Lu Lu

"The Lu Group aims to model and simulate physical and biological systems at different scales by integrating modeling, simulation, and machine learning and to provide strategies for system learning, prediction, optimization, and decision-making in real time. Lu Group’s current research interest lies in scientific machine learning (SciML) and artificial intelligence for science (AI4Science), including theory, algorithms, software, and its applications to engineering, physical, and biological problems. Their broad research interests focus on multiscale modeling and high-performance computing for physical and biological systems. "

computational modeling ;  deep learning ;  high-performance computing ;  neural networks ;  open science ;  simulation  

algorithms ;  artificial intelligence ;  computational biology ;  machine intelligence ;  machine learning ;  predictive modeling  

Lu Lu is an Assistant Professor in the Department of Statistics and Data Science at Yale University. Before joining Yale, he was an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Pennsylvania from 2021 to 2023 and an Applied Mathematics Instructor in the Department of Mathematics at Massachusetts Institute of Technology from 2020 to 2021. He obtained his PhD in Applied Mathematics at Brown University in 2020, master's degrees in Engineering, Applied Mathematics, and Computer Science at Brown University, and bachelor's degrees in Mechanical Engineering, Economics, and Computer Science at Tsinghua University in 2013. He has received the 2022 US Department of Energy Early Career Award and the 2020 Joukowsky Family Foundation Outstanding Dissertation Award from Brown University. He is also an action editor of the Journal of Machine Learning.