Yangyang (Ian) Fu, PhD
About Yangyang (Ian) Fu, PhD
Yangyang (Ian) Fu, PhD, is a Research Engineer at Lennox International, where he leads a team focused on enhancing products through a physics-informed deep learning cloud service. He has published over 50 research papers and has extensive experience in machine learning techniques for control applications.
Work at Lennox
Currently, Yangyang Fu serves as a Research Engineer at Lennox International, a position he has held since 2023. In this role, he leads an industrial team focused on enhancing products through the development of a physics-informed deep learning-based cloud service. His responsibilities include supporting numerical modeling and simulation, which are integral to the company's research and development efforts. The hybrid work environment allows him to collaborate effectively with team members while contributing to innovative solutions in the HVAC industry.
Education and Expertise
Yangyang Fu holds a Doctor of Philosophy (PhD) in Architectural Engineering from the University of Colorado Boulder, where he studied from 2017 to 2019. Prior to that, he earned a Master of Science (MS) in Mechanical Engineering from Tongji University, completing his studies from 2012 to 2015. His academic background is complemented by extensive expertise in deep learning modeling, tuning, fine-tuning, and deployment, which he applies in his current research initiatives.
Background
Before joining Lennox International, Yangyang Fu accumulated diverse experience in various research roles. He worked as a Research Engineer at Texas A&M University from 2021 to 2022 and as an Autonomous Systems & AI Engineer at PassiveLogic in 2022. His earlier experience includes positions as a Research Assistant at the University of Miami and the University of Colorado Boulder, as well as a PhD Intern at the Pacific Northwest National Laboratory in 2018. This varied background has equipped him with a robust understanding of machine learning techniques for control applications.
Publications and Research Contributions
Yangyang Fu has published over 50 research papers focused on machine learning techniques for control applications. His contributions to the field reflect a commitment to advancing knowledge and practical applications in deep learning and control systems. His research efforts are recognized within the academic community, showcasing his ability to address complex challenges through innovative methodologies.
Kaggle Competition Experience
Yangyang Fu has a proven track record of participation in Kaggle competitions, which highlights his practical skills in data science and machine learning. This experience allows him to apply theoretical knowledge in competitive environments, further enhancing his expertise in developing effective machine learning models.