Teaching Statement
Jia-Yu (Tim) Pan

I love to teach.  I enjoy interacting with students, and find great
satisfaction in preparing students with skills and knowledge that will
help them with employment or further study.  In addition, I 
consider teaching and research complementary activities.  Research
provides real-world examples that can motivate students and make them
appreciate the importance and fun of a particular subject.  On the
other hand, teaching helps me develop clear explanations of difficult
concepts, which is an essential skill for research.


I have taught at advanced and introductory levels at Carnegie Mellon
University and National Taiwan University.  I have led weekly
recitations, held office hours, given full lectures, and designed
homework sets and programming projects.  At Carnegie Mellon, I was a
TA for two upper-undergraduate courses: databases and computer vision.
These two courses covered the principles and recent research topics,
as well as real system implementation.  In the databases course, I
designed projects where students were asked to implement components
inside the PostgreSQL database, and also projects on building
web-based application with a database backend.  In the computer vision
course, I folded my own research into lectures on machine learning
techniques in computer vision.  At National Taiwan University, I was a
TA of an introductory course in computer science for first-year
undergraduates.  This course introduced students to many areas in
computer science such as software systems, computer architecture, and
artificial intelligence.


In my experience, there are several techniques which help students get
the most out of courses.  One thing I found important is to help
students from the beginning: make sure they understand what the
problem or project is asking for, and help them start the
problem-solving process.  Students are willing to work, but they also
get frustrated easily if the first couple of things they try do not
work.  Interactive discussions where the students are asked to explain
the problems or clarify their solutions seem to help students focus
their thoughts and identify sources of confusions.  Other techniques
such as hands-on projects, concrete examples, and relating the
concepts to students' personal experience are also tools that I often
use when I teach.


I am happy to teach a variety of computer science courses for
undergraduates and graduate students.  Within my field of expertise, I
would be delighted to teach courses in data mining, database, and
information retrieval.  I would also enjoy teaching linear algebra,
machine learning, computer vision and artificial intelligence, as well
as any of the introductory courses (e.g., introduction to programming,
discrete mathematics, or data structures).