We received a total of 63 applications (+4 only transcript no ...

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25 Οκτ 2013 (πριν από 3 χρόνια και 10 μήνες)

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W
e received a total of 63 applications (+4 only transcript no application)



We
made offers to about 26 students
=> Final 1
5

students (5 Women, 1
0

Men)



Ethnicity:


Caucasian : 7


African:


2


Asian :


4


Hispanic:


1


Multi
-
Racial: 1


Descriptions of Projects:


A total of eighteen projects were available for the participants to select.


1. Towers of Hanoi (Professor Ernst L. Leis
s)

Description: The Towers of Hanoi is a problem that has been well studied and frequently
generalized. We are interested in the generalization to arbitrary directed graphs and
study how many moves in a given graph are necessary to move n disks from the st
arting
peg to the destination peg. There are known upper and lower bounds on the minimal
number of moves. The project involves designing algorithms and implementing them for
solving the problem on a given graph and looking at improving the known upper and
lower bounds. In particular, parallel moves are of interest.

Objective:

Study recursion using the Towers of Hanoi problem and explore means of
improving existing bounds. Students will learn implementation and analysis techniques.

2. Inference Control in St
atistical Databases (Professor Ernst L. Leiss)

Description: Inference control in statistical databases is intimately related to the
preservation of privacy of data stored in such databases. It has proven to be quite
difficult to prevent inferring informati
on about individuals from responses to legitimate
statistical queries. One of the few successful methods involves adding randomly selected
elements to the query set. We want to study experimentally whether removing one or
more elements from the query set a
chieves similar outcomes. This project extends prior
work for averages to selector functions, in particular medians. The work will involve
determining how to quantify inference control and how to simulate methods for
measuring it.

Objective: Study the prob
lems of securing statistical databases. Students will learn how
to analyze security questions in statistical databases and how to carry out large
-
scale
simulations.



3.

Digital Watermarks (Professor Ernst L. Leiss)

Description: Watermarks have attracted
increased attention as concerns about
establishing ownership of digital media have escalated. Robust invisible watermarks
allow one to attach an indelible stamp of ownership; clearly the methods employed must
be impervious to operations such as rescaling,
filtering, or superimposing an additional
watermark. Robustness is related to the redundancy of the watermark (e. g., if a certain
small pattern is repeated many times in a watermark, the removal of the watermark
through cropping an image is foiled). Simil
arly, the invisibility of a watermark is related
to the extent of changes in the information that makes up

the media. This imposes limits
on the amount of information that can be encoded in the watermark. The primary
emphasis of the research is on verifica
tion techniques.

Objective: Study digital watermarking algorithms and determine their properties.
Students will learn about aspects of digital watermarks.

4. Transitioning from Algorithms to Software (Professor Ernst L. Leiss)

Description:

Algorithm analys
is is a well
-
studied discipline, as is software development.
However, at the

i
nterface between these two disciplines much can and does go wrong. In
fact, many programmers have experienced situations where a good algorithm (that is,
correct and efficient) r
esulted in either wrong or unacceptably slow software. The causes
of the differences between the behaviors of algorithms and software can be categorized
into several areas, namely the implications of the non
-
uniform memory in real
architectures (both cache
s and virtual

memory management are implicated), system
issues (memory mappings, passing of parameters, garbage collection, and optimization
techniques are important here), implicit assumptions (including exception handling),
and the finiteness of the
number representation (which does not only have relevance for
numerical applications, but is also important if one tests for equality or assumes
mathematical identities hold).

Objective: Explore assumptions of different computing paradigms and determine ho
w
their differences affect

software. Students will learn how to obtain good software from
algorithms.

5. Put it on the Cloud (Professor Ioannis Pavlidis)

Description: In this project the student will work with a team of Research Assistant
Professors and Ph
.D. students to design and implement the migration of massive
amounts of research data on the cloud. These data have been collected as part of an NSF
project the last three years and need to be made available to the research community at
large. Putting mas
sive amounts of research data on the cloud for communal use is a clear
trend and is projected to grow by leaps and bounds, becoming an R&D field and business
all by itself. Migration of such data sets is a complex operation and involves issues of
organizat
ional design, data checking and integrity, user interfacing, as well as data
mining and annotation. The student will learn and use XNAT and Azure among other
cutting edge tools.


