University of Florida
Department of Electrical and Computer
CNT 6805, Section 226H
Network Science and Applications
This is a 3-credit course.
science is a new and emerging scientific discipline that examines the
interconnections among networks. The types of networks include, but are limited
to, physical or engineered networks (e.g., power grid and transportation
networks), information networks, biological networks (e.g., gene regulatory
networks, protein networks, cell networks), semantic networks (e.g. word
networks, concept networks), economic networks (e.g., stock markets), and social
networks. This field of science seeks to discover common principles, algorithms
and tools that govern network structures/topologies, network functionalities,
and network behaviors. This course introduces various methodologies and
technologies in network science and studies a multitude of applications of
- Exposure to continuous-time and discrete-time signal analysis, noise in
- E. Kolaczyk, “Statistical Analysis of Network
Data,” Springer, 2009. ISBN 9780387881454.
- M. Dehmer and S.C. Basak, “Statistical
and Machine Learning Approaches for Network Analysis”, Wiley, New
York, NY, 2012. ISBN-10: 0470195150 | ISBN-13: 978-0470195154
- Mark Newman, "Networks:
An Introduction", 1st edition, Oxford University Press,
May 20, 2010. ISBN-10: 0199206651 | ISBN-13: 978-0199206650
- Stanley Wasserman, Katherine Faust, "Social
Network Analysis: Methods and Applications",
1st edition, Cambridge University Press,
November 25, 1994. ISBN-10: 0521387078 | ISBN-13: 978-0521387071
- Charles Kadushin, "Understanding
Social Networks: Theories, Concepts, and Findings", 1st
edition, Oxford University Press, December 5, 2011. ISBN-10: 0195379470|
- Alain Barrat, Marc Barthélemy, Alessandro Vespignani, "Dynamical
Processes on Complex Networks", 1st edition,
Cambridge University Press, November 24, 2008. ISBN-10:
0521879507 | ISBN-13: 978-0521879507.
- David Easley, Jon Kleinberg, "Networks,
Crowds, and Markets: Reasoning About a Highly Connected World",
1st edition, Cambridge University Press, July 19,
2010. ISBN-10: 0521195330 | ISBN-13: 978-0521195331.
- Matthew O. Jackson, "Social
and Economic Networks", Princeton University Press, November 1, 2010.
ISBN-10: 0691148201| ISBN-13: 978-0691148205.
- Piet Van Mieghem, "Graph
Spectra for Complex Networks", Cambridge University Press,
January 17, 2011. ISBN-10: 052119458X | ISBN-13: 978-0521194587.
- Peter Bühlmann, Sara van de Geer, "Statistics
for High-Dimensional Data: Methods, Theory and Applications", Springer,
1st Edition, June 14, 2011. ISBN-10: 3642201911, ISBN-13: 978-3642201912.
Dr. Dapeng Oliver Wu
Office: NEB 431
Course website: http://www.wu.ece.ufl.edu/courses/cnt6805f16
Monday, Wednesday, Friday, period 9 (4:05 pm - 4:55 pm)
- Dr. Wu: Monday, Wednesday, period 8 (3 pm - 3:50 pm),
and by appointment
Structure of the Course
course consists of lectures, 3 homework assignments,
and 1 project.
- Network Representations and Characteristics
- Network Partitioning and Clustering
- Network Visualization
- Community Formation and Detection
- Network Sampling of Events
- Learning of Network Topology
- Estimation of Network Dynamics
- Complex Network Robustness and Vulnerability
- Network Interdependency and Cascading Failures
- Social Networks
- Complex Network Models
- Searching in Complex Networks
- Information Diffusion and Propagation
- Modeling of Network Evolution
the completion of the course, the student should be able to
- understand the basics of network science
- conduct statistical analysis of network data
- know the fundamental techniques in network science
acquire the basic skill of designing scheme for network partitioning,
sampling, and estimation
Please find handouts here.
- Perfect class attendance is not required, but regular attendance is
- It is the student's responsibility to independently obtain any missed
material (including handouts) from lecture.
- During lecture, cell phones should be turned off.
- No late submissions of your homework solution, and project proposal/report, are allowed
unless U.F. approved reasons are supplied and advance permission is granted by
the instructor. Excused late submissions are consistent with university
policies in the undergraduate catalog (https://catalog.ufl.edu/ugrad/current/regulations/info/attendance.aspx)
and require appropriate documentation.
faculty, staff and student of the University are required and expected to obey
the laws and legal agreements governing software use. Failure to do so can
lead to monetary damages and/or criminal penalties for the individual
violator. Because such violations are also against University policies and
rules, disciplinary action will be taken as appropriate. We, the members of
the University of Florida community, pledge to uphold ourselves and our peers
to the highest standards of honesty and integrity.
- All students are responsible for announcements made in lecture, on the
student access website, or via the class email list.
- It is expected that you will check your email several times per week for
possible course announcements.
- Students with disabilities:
- Students with disabilities requesting accommodations should first
register with the Disability Resource Center (352-392-8565, https://www.dso.ufl.edu/drc)
by providing appropriate documentation. Once registered, students will
receive an accommodation letter which must be presented to the instructor
when requesting accommodation. Students with disabilities should follow this
procedure as early as possible in the semester.
