Dr. Guang Lin has made major contributions to curriculum development in the uncertainty quantification and data sciences with important applications in modeling climate, environmental and biological systems at Purdue University. He has taught a variety of undergraduate, and graduate math courses. At Purdue, he developed two new courses on “Uncertainty Quantification” and “Machine Learning and Uncertainty Quantification for Data Science” in both Department of Mathematics and School of Mechanical Engineering.
Dr. Lin has participated in a variety of teaching programs at Brown University aimed at improving the quality of undergraduate education. Additionally, he has given many short courses and invited lectures on various research topics at international conferences and department colloquiums, which have helped to improve his teaching skills. He also has extensive experience in mentoring junior researchers and young students. In the past five years, he has mentored 26 summer interns and students, and 10 postdoctoral or post-master scholars.
Over 10 undergraduate students have worked as port of Dr. Lin’s research group. He has has served as mentor for Purdue Network for Computational Nanotechnology Summer Undergraduate Research Fellowship (SURF) program since 2014. He has mentored 5 undergraduates: Yiyi Chen, Ruotong Ji, Zixuan Liu, Tian Qiu, Lefei Liu through SURF program. In addition, he also served as mentor in Wentao Chen’s Purdue undergraduate team, who was awarded the prize of finalist in the MCM math modeling contest in 2016, which is one of 22 finalist teams out of 7421 teams around the world. Besides his teaching responsibilities, Dr. Lin was actively involved at Purdue University in undergraduate advising, serving as mentor at Purdue Campus for the Society for Collegiate Leadership & Achievement.