20.

Zhang, F., Xu, G., Cheng, X. A review of blockchain applications in the financial sector. Technology for Development, 2019, 15(08): 865-871.

Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

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Dr. Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

Shenzhen University, China

🎓 Dr. H. Sadia Nawaz is a distinguished researcher and academic in Computer Vision, with a Ph.D. from Ocean University of China. Her work focuses on Temporal Activity Detection using Natural Language. With a background in both teaching and research, she has contributed significantly to the field of computer vision and continues to pursue a career as a postdoctoral researcher. Her extensive knowledge and dedication to the subject make her a valuable asset to any research group.

Profile

Scopus

 

Education

📚 Dr. H. Sadia Nawaz holds a Ph.D. in Computer Science from Ocean University of China, specializing in Temporal Moment Localization using Natural Language. She also completed her Master’s in Information Science and Technology at the University of Sargodha and an MS in Computer Science and Technology with a focus on Cyber Security at the University of Lahore. Her academic background provides a strong foundation for her research and teaching roles.

Experience

💼 Dr. Nawaz has a robust teaching background, having served as a Programming Teaching Assistant at Heriot-Watt University and Ocean University of China, and as a Computer Science Lecturer at Superior University of Lahore and the University of Sargodha. Her roles in academia have honed her skills in teaching, mentoring, and research, contributing to her expertise in computer vision and machine learning.

Research Interests

🔍 Dr. Nawaz’s research interests include Activity Localization in Videos via Language, Temporal Moment Detection, and Natural Language Processing. She is particularly focused on moment detection in complex scenarios and the integration of machine learning methods with computer vision techniques to enhance video understanding and activity localization.

Awards

🏅 Dr. H. Sadia Nawaz has been recognized for her research contributions in the field of computer vision, particularly for her work on Temporal Moment Localization using Natural Language. Her research has been published in high-impact journals, reflecting her expertise and commitment to advancing the field.

Publications

Temporal Moment Localization via Natural Language by Utilizing Video Question Answers as a Special Variant and Bypassing NLP for Corpora

IVTEN – Integration of Visual-Textual Entities for Temporal Activity Localization via Language in Video

Revelation of Novel Paradigm in Temporal Moment Localization by Using Natural Language in Video

Multi-level Edges and Context Arranger Architecture Using Referencing Expressions for Temporal Moment Localization via Natural Language

A Frame-Based Feature Model for Violence Detection from Surveillance Cameras Using ConvLSTM Network