Qingyang
@qingyang-9879
Sr. Professional Staff/Research Scientist at Johns Hopkins University
Teaches Data Science, Web Development, Engineering, Software Engineering, Computer Engineering, Mathematics, Python, Docker/microservices, Big Data, Machine Learning, Artificial Intelligence, prompt engineering, large language models, agentic AI, Computer Science, data structures & algorithms, computer graphics, python, Artificial Intelligence Tools, Chatgpt, LLM, Chinese, Autonomous Systems, Applied ML, Robotics
Joined Jul 2025
About
Currently, I serve as a Senior Professional Staff Member and Research Scientist at the Johns Hopkins University Applied Physics Laboratory. My work centers on the development, testing, and application of advanced algorithms in applied mathematics, physics, and computational science to enhance Intelligence, Surveillance, and Reconnaissance (ISR) capabilities. I specialize in GenAI, Data Science, Data Engineering, Machine Learning, Deep Learning and, etc. In addition to technical contributions, I am actively involved in grant writing, proposal reviews, peer-reviewed research publications and interns mentoring.
Previously, I was a Postdoctoral Research Fellow at the University of Houston, where I led projects funded by the National Science Foundation (NSF) on machine learning–driven stochastic programming, and by the Department of Energy (DOE) on applying machine learning to solar energy vulnerability assessment. I also mentored multiple students, including three Ph.D. candidates from UH, one M.S. student from UT Austin, and one undergraduate researcher, providing guidance on research design and execution.
I hold a Ph.D. in Applied Mathematics (with a concentration in Operations Research) from the State University of New York at Buffalo. My doctoral research focused on large-scale urban transportation data analytics, optimization algorithms, data science, and applied microeconomics. Prior to my academic career, I worked as an Industrial Engineer across the aviation, aerospace, and automotive sectors and am certified as an Engineer in Training (EIT).
My technical expertise includes Generative AI, Deep Learning, Stochastic Programming, Machine Learning, and Deep Fake Detection. I am proficient in MATLAB, Wolfram Mathematica, Python, R, CPLEX, Gurobi, HPC environments, VBA, SAP, Lean methodologies, Linux (Ubuntu/Red Hat), Unix, Git, and Six Sigma.