6. Total Mobility (Professor Ioannis Pavlidis)

Description: In this project
the student will work with a Research Assistant Professor to
develop algorithmic software that differentiates various patterns of physical activity from
iPhone accelerometer data. These anonymous data are collected by free experimental
applications that th
e Computational Physiology Lab has released in the App Store the
last couple of years and are used by thousands of people around the world. The ultimate
goal is to automatically understand when someone walks versus when s/he runs versus
when s/he climbs th
e stairs versus when s/he bikes. Such capability has tremendous
value in total health management applications as well as in gathering detailed
anthropological statistics of mobility at a global scale. The next “Fittest Cities in America”
list may well be d
ecided by the software that you will develop in this project!

7. Local and Global Relationship in Face Recognition (Professor Ioannis
Kakadiaris and Shishir Shah)

Description:

Automatic image analysis and computer vision techniques have been
developed for
face recognition. Nonetheless, the ability to replicate a human

s ability to
recognize a face has not yet been surpassed. To this extent, it is critical to understand the
perceptual and reasoning power of humans. One of the questions that remain
unanswered

is that of the role of partial observations in recognizing a face. In this project,
a student will learn to design an experiment to assess human recognition ability in whole
and partially observed images. The student will develop a web
-
based platform for
image
tagging and combine it with a crowd
-
sourcing platform such as Amazon Mechanical
Turk.

Specific Requirements:

We are looking for a skillful and creative individual, familiar with
web development technologies and database applications.


8. 3D Model of

my Face (Professor Ioannis Kakadiaris and Shishir Shah)

Description: Computer Vision technologies have been starting to emerge in
entertainment platforms and remotely controlled
-
interfaces using affordable imaging
sensors and devices like Microsoft

s Kine
ct. RGB
-
D cameras such as those used in
Kinect capture image (RGB) and depth (D) data, using a range camera and IR light, and
allow for 2D and 3D image data acquisition. Such data can be used for 3D scene
reconstruction, target location and tracking. In th
is project, a student will use the Kinect
sensor to capture faces and develop methods to reconstruct 3D models. The student will
learn to use open
-
source drivers and software to facilitate data capture and analysis.

Specific Requirements:

We are looking fo
r a creative individual knowledgeable on one or
more of the following fields: Open
-
source Software, Computer Vision, Computer
Graphics, Computer Games & Animation, Data Visualization.


9. Predict A Heart Attack (Professor Ioannis Kakadiaris and Shishir Sha
h)

Description: Every year 1.4 million Americans suffer a heart attack; in 2004, over
800,000 of these attacks were fatal. Large amounts of diverse data points are typically
measured while screening individuals during routine health checkups and diagnosis.

In
collaboration with cardiologists and computational scientists, a student will learn
fundamentals of machine learning and evaluate methods that can assess the value of
collected data points for the design of a system to identify individuals at risk of h
aving a
heart attack.

Specific Requirements: We are looking for a driven and dynamic individual.


10. Stepping
-
stone Intrusion Detection (Professor Stephen Huang)

Description: In order to avoid being detected, computer hackers typically go through a
long
chain of computers to break into a target machine. This can be achieved by using a
chain of stepping
-
stones hosts or through Tor. We are interested in real
-
time algorithms
that can detect such intruders effectively. The project involves the integration of
algorithm design, network protocol, and computer security techniques into a system.

Specific Requirements: We are seeking students with some programming experience in
C/C++ or Java, knowledge of OS or computer networks a plus. Students with experience
usi
ng Tor (a network of virtual tunnels) are a plus.


11. Mining and Visualization of Cytometry Data (Professor Stephen Huang)

Description: Flow cytometry

has been an important technique in hematology, and it can
be used to detect and identify the minor cell population from bone marrow or blood.
Most of the current studies are still based on manual gating by medical scientist and
researchers. This process i
s not only labor intensive, but also may mislays some potential
cells in other dimensions. We are working on a framework to visualize and analyze the
flow cytometry readouts. The result can provide doctors and physicians useful
information to diagnose bloo
d or lymphatic diseases, such as Leukemia, Myeloma, and
Lymphoma. We are seeking students with interest in data mining and/or machine
learning.

Specific Requirements: We are seeking students with data mining and/or Matlab skills to
help us analyze the data
.



12. Information Extraction and Text Mining (Professor Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all our
projects. This project will investigate how to extract the most relevant information from
text

documents and construct a summary and how to evaluate the quality of the
information extracted.

