Yuzhu Cai | Large language Model | Best Researcher Award

Dr. Yuzhu Cai | Large language Model | Best Researcher Award

Ph.D, Beihang University, China

Yuzhu Cai is a dedicated researcher and innovator in software engineering and information security, currently pursuing a Ph.D. at Beihang University, China. With a strong foundation in cryptography, AI-driven educational platforms, and password security, he has actively contributed to cutting-edge research and technology development. His entrepreneurial mindset is reflected in his co-founding of Han Hai Xing Tu Technology Co., Ltd., where he focuses on AI-based educational planning. His work has earned numerous national awards, recognizing his excellence in algorithm design, mathematical modeling, and cybersecurity innovations.

Publication Profile

Google Scholar

🎓 Education

Yuzhu Cai is currently a Ph.D. student in Software Engineering at Beihang University (2024 – Present). He holds a Bachelor of Science degree in Information Security from Nankai University (2020 – 2024) and pursued a Minor in Mathematics (2021 – 2023) at the same institution. His academic journey reflects a deep commitment to cybersecurity, cryptography, and artificial intelligence.

💼 Experience

Yuzhu has actively contributed to research and development through multiple high-impact projects. He worked on implementing large language models (LLMs) for script generation and ASR correction, releasing fine-tuned models trained on Chinese corpora. His research on password distribution analyzed security models and their economic impact, providing insights for future cryptographic advancements. Additionally, he developed HoneyCloud, a secure multi-cloud password manager leveraging threshold secret-sharing algorithms, which won prestigious cryptography awards. His entrepreneurial endeavors include the co-founding of Han Hai Xing Tu Technology Co., Ltd., an AI-driven educational planning platform.

🏆 Awards and Honors

Yuzhu Cai has received multiple national-level awards, showcasing his expertise in cybersecurity, cryptography, and algorithm design. His accolades include First Prize in the National Information Works Competition (Most Innovative and Entrepreneurial Value Award), First Prize in the National Cryptography Technology Competition, and First Prize in the Mathematical Modeling Competition (Tianjin Area). He also secured a Bronze Medal in the National Algorithm Design Challenge and received scholarships recognizing his innovation and academic excellence at Nankai University.

🔬 Research Focus

Yuzhu’s research primarily revolves around cybersecurity, cryptography, and artificial intelligence applications in software engineering. His work includes securing password distribution models, enhancing the security of cloud-based password managers, and exploring AI-driven educational platforms. His projects demonstrate a strong focus on improving security frameworks, understanding password economics, and applying LLMs to vertical fields. His contributions have implications for both theoretical advancements and real-world applications in cybersecurity and AI.

📚 Publications

Ethical-lens: Curbing malicious usages of open-source text-to-image models

Self-evolving multi-agent collaboration networks for software development

🔚 Conclusion

Yuzhu Cai is a forward-thinking researcher and entrepreneur whose contributions to cybersecurity, AI, and cryptography have earned national recognition. His innovative projects and publications showcase a deep understanding of security frameworks, AI applications, and cryptographic advancements. Through his Ph.D. research and entrepreneurial ventures, he continues to drive technological progress in software security and AI-driven solutions. 🚀

Sara Tehsin | Deep learning | Best Researcher Award

Ms. Sara Tehsin | Deep learning | Best Researcher Award

PhD Student, National University of Sciences and Technology, Islamabad, Pakistan

Sara Tehsin is a motivated and results-driven professional with over ten years of experience in Image Processing and Machine Learning. As an Engineering Lecturer at HITEC University in Taxila, Pakistan, she excels in delivering high-quality educational experiences and has a proven track record of producing outstanding results through her strong work ethic, adaptability, and effective communication skills. She is passionate about academic development and seeks opportunities to contribute her expertise while furthering her professional growth. 📚💻

Publication Profile

Google Scholar

Education

Sara Tehsin is currently pursuing a PhD in Computer Engineering at the National University of Sciences and Technology (NUST), Islamabad, where she has achieved a remarkable GPA of 3.83/4.00. Her research focuses on Digital Forensics, Deep Learning, and Digital Image Processing. She holds a Master’s degree in Computer Engineering from NUST, where she graduated with a GPA of 3.7/4.0, and a Bachelor’s degree from The Islamia University of Bahawalpur, with a GPA of 3.36/4.00. 🎓🌟

Experience

Sara has extensive teaching experience, currently serving as an Engineering Lecturer at HITEC University since September 2019, where she develops engaging curriculum and delivers lectures aligned with international standards. Previously, she was a Computer Science Lecturer at Sharif College of Engineering and Technology, and she also served as a Teaching Assistant at NUST and a Lab Engineer at Foundation University. Her roles have encompassed curriculum development, practical instruction, and student support in various computer science subjects. 👩‍🏫🔧

Research Interests

Sara’s research interests encompass Digital Forensics, Deep Learning, Digital Image Processing, and Machine Learning. She focuses on developing innovative solutions for image recognition and forgery detection, contributing significantly to the fields of computer vision and machine learning. Her work aims to enhance the accuracy and efficiency of image processing systems. 🧠🔍

Publications

Self-organizing hierarchical particle swarm optimization of correlation filters for object recognition
S. Tehsin, S. Rehman, M.O.B. Saeed, F. Riaz, A. Hassan, M. Abbas, R. Young, …
IEEE Access, 5, 24495-24502 (2017)
Cited by: 21

Improved maximum average correlation height filter with adaptive log base selection for object recognition
S. Tehsin, S. Rehman, A.B. Awan, Q. Chaudry, M. Abbas, R. Young, A. Asif
Optical Pattern Recognition XXVII, 9845, 29-41 (2016)
Cited by: 18

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments
S. Tehsin, S. Rehman, F. Riaz, O. Saeed, A. Hassan, M. Khan, M.S. Alam
Pattern Recognition and Tracking XXVIII, 10203, 28-39 (2017)
Cited by: 12

Comparative analysis of zero aliasing logarithmic mapped optimal trade-off correlation filter
S. Tehsin, S. Rehman, A. Bilal, Q. Chaudry, O. Saeed, M. Abbas, R. Young
Pattern Recognition and Tracking XXVIII, 10203, 22-37 (2017)
Cited by: N/A