Comp Sci Dept,                                                                 Phone:  412 965 6778

2300 6th St.                                                                                         
Washington, DC 20059                                                   Email:


To obtain a position in academic or industrial research that will challenge me and allow me to explore new areas.



Carnegie Mellon University                                                  Pittsburgh, PA

PhD Computer Science, December 2008


Carnegie Mellon University                                                  Pittsburgh, PA

MSc. Computer Science, May 2006


Howard University                                                              Washington, DC

BSc. Systems and Computer Science, May 2002            Major GPA: 4.0/4.0

Summa Cum Laude                                                Cumulative GPA: 3.96/4.0




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.



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.




08/02 – 12/08

Graduate Student at Carnegie Mellon University

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.


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.


05/03 – 08/03

Summer Intern at IBM T.J. Watson Research Center

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.


05/02 – 08/02

Summer Intern at IBM T.J. Watson Research Center

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.




08/01 – 12/01

Tutorial Assistant for Operating Systems, Howard University

Assisted Prof. Legand Burge in running a required senior course in Operating Systems. Graded homework, quizzes and exams.


05/01 – 08/01

Summer Intern at IBM T.J. Watson Research Center

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.



01/01 - 05/01


Tutorial Assistant for Structure of Programming Languages, Howard University

Assisted Legand Burge in running a required senior course on programming languages, compilers and theoretical issues in computing. Graded student homework, exams and projects.



03/99 – 05/02

Assistant to the Principle Investigator, Howard University Future Aerospace Science and Technology  (HUFAST)                                     

·         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.      


01/00 – 09/00









System Administrator, Computer Learning and Design Center (CLDC), Howard University 


  • Lead a team of four people in maintaining and upgrading a PC lab with 18 Linux machines.
  • Upgraded software packages and replaced failed hardware components.
  • Fixed problems with Network File System (NFS), printer configuration, and generally assisted lab users.
  • Assisted junior co-workers in completion of their tasks and taught a class on Perl.



Mugizi Rwebangira, On Ranking Senators by Their Votes, Lecture Notes in Electrical Engineering 2012, 1, Volume 124, Recent Advances in Computer Science and Information Engineering, Pages 261-268


Hui Li, Lauren Scott, Chunmei Liu, Mugizi Rwebangira and Legand Burge, Rapid and Accurate Generation of Peptide Sequence Tags with a Graph Search Approach Lecture Notes in Computer Science, 2011, Volume 6674, Bioinformatics Research and Applications, Pages 253-261


Ko KD, Liu C, Rwebangira MR, Burge L, Southerland W. The Development of a Proteomic Analyzing Pipeline for Identifying Proteins with Multiple RRMs and Predicting their Domain Boundaries. Workshop on Computational Structural Bioinformatics, BIBM 2011, 374-381.


Li H, Liu C, Rwebangira MR, Burge L, Southerland W. Rapid Identification of multiple Post-translational Modifications with Peptide Sequence Tags. Workshop on Integrative Data Analysis in Systems Biology, BIBM 2011, 251-254.


Wardell Samotshozo, Mugizi Robert Rwebangira, Chunmei Liu, Legand Burge, Rhonda Davis, Ronald Doku, William Southerland. Pairing Algorithm for De Novo Sequencing of Tandem Mass Spectra. National Technical Association Conference, Howard University, 2011


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 2010


M.R. Rwebangira. On Ranking Senators.  arXiv:0909.1418. Technical Report. 2009


M.R. Rwebangira, A. Blum. Learning by Combining Native Features with Similarity Functions. Technical Report  2009


M.R. Rwebangira, J. Lafferty. Local Linear Semi-supervised Regression. Technical Report 2009


M.R. Rwebangira. Learning by Combining Native Features with Similarity Functions. Extended Abstract, WEHYS 2008


M.R. Rwebangira. Techniques for Exploiting Unlabeled Data. Doctoral Thesis 2008


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, 2001 Advanced Topic Workshop on Middleware 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.



Graduate Fellowship at Carnegie Mellon University -2002-2008

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

Howard University Presidential Scholarship - Full four-year scholarship.(1998-2002)

Dean's Honor Roll - 1998-2002

National Dean’s List – 99/00

Top Junior in Engineering – 2001



Available upon request