Yuying wants to be an Applied (Engineering) Scientist, meaning, a person who appreciate the glory of Physics and Mathematics while also be able to Engineer the ideas to make them measurable.
Now, he’s half way on it:
- In 2011-2015, He built up his Mathematics and Statistics background in Nankai University. At that time, he focused his study on statistical learning and optimization.
- Then he moved to Georgia Tech and obtained a MS degree in Computer Science. This is where he picked up his engineering weapons (eg. High Performance Computing). As a side dish, he joined the Machine Learning group to study the latest ML, DL technologies.
- As a practice, in 2016 summer, he interned at Amazon (SCOT) as a Machine Learning Research Scientist, this is the first time he applied his methodologies learned in school to the real-world business problems. What delightful experience!
- In 2017 summer, he learned Bayesian perspectives of Deep Learning from Duke-Tsinghua deep learning summer school and programmed his first Tensorflow CNN & RNN.
- Armed with scientific insights and engineering skills, now he’s ready to do some serious stuffs: GO BEYOND curve fitting –> learn the mechanism of systems from data –> fully control complex systems (eg. networks). He is now a PhD in Applied Mathematics at University of Washington (A highly interdisciplinary PhD program where he can collaborate with scientists from all fields and get to know the latest updates of Science and Technology. So excited!)
- To be accomplished …