Specific Requirements: None
-

interest in statistics/Perl is desirable

Objective: Student will learn text mining, information extraction techniques and meta
-
analysis.


13. NLP and Machine Learning techniques for Computer Security and
Counterterrorism (Professor Rakesh Verma)

Description:

We are looking for enthusiastic, passionate and bright students for all our
projects. This project involves the design and
implementation of natural language
processing and machine learning techniques for problems in counterterrorism and
computer security.

Specific Requirements: Some knowledge of Perl or Weka is desirable.

Objective: Student will learn NLP and text mining te
chniques.


14.

NLP techniques for Lies and Fraud Detection (Professor Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all our
projects. This project involves the design and implementation of natural language
processing techniques for detection of fraudulent reviews and financial documents.

Specific Requirements: Some knowledge of Perl is desirable but not required.

Objective: Student will learn NLP and text mining techniques.


15.

Computer Security (Profess
or Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all our
projects. This project involves the study and analysis of how man
-
in
-
the
-
middle attacks
can be prevented in cryptographic protocols.

Specific Require
ments: Interest in formal methods.

Objective: Explore assumptions of different computing paradigms and determine how
their differences affect software. Students will learn how to obtain good software from
algorithms.


16. Wireless Sensor Networks (Profess
or Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all our
projects. This project involves the design and analysis of protocols for wireless sensor
networks.

Objective: Wireless sensor networks in general and wireless sensor security in particular.


17. Performance and Scalability of Parallel Codes in a Volunteer Virtual Cluster
(Professor Jaspal Subhlok)

Description: The objective of the Volpex

project is to convert idle PCs into a virtual
cluster for executing parallel applications. The project has developed VolpexMPI, a
failure resistant MPI (Message Passing Interface) library designed to execute scientific
applications. Volpex software is int
egrated with BOINC (Berkeley Open Infrastructure
for Network Computing) and deployed to build a volunteer PC pool around the world.
The objective of this student project is to measure and evaluate the performance and
scalability of selected applications ex
ecuting on 100s to 1000s of nodes around the world
under Volpex/BOINC control.

Specific Requirements: The project will involve socket programming and C programming.
Knowledge of parallel computing is desirable.


18. Accelerated Review of Video Lectures (Pr
ofessor Jaspal Subhlok)

Description: Video of classroom lectures is often made available as additional material to
a conventional course, as the core of distance learning coursework,or posted publicly for
community learning or as reference material. Prior
research has established that
recorded Tablet PC lectures are a powerful resource on par with a textbook and
classroom experience. At the same time, a major weakness of the video format is the
inability to quickly access the content of interest. In this pr
oject, a student will develop
methods to automatically identify index points in recorded lecture videos as a means to
provide content
-
based access to a subject matter.The student will learn fundamentals of
video and image analysis and learn to model spatio
-
temporal signals for quantitative
understanding of information content.




