UMass Boston

Data Mining, Cyber Security, Health Informatics, Big Data

PhD, University of Maryland, Baltimore County

MS, University of Maryland, Baltimore County

BS, Makerere University Kampala, Uganda

• Josephine Namayanja, Vandana P. Janeja, Change Detection In Temporally Evolving Computer Networks: Changes in Densification and Diameter Over Time, IEEE Intelligence and Security Informatics (ISI) 2015.
• Josephine Namayanja, Vandana P. Janeja, Change Detection In Temporally Evolving Computer Networks: A Big Data Framework, First International Workshop on High Performance Big Graph Data Management, Analysis, and Mining, co-located with the IEEE Big Data 2014.
• Vandana P. Janeja, Ali Azari, Josephine Namayanja, Brian Heilig, B-DIDS: Mining Anomalies In A Big-Distributed Intrusion Detection System, 2014 IEEE International Conference on Big Data October 27-30, 2014, Washington DC, USA.
• Josephine Namayanja, Vandana P. Janeja: Discovery of Persistent Threat Structures through Temporal and Geo-Spatial Characterization in Evolving Networks. IEEE Intelligence and Security Informatics (ISI) 2013.
• Josephine Namayanja, Vandana P. Janeja: An Assessment of Patient Behavior Over Time–Periods: A Case Study of Managing Type 2 Diabetes Through Blood Glucose Readings and Insulin Doses. Journal of Medical Systems, November 2012, Volume 36, Issue 1 Supplement: 65-80.
• Vandana P. Janeja, Nabil Adam, Josephine Namayanja: IntAleGen: Integrated Alert Generation in Multi Pronged attacks on Networked Systems. Workshop on Cryptography for Emerging Technologies and Applications at National Institutes for Standards and Technology (NIST). 2011.
• Josephine M. Namayanja, Vandana Pursnani Janeja: Subspace Discovery for Disease Management: A Case Study in Metabolic Syndrome. International Journal of Computational Models and Algorithms in Medicine (IJCMAM) Vol. 2(1): 38-59 (2011).
• Josephine M. Namayanja: Evaluation of Clustering Patterns using Singular Value Decomposition (SVD): A Case Study of Metabolic Syndrome. International Journal of Computational Models and Algorithms in Medicine (IJCMAM) Vol. 1 (3): 69-80 (2010).

Josephine Namayanja has a broad interest in research primarily in data mining. Her research focuses on the application of data mining to detect persistent patterns associated to change in network behavior. This research poses potential benefits in the domain of cyber security. She has also worked on research in healthcare where she has proposed methods that can be utilized in disease management and patient care, particularly to address needs for individuals with Metabolic Syndrome and Type II Diabetes respectively. Her research has been published in prestigious venues such as IEEE Big Data, IEEE Intelligence and Security Informatics, and Journal of Medical Systems. Her research has also been recommended by principle scientists in the domain and voted among the top articles in the domain. She is currently working on various research-related projects on Post-Traumatic Stress Disorder (PTSD) and Cyber Security Analytics for Massive Communication Graphs.

Courses Taught

• Information Technology Problem Solving
• Information Technology Capstone

Research Interests

• Data Mining focusing on Temporal Data Mining, Subspace Mining, Spatial-Temporal Data Mining and Machine Learning.
• Big Data Analytics for Cyber Security and Holistic Analytics for Big Graphs.
• Health Care Analytics for Disease Management and Patient Care.

Professional Experiences

• Program Committee Member: IEEE International Conference on Data Mining 2015 PhD Forum.
• Peer Reviewer: Decision Support Systems (DECSUP), Software: Practice and Experience,  Encyclopedia of GIS, International Journal of Computational Models and Algorithms in Medicine (IJCMAM), International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS). 
• Research Associate and Team Lead: MBI Research Institute, Washington D.C.
• Member: American Association for the Advancement of Science (AAAS) Science & Technology Policy Fellows for Women of Color.
• Adviser: Global Health Corps (GHC)