2019
Teaching:
2016 Teaching:
2015
Teaching:
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.