David Juedes, Associate Professor and Assistant Chair
for Computer Science
Education:
Ph.D. in Computer Science, Iowa State University, 1994
Ph.D. Advisor: Jack Lutz
Dissertation Title: The Complexity and Distribution of Computationally
Useful Problems
M.S. in Computer Science, Iowa State University, 1990
B.S. in Computer Science and Mathematics, University of Wisconsin-La
Crosse, 1988
Teaching
I am commited to being an excellent teacher. I believe that the
key to excellent teaching is having a
deep understanding of the underlying material. Our duty as
educators is to provide students with the tools
that they will need to succeed in the future. We cannot do this
without teaching our students meaningful
content. For
this reason, I continue to learn new material to broaden my knowledge
of computing so that
I can pass my insight on to my students.
While people learn in a variety of ways, I am convinced that students
learn best by taking an active role
in
in their classes. For this reason, I strive to design
interesting, non trivial assignments and projects so that
students expand their knowledge of computing by writing and
doing.
I have taught the following courses at Ohio University: CS 240B
(Introduction to Computer Science in C++ II),
CS 240C (Introduction to Computer Science in C++ III), CS 300
(Introduction to Discrete Structures),
CS 361 (Data Structures), CS 404/504 (Design and Analysis of
Algorithms), CS 406/506 (Computation Theory),
CS 410/510 (Formal Languages and Syntactic Analysis), CS 456/556
(Software Design and Development),
CS 604 (Advanced Algorithms), CS 605 (Parallel Computation Theory), and
CS 606 (Computational Complexity).
I am interested in the design of software for grading and evaluating
student projects.
This is the main purpose of the Web Based
Grading Project that I initiated recented.
Research
My primary research interest is in the theory of computing and the
theory of algorithms. I have published research
results in the SIAM Journal on
Computing, Theoretical
Computer Science, Computational
Complexity,
Information and Computation, ACM Transactions on Mathematical Software,
Theory of Computing Systems,
the Journal of Computer and Systems
Sciences, and several other journals. My work has
been cited in various
publications. See CiteSeer for details.
(Search citations for "juedes".)
In addition to my research in the theory of computing, I have research
interests in other areas of computing: real-time
systems, bioinformatics, and numerical software. I am
currently on the conference committee for the
Ohio Collaborative Conference on
Bioinformatics.
Recent Publications:
- The Complexity of Polynomial Time Approximation (with L. Cai, M.
Fellows, and F. Rosamond), Theory of
Computing Systems, accepted for publication.
- Approximation Algorithm for Periodic Real-Time Tasks with
Workload Dependent Running-Time Functions (with F. Drews, D. Gu, L.
Welch, K. Ecker, and S. Schomann), Real
Time Systems, accepted for publication.
- Tight lower bounds for certain parameterized NP-hard problems
(with J. Chen, B. Chor, M. Fellows, X. Huang, I. Kanj, and G. Xia), Information and Computation 201
(2005), pages 216--231.
- Baire category and nowhere differentiability for feasible real
functions (with J. M. Breutzmann and J.H. Lutz), Mathematical Logic Quarterly, 50
(2004) No. 4/5, pages 460--472.
Students:
I am currently advising the research of three graduate students and one
undergraduate student.
Dan Xiao is a currently working towards a Ph.D. degree. Dan
is studying parameterized algorithms.
Selvameenal Chokkalingham (not pictured) is working towards an M.S.
degree in Computer Science. She
is currently studying applications of algorithms that employ hypergraph
decompositions.
Marco Wotschka is currently working on an M.S. degree in Computer
Science. Marco plans to study
parameterized algorithms for bioinformatics. Marco's TopCoder rating is 1244 (68th
percentile).
Hiep Dinh is an undergraduate student in the Honors Tutorial Program in
Computer Science. Hiep
is currently examining lower bound techniques in complexity
theory. Hiep's TopCoder
rating is
1901 (94 percentile) and he was a finalist at last year's Google Code
Jam. Hiep's research is supported by
the Provost's Undergraduate Research Fund.