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MUGIZI ROBERT RWEBANGIRA Address: 2300 6th St.
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OBJECTIVE |
To obtain a position in academic or industrial research that
will challenge me and allow me to explore new areas. |
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EDUCATION |
Carnegie Mellon University
Pittsburgh, PA
PhD Computer Science,
December 2008 Carnegie Mellon University
Pittsburgh, PA
MSc. Computer Science, May
2006
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EXPERIENCE 08/10 - Present |
Assistant Professor, Howard University Research,
teaching and pursuing external funding in the areas of machine learning with
applications to computational biology and other topics. |
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04/09 – 08/10 |
Post-doctoral Researcher and Adjunct
Professor, Howard University Supervised
all aspects of the required algorithms class for Computer Science
undergraduates by designing the syllabus, delivering lectures, and setting homeworks and exams. Conducted
independent research in the area of applied machine learning, considering
topics such as ranking legislators and low-dimensional data visualization. |
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08/02 – 12/08 |
Graduate Student at Working
with Avrim Blum and John Lafferty, I investigated
various ways of using unlabeled data to help solve learning problems. I
studied transductive classification using graph
min-cut algorithms, transductive regression and
augmenting features with unlabelled data. |
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08/07 – 12/07 08/04 – 12/04 |
Teaching Assistant for Computational
Discrete Math Twice
assisted Klaus Sutner in teaching this upper level
undergraduate course in Discrete Math by grading home works, holding office
hours, giving supporting lectures and delivering guest lectures as needed. |
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05/03 – 08/03 |
Summer Intern at Worked
with Vittorio Castelli, Tessa Lau, Lawrence Bergman
and Daniel Oblinger on learning from procedure
traces. This project involved recording traces of several different users
performing the same task and then automatically combining these traces into
one “super trace” that could be run by a non-expert. I designed and
implemented code to test the effectiveness of the system. |
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05/02 – 08/02 |
Summer Intern at Worked
with John S. Davis, Marion S. Blount, April W. Savoy and Maria Ebling. Our research focused on finding ways to use
information about the users’ Context to learn their habits. I helped design the system and implemented
code to do data mining on the context information. |
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08/01 – 12/01 |
Tutorial Assistant for Operating
Systems, Assisted
Prof. Legand Burge in running a required senior
course in Operating Systems. Graded homework, quizzes and exams. |
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05/01 – 08/01 |
Summer Intern at Worked
with Daby Sow and Chatschik Bisdikian on mechanisms
for Content Delivery. Our research focused on analyzing the effectiveness of
prefetching in reducing latency to the end user. I wrote code to test our
model, conducted a series of tests and co-wrote a paper. |
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01/01 - 05/01 |
Tutorial Assistant for Structure of
Programming Languages, Assisted
Legand Burge in running a required senior course on
programming languages, compilers and theoretical issues in computing. Graded
student homework, exams and projects. |
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03/99 – 05/02 |
Assistant to the Principle
Investigator, ·
Performed research into distributed computing systems. ·
Researched issues pertaining to fault tolerance. ·
Worked extensively with CORBA and Java. ·
Co wrote and presented
a paper at an international conference.
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01/00 – 09/00 |
System Administrator, Computer Learning and
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PUBLICATIONS
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H. Sueing, J. Jackson, R. Iziduh, A.N.
Washington, M.R. Rwebangira, L. Burge. The Opportunistic Routing of the Washington Metropolitan Area Bus
System as a Wireless Vehicular Node Simulated Network. WORLDCOMP 10 M.R. Rwebangira. On Ranking Senators. arXiv:0909.1418.
Technical Report. 2009 M.R. Rwebangira. Learning by Combining Native Features with
Similarity Functions. Extended Abstract, WEHYS 08 M.R. Rwebangira, A. Blum. Learning by Combining Native Features with
Similarity Functions. Technical Report M.R. Rwebangira, J. Lafferty. Local Linear Semi-supervised Regression. Technical Report M.R. Rwebangira. Techniques for Exploiting Unlabeled Data. Doctoral Thesis A. Blum,
T-H. H. Chan, M. R. Rwebangira. A Random-Surfer Web-Graph Model.
ANALCO 2006. M. F. Balcan, A. Blum, P. Choi, J. Lafferty, B. Pantano, M.R. Rwebangira, X. Zhu. Person
Identification in Webcam Images: An Application of Semi-Supervised Learning. ICML 2005 Workshop on Learning with Partially
Classified Training Data. A. Blum, J. Lafferty, M.R. Rwebangira, R. Reddy. Semi-supervised
Learning Using Randomized Mincuts.
International Conference on Machine Learning 2004. D. Sow, G. Banavar, J.S. Davis II, J Sussman, M.R. Rwebangira Preparing the Edge of the Network for
Pervasive Content Delivery, Advanced Topic Workshop onMiddleware
for Mobile Computing with IFIP/ACM middleware conference L. Burge, M.R. Rwebangira. “Constructing Reliable Software Across the ORB”. International
Conference of Minorities in Computing. ADMI 2000. |
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AWARDS &
HONORS |
Graduate Fellowship at Highest GPA among graduating Seniors in Engineering - 2002 Golden Key International Honour
Society -2001 Elected Cataloger for Local Chapter of Tau Beta Pi – 2001 Elected to Tau Beta Pi Honor Society –2000 Dean's Honor Roll - 1998-2002 National Dean’s List – 99/00 Top Junior in Engineering – 2001 |
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REFERENCES |
Available upon request |