UF students are bound by The Honor
Pledge which states, “We, the members of the University of Florida community,
pledge to hold ourselves and our peers to the highest standards of honor and
integrity by abiding by the Honor Code. On all work submitted for credit by
students at the University of Florida, the following pledge is either required
or implied: “On my honor, I have neither given nor received unauthorized aid
in doing this assignment.” The Honor Code (https://www.dso.ufl.edu/sccr/process/student-conduct-honor-code/)
specifies a number of behaviors that are in violation of this code and the
possible sanctions. Furthermore, you are obligated to report any condition
that facilitates academic misconduct to appropriate personnel. If you have any
questions or concerns, please consult with the instructor or TAs in this
Students are encouraged to discuss
class material in order to better understand concepts. All homework answers
must be the author's own work. However, students are encouraged to discuss
homework to promote better understanding. What this means in practice is that
students are welcome to discuss problems and solution approaches, and in fact
can communally work solutions at a board. However, the material handed in must
be prepared starting with a clean sheet of paper (and the author's
recollection of any solution session), but not refer to any written notes or
existing code from other students during the writing of the solution. In other
words, writing the homework report shall be an exercise in demonstrating the
student understands the materials on his/her own, whether or not help was
provided in attaining that understanding.
All work submitted in this course must be your own and produced exclusively
for this course. The use of sources (ideas, quotations, paraphrases) must be
properly acknowledged and documented. For the copy of the UF Honor Code and
consequences of academic dishonesty, please refer to http://www.dso.ufl.edu/sccr/honorcodes/honorcode.php.
Violations will be taken seriously and are noted on student disciplinary
records. If you are in doubt regarding the requirements, please consult with
the instructor before you complete any requirement of the course.
Students are expected to provide feedback on the quality of instruction in
this course by completing online evaluations at https://evaluations.ufl.edu/evals.
Evaluations are typically open during the last two or three weeks of the
semester, but students will be given specific times when they are open.
Summary results of these assessments are available to students at
All faculty, staff, and students of the University are required and expected
to obey the laws and legal agreements governing software use. Failure to do so
can lead to monetary damages and/or criminal penalties for the individual
violator. Because such violations are also against University policies and
rules, disciplinary action will be taken as appropriate. We, the members of the
University of Florida community, pledge to uphold ourselves and our peers to the
highest standards of honesty and integrity.
There are federal laws protecting your privacy with regards to grades earned
in courses and on individual assignments. For more information, please see:
If you or a friend is in distress,
or 352 392-1575 so that a team member can reach out
to the student.
Counseling and Wellness Center:
392-1575; and the University Police Department: 392-1111 or 9-1-1 for
Recovery Services (SARS)
Student Health Care Center,
Police Department at 392-1111 (or 9-1-1 for emergencies), or
technical support, 352-392-4357 (select option 2) or
e-mail to Learningemail@example.com.
Center, Reitz Union, 392-1601. Career
assistance and counseling.
http://cms.uflib.ufl.edu/ask. Various ways
to receive assistance with respect to using the libraries or finding
Teaching Center, Broward Hall, 392-2010 or 392-6420. General study
skills and tutoring.
302 Tigert Hall,
846-1138. Help brainstorming, formatting,
and writing papers.
||See the course calendar
4pm, December 14
The project report consists of
- (50%) A written report for your project
- (25%) Computer programs that you develop for your
- (10%) Powerpoint file of your presentation
- (15%) Your presentation/demo video on
Top 25% students will receive A. Average score will be at least B+.
More information on UF grading policy may be found at: https://catalog.ufl.edu/ugrad/current/regulations/info/grades.aspx
- Due dates of assignments are specified in the
- No late
submissions are allowed unless U.F. approved reasons are supplied and
advance permission is granted by the instructor.
- If you wish to dispute a
homework grade, you must return the assignment along with a succinct written
argument within one week after the graded materials have been returned to the
class. Simple arithmetic errors in adding up grade totals are an exception,
and can normally be handled verbally on-the-spot during office hours of the
TA. For all other disputes, the entire homework may be (non-maliciously)
re-graded, which may result in increase or decrease of points.
The class project will be done individually (that is, teaming with other
students is not allowed).
Each project requires a proposal and a final report. The final report is expected to be
in the format of a conference paper plus computer programs, a Powerpoint
file, and a video.
Oct. 28, the project proposal (up to 2 pages) is due. On Dec. 14, the
final report (up to 10 pages) is due. For details about the project,
please read here.
Suggested topics for projects are listed here.
Course calendar can be found here.
Anaconda: Anaconda is the
leading open data science platform powered by Python.
Theano is a Python library that lets you to define, optimize, and evaluate
mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).
Keras: Keras is a minimalist,
highly modular neural networks library, written in Python and capable of
running on top of either TensorFlow or Theano. It was developed with a focus
on enabling fast experimentation. Being able to go from idea to result with
the least possible delay is key to doing good research.
Source code for text classification (classification of text messages into
20 different categories), using deep neural networks
- Pajek: computer program for
(large) network analysis and visualization. Pajek runs on Windows and is free
for noncommercial use.
- The web
site for the book of E. Kolaczyk,
“Statistical Analysis of Network Data,” Springer, 2009.
- Graph theory in Matlab: