Mr. Lei Yang, College of Business Foreign Languages, Shenzhen Polytechnic University, China
Yang Lei, born in September 1988, is a distinguished researcher and educator specializing in big data analytics, artificial intelligence, and cybersecurity within the energy sector. With a robust academic foundation and extensive industry experience, he has significantly contributed to the development of intelligent systems for healthcare, finance, and smart infrastructure. Currently serving as a full-time computer science lecturer at Shenzhen Polytechnic University, Yang Lei is dedicated to advancing research in data mining and deep learning, aiming to address complex challenges in modern energy systems.
🎓 Education
Yang Lei’s academic journey began with a Bachelor of Science in Applied Mathematics from Hunan University (2010–2014), where he developed a strong analytical foundation. He further pursued a Master’s degree in Computer Technology at the same institution (2014–2016), focusing on the intersection of computational methods and real-world applications. This combination of mathematical rigor and technological proficiency has been instrumental in his multidisciplinary research endeavors.
💼 Professional Experience
Yang Lei’s professional career encompasses roles that bridge academia and industry. At Shenzhen Polytechnic University (2022–present), he imparts knowledge in data structures, big data, cloud computing, and Python programming. Previously, as a Big Data Engineer at Shenzhen Hualang Education Investment Co., Ltd. (2021–2022), he analyzed educational data to identify investment opportunities. His tenure at Shenzhen Medical Information Center (2019–2021) involved constructing a medical big data platform, while at GF Securities (2017–2019), he developed quantitative trading strategies. Earlier, at Guangzhou Unicom (2016–2017), he managed cloud platform development and product operations.
🔬 Research Interests
Yang Lei’s research interests lie at the confluence of data mining, deep learning, and cybersecurity, particularly within energy systems. He focuses on developing robust algorithms to enhance the resilience of smart grids and renewable energy infrastructures against cyber threats. His work often involves leveraging machine learning techniques to predict and mitigate risks associated with false data injection attacks, aiming to ensure the stability and security of modern energy networks.
🏆 Awards and Recognitions
Yang Lei’s contributions have been recognized through various grants and projects. Notably, he received funding from the Special Foreign Languages Research Project of the 2023 Annual Plan for Guangdong Provincial Philosophical and Social Sciences Program (GD23WZXC02-17), the Shenzhen Philosophy and Social Science Planning Project for 2022 (SZ2022D057), and research and teaching projects at Shenzhen Polytechnic University (7025310580). These accolades underscore his commitment to advancing research in data analytics and cybersecurity.
📚 Publications
Adversarial False Data Injection Attacks on Deep Learning-Based Short-Term Wind Speed Forecasting.
Cybersecurity Challenges in PV-Hydrogen Transport Networks: Leveraging Recursive Neural Networks for Resilient Operation.