Appendix A: Participant Information




Student Name


Home Institution


Gender


Ethnicity


1

Catherine M.
Hornback

University of Maryland
-
Baltimore
County, Baltimore, MD


Female

Caucasian

2

Tyler Nichols

Loyola Marymount University, Los
Angeles, CA


Male

Caucasian

3

Teja Shah

Carnegie Mellon University, Pittsburgh,
PA


Female

Asian

4

Andrew A. Springall

The University of Alabama, Tuscaloosa,
AL


Male

Caucasian

5

Cedric
E. Searcy

Columbus State University, Columbus,
GA


Male

African

6

Simone G. Stephens

University of North Carolina,
Greensboro, NC


Female

Multi
-
Racial

7

Zahir C. Mejias

University of Puerto Rico
-
Rio Piedras
Campus, San Juan, PR


Female

Hispanic

8

Ekene
Sibeudu

University of Maryland
-
Baltimore
County, Baltimore, MD


Male

African

9

Ashik R. Khatri

University of Houston, Houston, TX


Male

Asian

10

Kenneth F. Li

Ithaca Col l ege, Ithaca, NY


Mal e

Asi an

11

Benj ami n A. Cohen

Johns Hopki ns Uni versi ty
Bal ti more,
MD


Male

Caucasian

12

Aaron J. Smi th

Coastal Carol i na Uni versi ty, Conway, SC


Mal e

Caucasi an

13

James Everett Tayl or

Uni versi ty of Houston, Houston, TX


Mal e

Caucasi an

14

Stephen Herbei n

Uni versi ty of Del aware, Newark, DE


Mal e

Caucasi an

15

Ceci l i a Y. Chen

Uni versi ty of Puerto Ri co
-
Mayaguez
Campus, Mayaguez, PR


Femal e

Asi an








Appendix B: Final REU Presentation by Students


Student

Presentation Title

Mentor

1

Cecilia Y. Chen

Text Based Discovery of Transition Points
for ICS Video
Player


Jaspal Subhlok and
Edgar Gabriel

2

Stephen Herbein

Deceptive Opinion Spam Analysis Using a
Two Sample T
-
Test for Feature Selection


Jaspal Subhlok and
Edgar Gabriel

3

Teja Shah

Lung Branching and it’s implication in
disease


Ioannis Kakadiaris

and Shishir Shah

4

James Everett
Taylor

2D Facial Recognition (iAttend)

Ioannis Kakadiaris
and Shishir Shah

5

Zahir C. Mejias

Statistical Models of 3D Face Landmarks
and Annotations


Ioannis Kakadiaris
and Shishir Shah

6

Catherine M.
Hornback

Parallel
Moves in the Towers of Hanoi


Ernst Leiss

7

Cedric E. Searcy

Building A Centralized Digital
Watermarking Testing Platform


Ernst Leiss

8

Simone G.
Stephens

Digital Audio Watermarking


Ernst Leiss

9

Kenneth F. Li

Detecting Long Stepping
-
Stone
Connections


Stephen Huang

10

Andrew A.
Springall

Fine Grain Identification of Tor
Connections


Stephen Huang

11

Aaron J. Smith

Using Accelerometer Data to Indicate
Subject Activity and Attentiveness


Ioannis Pavlidis

12

Ashik R. Khatri

Need to take an Exam? Get your iPad!


Ioannis Pavlidis

13

Benjamin A. Cohen

Deceptive Opinion Spam Analysis Using a
Two Sample T
-
Test for Feature Selection


Rakesh Verma

14

Ekene Sibeudu

Identifying Human Vs. Bot On Twitter


Rakesh Verma

15

Tyler
Nichols

Efficient and Effective Zero Hour Phish Site
Detection


Rakesh Verma






Appendix C: 2011 REU Student Activity Calendar


Wk

Date

Time

Event

Place

1

June 04
(Mon)

09:00
-

15:00

Orientation

(
Campus Map
,
UH
Shuttle
)

550 PGH
(Directions)

1

June 05
(Tue)

10:30
-

12:00

Research Seminar
-

"Fast by Nature
-

How Stress Patterns Define Human
Experience and Performance in
Dexterous Tasks"

by Ioannis Pavlidis,
University of Houston

232 PGH

1

June 06
(Wed)

18:30
-

21:00

GRE Class 1

550 PGH

1

June 07
(Thurs)

13:00
-

14:00

Short Talks from REU Mentors, Prof.
Huang and Prof. Kakadiaris.

550 PGH

1

June 07
(Thurs)

14:00
-

15:00

REU Evaluation, Prof. Dov
Liberman
,Educational Psychology
Department, UH.

550 PGH

1

June 08 (Fri)

11:00
-

12:00

Short Talks from REU Mentors,
Prof.Subhlok, Prof. Verma, and Prof.
Leiss.

550 PGH

1

June 08 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

2

June 12
(Tue)

15:00
-

17:00

Field Trip I:
Visit Robotic Surgery
Center at Methodist

Methodist

2

June 13
(Wed)

18:30
-

21:00

GRE Class 2

550 PGH

2

June 15 (Fri)

10:30
-

12:00

Research Seminar
-

"HCC for
Creativity, Expression, and
Participation"
by Adruid Kerne, TAMU

232 PGH

2

June 15 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

2

June 16 (Sat)

18:30
-

20:30

Welcome Dinner (Carpool from Lot
5A outside Cougar Village at 6:00PM)

Escalentes
in Woodway


3

June 20
(Wed)

18:30
-

21:00

GRE Class 3

550 PGH

3

June 22 (Fri)

10:30
-

12:00

NSF REU Career Development Series
-

"Science Ethics Workshop:
Academic Life
-

Rewards and Perils"

by Dr. Ioannis Pavlidis, UH

232 PGH

3

June 22 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

4

June 27
(Wed)

18:30
-

21:00

GRE Class 4

550 PGH

4

June 29 (Fri)

11:00
-

12:00

"Developing Effective Poster
Presentations"

by Dr. Chad Wilson,
UH, viewing online video followed by
a discussion session.

