DEBORAH MUDALI
Mobile : +1 423 314 6522
E-mail: [email protected], [email protected]
Research Interests:
Machine learning, medical image analysis, pattern recognition, scientific visualization, data science, data analytics, feature selection and extraction in medicine.
Current project title: Early Detection of Onchocerciasis
Abstract: Onchocerciasis commonly known as River blindness is a prevalent disease that affects mostly people in the sub-Saharan Africa regions infested with black flies. Its symptoms amongst many include; intense itching, skin lesions, nodules, leopard skin, etc. If this disease is untreated or treated late, it could lead to vision impairment and nodding disease which is a neurological condition. We are investigating ways in which to curb River blindness by studying subject blood and skin images to build algorithms to detect the disease in its earliest stage. This will improve on the effectiveness of the given treatment to prevent aftermaths like nodding disease.
Education:
2010-2014 PhD in Computer Science
University of Groningen, The Netherlands.
Supervisor: Prof. Dr. Jos B.T.M Roerdink
Graduation: 14th March 2016
Thesis Title: Prediction of neurodegenerative diseases from functional brain imaging data.
Summary: Neurodegenerative diseases (NDs) are increasingly becoming a problem, affecting mostly the old in developed countries. These diseases are hard to diagnose at an early stage. Further, it is not easy to discriminate among the neurodegenerative diseases since they exhibit similar symptoms. Methods for predicting and distinguishing NDs in the early stages were applied to brain imaging data. Some of the classification methods included decision trees, learning vector quantization and support vector machine.
2004-2006 Masters in Computer Science (Msc)
Makerere University, Uganda.
Supervisor: Dr. Ezra K. Mugisa
Thesis Title: A web based medical data and image repository
Summary: A database which stores all types of medical data and images for online access and analysis by medical practitioners.
2001-2004 Bachelors in Computer Science (Bsc)
Mbarara University of Science and Technology (MUST)
Project title: Pharmacy monitoring system
Research Experience:
2010-2015 PhD student
Scientific Visualization and Computer Graphics Group,
Rijk University of Groningen, The Netherlands.
2014 to date Research fellow
Artificial Intelligence Group, Makerere University.
Teaching Experience:
2018 to date Visiting Scholar and Lecturer,
Department of Computer Science,
College of Engineering and Computer Science,
University of Tennessee at Chattanooga (UTC).
Role: Research and Teaching.
Courses: Fundamentals of Computing, Data structures & program design, Data analytics and Operating systems.
2017 to date Lecturer and Graduate Research Coordinator,
Department of Computer Science,
College of Computing & Information Sciences,
Makerere University (MUK).
Role: Teaching and supervising PhD, Masters and Bachelors Students.
Subjects: Image processing, data warehousing and data mining
Others: Coordinating the entire graduate research activities such as enrollment, concept and proposal writing, dissertations/theses preparations, setting up panel discussions. determining the panelists per session, etc.
2015-2017 Lecturer, Department of Computer Science,
Faculty of Computing and Informatics,
Mbarara University of Science and Technology (MUST).
Role: Teaching and supervising student research projects.
Subjects: Biomedical data mining, and Biomedical modeling and simulations
2007-2009 Lecturer, Institute of Computer Science (MUST)
Courses I taught: Data Mining, Information Systems Management, Data Structures and Analysis of Algorithms, Systems Analysis and Design, Software Engineering, Systems Programming and Operating Systems.
2008 Ag. Director, Institute of Computer of Science (MUST)
§ Oversee the activities in the institute of computer science, attend
meetings, and allocate tasks.
2004-2006 Supervisor, Faculty of Computing and Information Technology
Makerere University (MUK)
· Supervised students during examinations.
Programming Languages:
C/C++, Java, Matlab, R (Rstudio), Python, Orange, extra.
Other Experiences and Skills:
June to July 2008 (MUST): CISCO/IT Essentials
May 2005 (MUK): CISCO/CCNA
2002-2003 Trainee
Computer hardware and network installation at International Business Solutions LTD
Publications:
Deborah Mudali. Adaptable skin disease classification. ACM Mid Southeast 2018 Fall Conference. 2018. Abstract.
