Post doctorate at Nanjing University of Science and Technology, China
Dr. Jincheng Chen is a distinguished postdoctoral researcher at the School of Energy and Power Engineering, Nanjing University of Science & Technology in Nanjing, China. His work seamlessly integrates artificial intelligence with thermodynamic modeling, focusing on applications that range from military reconnaissance to industrial thermal management. Dr. Chen has made significant strides in predicting infrared radiation characteristics and reconstructing three-dimensional temperature fields, positioning himself as a leading figure in AI-enhanced thermodynamics.
Profile
ORCID
Education
Dr. Chen earned his Ph.D. in Power Engineering and Engineering Thermophysics, where he specialized in the intersection of AI and thermodynamic phenomena. His doctoral research laid the groundwork for innovative methods in temperature field prediction and infrared radiation modeling, combining traditional thermodynamic principles with cutting-edge artificial intelligence techniques.
Experience
At Nanjing University of Science & Technology, Dr. Chen has been instrumental in advancing research that merges AI with thermodynamics. His development of the 3D Infrared Characteristic Prediction Framework (3DICPF) has provided new avenues for simulating infrared imagery of ground targets under various environmental conditions. Additionally, his work on AI-based networks for three-dimensional temperature field reconstruction has offered rapid and accurate solutions for complex thermal predictions, benefiting both military and civilian sectors.
Research Interests
Dr. Chen’s research interests are centered on the application of generative artificial intelligence in thermal modeling and infrared radiation analysis. He focuses on creating realistic infrared images and 3D models from minimal input data, enhancing battlefield simulations and target recognition systems. His work also delves into the prediction and modeling of infrared radiation characteristics of ground targets, particularly armored vehicles, and the development of AI models for swift temperature field predictions using single-temperature images and meteorological data.
Awards
Dr. Chen’s innovative contributions have been recognized with several accolades, including the Best Paper Award at the International Conference on Heat Transfer and Thermophysics in 2023. He was also honored with the Young Researcher Award by the Chinese Society of Engineering Thermophysics in 2024, acknowledging his pioneering work in AI-enhanced thermodynamic modeling.
Publications
Dr. Chen has authored several influential papers, including:
“PISC-Net: A Comprehensive Neural Network Framework for Predicting Metasurface Infrared Emission Spectra” (2024, ACS Applied Materials & Interfaces).
“A Novel Framework for Predicting 3D Scene Infrared Radiation Characteristics through AI-Enhanced Thermodynamic Modeling” (2024, International Journal of Heat and Mass Transfer).
“Thermo-Mesh Transformer Network for Generalizable Three-Dimensional Temperature Prediction” (2025, Engineering Applications of Artificial Intelligence).
“Fast Prediction of Complicated Temperature Field Using Conditional Multi-Attention Generative Adversarial Networks (CMAGAN)” (2021, Expert Systems With Applications).
“Global Temperature Reconstruction of Equipment Based on the Local Temperature Image Using TRe-GAN” (2022, Applied Soft Computing).
These publications have been cited by numerous subsequent studies, reflecting Dr. Chen’s significant impact on the fields of AI and thermodynamics.
Conclusion
In summary, Dr. Jincheng Chen’s remarkable contributions to the integration of artificial intelligence and thermodynamic modeling have positioned him as a leading figure in his field. His innovative approaches to infrared radiation prediction and temperature field reconstruction have yielded significant advancements with practical applications in both military and industrial sectors. Dr. Chen’s dedication to advancing knowledge, coupled with his impactful research outcomes, aligns seamlessly with the criteria of the Best Researcher Award. His work exemplifies the essence of this accolade, highlighting a researcher whose efforts have profoundly influenced both academia and society at large.