Cheng Chen holds a Ph.D. in mechanical engineering from the University of Georgia and has published numerous papers on topics such as computational design, geometric modeling, and engineering education. His research interest is in developing digital threads to connect requirement management and computer-aided design using machine learning. He is always seeking innovative approaches to fill knowledge gaps and to assist in solving complex design challenges. He is currently working on several projects to develop various natural language models for requirement management. Cheng is passionate about applying his domain expertise to improve STEM education, with an emphasis on how AI can be incorporated into design practices. His master's thesis focused on improving the prediction accuracy of spray droplet size and velocity distribution using the maximum entropy principle (MaxEnt) and MPI.

Dr. Chen is a first-generation college student and member of Tri-Alpha. His diverse background enables him to promote educational access and opportunities for underrepresented students. He is committed to using his education and skills to create a positive and inclusive environment in the STEM education field. As an educator, his goal is to contribute to the university and local community by inspiring and encouraging others to pursue their dreams, regardless of their background or circumstances. With his unique perspective and dedication to making a difference, he is actively involved in promoting diversity and inclusion in Education 4.0.

Education:

Ph.D. in Mechanical Engineering, University of Georgia, 2022
M.Sc. in Aerospace Engineering, Florida Institute of Technology, 2016
B.S. in Mechanical Engineering, Century College of BUPT, 2012

Research Focus Areas:

• Computational Design 
• Smart Manufacturing
• Requirement Management
• Digital Thread
• Spray Optimization
• Engineering Education

Links:

• Personal Website
• Google Scholar
• LinkedIn
• ResearchGate