Muhammad Bilal Mahmood | Security | Best Researcher Award

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Mr. Muhammad Bilal Mahmood | Security | Best Researcher Award

PhD Scholar, Dalian University of Technology, China

Muhammad Bilal Mahmood is a dedicated researcher and educator in Software Engineering, currently pursuing his Ph.D. at Dalian University of Technology, China 🎓. With a strong foundation in Computer Engineering and extensive expertise in machine learning, natural language processing, and cybersecurity, he has contributed significantly to academia and research. As a lecturer at The University of Lahore, Pakpattan Campus, since 2017, he has been instrumental in shaping young minds and fostering innovation 💡. His research interests include deep learning, facial expression recognition, and AI-driven cybersecurity solutions.

Publication Profile

ORCID

📚 Education

Muhammad Bilal Mahmood’s academic journey reflects his passion for cutting-edge technology and innovation 🚀. He is currently a Ph.D. candidate in Software Engineering (2021–2025) at Dalian University of Technology, China. Prior to this, he earned his MS in Computer Engineering from NUST College of Electrical & Mechanical Engineering, Rawalpindi, Pakistan (2015) 🎓. His undergraduate studies in Computer System Engineering were completed at NFC Institute of Engineering & Technological Training, Multan, Pakistan (2011), laying the groundwork for his expertise in programming and research.

💼 Experience

With over six years of academic and research experience, Muhammad Bilal Mahmood has been serving as a Lecturer at The University of Lahore, Pakpattan Campus, since 2017 🏫. His responsibilities include developing system requirement specifications, designing databases, programming under strict coding guidelines, and ensuring seamless project management 📊. His ability to mentor students and collaborate with fellow researchers has made him a valuable asset in the field of software engineering.

🏆 Awards and Honors

Throughout his career, Muhammad Bilal Mahmood has been recognized for his contributions to research and academia 🏅. His innovative work in deep learning, NLP, and cybersecurity has earned him appreciation within the research community. His expertise in artificial intelligence-driven security solutions has led to impactful publications, making significant contributions to advancing technological frontiers.

🔬 Research Focus

Muhammad Bilal Mahmood’s research primarily revolves around artificial intelligence, deep learning, and cybersecurity 🔍. His work includes speech emotion recognition, malicious package detection in PyPI, and facial expression analysis using convolutional neural networks 🤖. He has also contributed to medical image processing, topic discovery in health data, and chatbot development for university applications. His interdisciplinary research bridges the gap between AI and real-world applications, improving human-computer interactions.

📝 Conclusion

Muhammad Bilal Mahmood is a passionate researcher, educator, and software engineer dedicated to advancing AI-driven solutions and cybersecurity methodologies 💡. His commitment to academia, combined with his innovative research projects, makes him a valuable contributor to the field. Through his teaching and research, he continues to inspire the next generation of engineers and scientists, pushing the boundaries of technological advancements. 🚀

📄 Publications

Recognizing Semi-Natural and Spontaneous Speech Emotions Using Deep Neural Networks – This research explores deep learning-based speech emotion recognition to enhance human-computer interaction. [Published in: Journal Name, Year] 📜🔗

PypiGuard: A novel meta-learning approach for enhanced malicious package detection in PyPI through static-dynamic feature fusion – This paper introduces a cutting-edge security framework for detecting malicious packages in Python’s package repository. [Published in: Journal Name, Year] 📜🔗

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.