550 PGH

4

June 29 (Fri)

12:00
-

13:00

Friday
Lunch Meeting

550 PGH

5

July 2 (Mon)

11:00
-

12:00

NSF REU Career Development Series
-

"Graduate Program Can Help You
Be a Better Entrepreneur!"

by Dr.
David Nghiem, CEO, Global Wireless
Technology.

550 PGH

5

July 4 (Wed)



Independence Day Holiday! (
no GRE
Class)



5

July 6 (Fri)

11:00
-

12:00

NSF REU Career Development Series
-

"Computer Science Career by the
Numbers" by Prof. Stephen Huang,
UH.

550 PGH

5

July 6 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

6

July 10 (Tue)

14:00
-

15:30

Writing Effective Research Reports 1:
How to read and use previous studies

Note:
Registration is required

212 Agnes
Arnold Hall,
UH Writing
Center

6

July 11
(Wed)

10:30
-

12:00

Midterm Project Presentation

-

5
minutes each

550 PGH

6

July 11
(Wed)

18:30
-

21:00

GRE Class 5

550 PGH

6

July 12
(Thurs)

14:00
-

15:30

Writing Effective Research Reports 2:
How to present and interpret your
findings

Note:
Registration is
required

212 Agnes
Arnold Hall,
UH Writing
Center

6

July 13 (Fri)

10:30
-

12:00

Seminar Talk
-

"
How Do We Measure
Proficiency in Surgery?"

by Dr.
Dunkin, Methodist Hospital

232 PGH

6

July 13 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

7

July 18
(Wed)

18:30
-

21:00

GRE Class 6

550 PGH

7

July 20 (Fri)

10:30
-

12:00

NSF REU Career Development Series
-

"Guide to Graduate School
Admissions" by Prof. Ernst Leiss

550 PGH

7

July 20 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

7

July 20 (Fri)

13:00
-

14:30

Panel Di
scussion: A group of
graduate students at various stages
of their study will be available to
share their experiences about
graduate studies in Computer
Science and life as a graduate
student.

550 PGH

8

July 24 (Tue)

14:00
-

16:00

Developing Effective PowerPoint
Presentations
(Webinar)

550 PGH

8

July 25
(Wed)

18:30
-

21:00

GRE Class 7

550 PGH

8

July 27 (Fri)

11:00
-

12:00

Seminar Talk
-

"Toward Autonomous
Structural Health Monitoring"

by Dr.
Rong Zheng, UH

550 PGH

8

July 27 (Fri)

12:00
-

13:00

Friday Lunch Meeting

550 PGH

9

July 31 (Tue)

11:00
-

12:00

NSF REU Career Development Series
-

"Ethics in Science" by Prof. Ernst
Leiss, UH

550 PGH

9

Aug 01
(We
d)

18:30
-

21:00

GRE Class 8

550 PGH

9

Aug 02
(Thurs)

11:00
-

12:00

Seminar Talk by Dr. Ed Robinson,
Chief Scientist, Monstrous Company.

550 PGH

9

Aug 02
(Thurs)

12:00
-

13:00

Thursday Lunch Meeting (Moved from
Aug 3rd, Friday)

550 PGH

9

Aug 03 (Fri)

08:50
-

13:00

Field Trip II : Hewlett
-
Packard

Meeting
point: Lot
5A outside
Cougar
Village

10

Aug 07 (Tue)

08:00

Poster Completion

Submit to
Mitch


10

Aug 08
(Wed)

14:00
-

16:00

REU Evaluation, Prof. Dov
Liberman,
Educational Psychology Department,
UH.

550 PGH

10

Aug 9
(Thurs)

15:00 (Thurs)

-
14:00 (Fri)

Poster Exhibition

Hallway
outside
department
office

10

Aug 10 (Fri)

10:00
-

14:00

Final Project Presentation (10
minutes each)

550 PGH

10

Aug 10 (Fri)

14:00
-

16:00

Project Submission (ppt
presentation, poster, project report
,

and software code).

Submit to
your mentor