D. Mudali, L. K. Teune, R. J. Renken and K. L. Leenders, and J. B. T. M. Roerdink. “Classification of Parkinsonian Syndromes from FDG-PET Brain Data Using Decision Trees with SSM/PCA Features”, Computational and Mathematical Methods in Medicine, Article ID 136921:1–10, 2015. DOI: http://dx.doi.org/10.1155/2015/136921.
Deborah Mudali, Michael Biehl, Klaus L. Leenders , and Jos B. T. M. Roerdink. LVQ and SVM Classification of FDG-PET Brain Data. In Advances in Self-Organizing Maps and Learning Vector Quantization, pages 205–215. . Springer International Publishing, 2016.
D. Mudali, L. K. Teune, R. J. Renken, K. L. Leenders and J. B.T. M. Roerdink. Comparison of Decision Tree and Stepwise Regression Methods in Classification of FDG-PET Brain Data using SSM/PCA Features. 8th International Conference on Advanced Computational Intelligence, ICACI, Thailand, February 14-16, 2016.
M. Biehl, D. Mudali, and K. L. Leenders and J. B. T. M. Roerdink. Classification of FDG-PET Brain Data by Generalized Matrix Relevance LVQ. In BrainComp 2015. Pages 131–141, 2016.
L. K. Teune, R. J. Renken, D. Mudali and B. M. De Jong, R. A. Dierckx and J. B. T. M. Roerdink, and K. L. Leenders. Validation of parkinsonian disease-related metabolic brain patterns. Movement Disorders”, 28(4):547–551, 2013.
DOI: http: //dx.doi.org/10.1002/mds.25361.
D. P. Williams, D. Mudali, H. Buddelmeijer and P. Noorishad, S. Meles, R. J. Renken and K. L. Leenders, and E. A. Valentijn and J. B. T. M. Roerdink. Visualization of Decision Tree State for the Classification of Parkinson’s Disease. Journal of Biomedical Engineering and Medical Imaging, 2016. Accepted.
D. Mudali, L. K. Teune, R. J. Renken and K. L. Leenders, and Jos B. T. M. Roerdink. “Comparison of decision tree and stepwise regression methods in classification of FDG-PET data”. In Third European Conference on Clinical Neuroimaging, March 31-April 1, Lille, France. Page 16, 2014. Abstract.
Deborah Mudali, L. K. Teune, R. J. Renken and K. L. Leenders, and J. B. T. M. Roerdink. “Decision Tree Classification of FDG-PET Data to Predict Neurodegenerative Diseases”. ICT-OPEN 2012 ASCI, October 22, 2012, Rotterdam, Netherlands. (Poster)
L. K. Teune, D. Mudali, R. J. Renken and B. M. De Jong, M.Segbers, J. B. T. M. Roerdink , R. A. Dierckx, and K. L. Leenders. Glucose IMaging in ParkinsonismS. In 16th International publications Congress of Parkinson’s Disease and Movement Disorders, Dublin, Ireland June 17-21. 2012. Abstract
David Williams, Deborah Mudali, Hugo Buddelmeijer, Parisa Noorishad, Milena Ivanova, Edwin Valentijn and Jos Roerdink: Interactive Visualization of Decision Trees for the Classification of Parkinson’s Disease. ICT-OPEN 2015 ASCI, March 24-25, 2015, Amersfoort, Netherlands. (Poster)
References:
Prof. Dr. Michael Biehl
Intelligent Systems Group
Johann Bernoulli Institute for Mathematics and Computer Science
University of Groningen
P.O. Box 407, 9700 AK Groningen
The Netherlands
Tel: +31503633997
Fax: +31503633800
Email: [email protected], [email protected]
Prof. Dr. Jos BTM Roerdink
University of Groningen
Johann Bernoulli Institute for Mathematics and Computer Science
P.O. Box 407, 9700 AK Groningen
The Netherlands
Tel: +31503633931
Fax: +31503633800
Email: [email protected]
Dr. Joseph Migga Kizza
Professor and Head
Department of Computer Science & Engineering;
College of Engineering and Computer Science
The University of Tennessee-Chattanooga
Chattanooga, Tennessee, 37403
Tel: 1-423-425-4043
Fax: 1-423-425-5229
Email: [email protected]