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
🎓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
-
Crypto-Ransomware Detection Through a Honeyfile-Based Approach with R-Locker
📅 Published: 2025 | 📘 Journal: MDPI, Mathematics | 📑 Cited by: 5 articles (as of 2025)
-
Poster: Crypto Ransomware Detection Through a Honeyfile-Based Approach with R-Locker
📅 Presented: Feb. 2025 | 📍 The Grove School of Engineering Expo, NY, USA
-
Poster: Anomaly-Based Approach for Crypto Ransomware Detection
📅 Presented: Nov. 2023 | 📍 AFRL-CUNY Technology and Workforce Development Forum
-
Poster: Ransomware Detection Methodology
📅 Presented: May 2022 | 📍 Defense & Intelligence Research Forum, NY, USA
-
Thesis: Visualization of Mobile Robot Localization and Mapping
📅 Published: April 2017 | 📍 Purdue University Northwest
-
Thesis: Design of High-Precision Laser Engraving Platform Control System Based on STC12C5608AD
📅 Published: June 2017 | 📍 Shaanxi University of Technology