Mr. Xiang Fang | Ransomware detection | Best Researcher Award

Posted on by Computer Scientists Awards

Mr. Xiang Fang | Ransomware detection | Best Researcher Award

Phd student, The City College of New York, United States.

Xiang Fang is a dedicated and technically proficient researcher in electrical and computer engineering, currently pursuing his Ph.D. at The City College of New York. With a multifaceted background combining hardware, software, cybersecurity, and AI-powered applications, Xiang stands out for his innovative approaches to problem-solving, especially in areas like control systems, image processing, and ransomware detection. His contributions span multiple international presentations, academic projects, and scholarly publications, reflecting a deep passion for research and a commitment to academic excellence. 🌍🔬

Publication Profile

Google Scholar

🎓Education Background

Xiang earned his Ph.D. in Electrical Engineering from The City College of New York (2020–2025), maintaining an impressive GPA of 3.60. Complementing his technical expertise, he acquired an MBA from Academic Europe Open University in April 2025, equipping him with valuable leadership and management skills. His journey began with an M.Sc. in Electrical and Computer Engineering from Purdue University Northwest (2017–2019), followed by a B.Sc. in Electrical and Information Engineering from Shaanxi University of Technology, China (2013–2017). 🎓📘📈

💼Professional Experience

Xiang has actively contributed to academia through teaching assistantships and tutoring roles. At The City College of New York, he worked as a Teaching Assistant for Healthcare Cybersecurity Pathways (2023) and graded Communication Theory (2025). His earlier experience includes tutoring English to middle school students (2013–2014). In research, he has led and contributed to multiple technical projects—ranging from digital image enhancement and SLAM systems to cloud-based secure applications and real-time ransomware detection using anomaly-based methods. 💡🖥️🧪

🏅Awards and Honors

Xiang’s commitment to excellence is reflected in his achievements, including the Certificate of Completion in Children and Climate Change, and the CodePath Cybersecurity Course Certificate. His research has been widely recognized through poster presentations at prestigious forums such as AFRL-CUNY, The Grove School of Engineering Expo, and the Defense & Intelligence Research Forum. 🏆📜🎖️

🔍Research Focus

Xiang’s primary research interests lie in cybersecurity, autonomous systems, signal processing, and AI-powered detection systems. His standout contributions include anomaly-based and honeyfile-based detection mechanisms for crypto ransomware, SLAM systems, and data visualization methods. Leveraging tools like MATLAB, Python, Kalman filters, and machine learning models such as LSTM, Xiang effectively bridges theoretical concepts with practical implementations. 🔐🤖📊

🔚Conclusion

A forward-thinking and results-driven scholar, Xiang Fang exemplifies the blend of innovation, technical acumen, and academic rigor. His trajectory, from hands-on hardware projects to advanced research in digital security, positions him as a rising star in the field of electrical and computer engineering. As he continues his journey, Xiang remains committed to tackling emerging global challenges with smart, scalable, and secure solutions. 🚀📡🌐

📚Top Publications Notes

  1. Crypto-Ransomware Detection Through a Honeyfile-Based Approach with R-Locker
    📅 Published: 2025 | 📘 Journal: MDPI, Mathematics | 📑 Cited by: 5 articles (as of 2025)

  2. Poster: Crypto Ransomware Detection Through a Honeyfile-Based Approach with R-Locker
    📅 Presented: Feb. 2025 | 📍 The Grove School of Engineering Expo, NY, USA

  3. Poster: Anomaly-Based Approach for Crypto Ransomware Detection
    📅 Presented: Nov. 2023 | 📍 AFRL-CUNY Technology and Workforce Development Forum

  4. Poster: Ransomware Detection Methodology
    📅 Presented: May 2022 | 📍 Defense & Intelligence Research Forum, NY, USA

  5. Thesis: Visualization of Mobile Robot Localization and Mapping
    📅 Published: April 2017 | 📍 Purdue University Northwest

  6. Thesis: Design of High-Precision Laser Engraving Platform Control System Based on STC12C5608AD
    📅 Published: June 2017 | 📍 Shaanxi University of Technology

 

Muhammad Asfand Hafeez | Information Security | Best Researcher Award

Posted on by Computer Scientists Awards

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.