Data Science Lunch: Xinquan Huang

Xinquan Huang is currently working with Prof. Paris Perdikaris and Prof. Nat Trask on generative models in science and engineering. His research interests span the areas of physics-informed machine learning, operator learning, generative modeling using diffusion models and their applications to fluid simulation, uncertainty quantification, and inverse problems. He completed his Ph.D. at King Abdullah University of Science and Technology and has interned at Microsoft Research AI4Science. Xinquan is also an AI x Science Fellow. 

During the academic year, our postdoctoral fellows meet for an informal lunch with a Penn faculty guest speaker. Each speaker then leads the group in a casual discussion regarding the use of data science in their research. Discussions vary in content, but tend to focus on the applications of machine learning and artificial intelligence in various academic disciplines.

We encourage open conversation and the exchange of ideas at each lunch, thus fostering a collaborative environment among fellows and faculty alike. As such, these lunches provide an excellent opportunity for our fellows to make interdisciplinary connections and discover new ways to utilize data science in their own research.