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Guang Lin is a Full Professor at Purdue University, where he serves as the Associate Dean for Research and Innovation in the College of Science and directs the Data Science Consulting Services. His research focuses on cutting-edge advancements in data science and AI, particularly in areas such as reliable AI, interpretable AI, and big data analysis through statistical machine learning. He integrates advanced computational methods with mathematical theories to push the boundaries in fields like Bayesian deep learning and predictive modeling. With a Ph.D. from Brown University in Applied Mathematics, Lin has previously worked as a Research Scientist at the Department of Energy's Pacific Northwest National Laboratory. He is recognized for his contributions with numerous awards, including the NSF CAREER Award and the Mid-Career Sigma Xi Award. His research is characterized by significant endeavors to develop trustworthy AI algorithms and innovative scientific discoveries. Lin’s work aims to enhance AI's interpretability and fairness, bearing crucial implications for complex decision-making in physical and biological systems. Lin is actively involved in mentoring and supports students and postdoctoral researchers interested in machine learning and big data analysis.
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