Research Assistant Professor
Department of Epidemiology
University of Pittsburgh
130 DeSoto Street, 127 Parran Hall
Pittsburgh, PA 15260
Voice: 412-624-4219
Fax: 412-624-3775
E-mail: vugam@edc.pitt.edu


Research Interests

• Application of Biostatistical Methods in Public Health, Women's Health, Cancer Research, Neurophysiology
• Methodology Improvements for Health Research and Clinical Assessment

Dr. Vuga's research interests are particularly focused on improving methodology for applied research covering epidemiological as well as medical research. Another field of her interest is the application of biostatistical methods including longitudinal analysis and missing data. Her major areas of application include women's health, cancer, and brain functioning.

Education & Training

• Graz University of Technology - M.S. Engineering Mathematics, 1995
• Vienna University of Technology - Ph.D. Engineering Mathematics, 2001
• University of Pittsburgh - M.S. Biostatistics, 2005

Honors and Awards

• Elected 2006, Delta Omega Honor Society in Public Health - Omicron Chapter
• 2006 Thesis Award, The Best Master Thesis of the year 2005 in the Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, awarded by Delta Omega Society, The National Honor Society in Public Health
• 2007 Annual Honor Convocation, Honored for Outstanding Academic Achievements, University of Pittsburgh

Teaching

• EPIDEM 2185 - Introduction to SAS

Current Projects

    Lead Statistician

• 2006-2009

Study of Women's Health Across the Nation III (SWAN), Coordinating Center, NIA


• 2009-2014

Study of Women's Health Across the Nation IV (SWAN), Coordinating Center, NIA

    Biostatistician

• 2008-2010

Lung Cancer SPORE Developmental Research Program

Selected Publications

Crawford S., Santoro N., Laughlin G.A., Sowers M.F., McConnell D., Sutton-Tyrrell K., Weiss G., Vuga M., Randolph J., Lasley B. Circulating Dehydroepiandrosterone Sulfate Concentrations during the Menopausal Transition. J. Clin. Endocrinol. Metab., In Press.

Scuteri A., Vuga M., Najjar S.S., Mehta V., Everson-Rose S.A., Sutton-Tyrrell K., Matthews K., Lakatta E.G. 2008. Education eclipses ethnicity in predicting the development of the metabolic syndrome in different ethnic groups in mid-life: the Study of Women's Health Across the Nation (SWAN). Diabetic Medicine, 25, 1390-1399.

Vuga M., Fox N.A., Cohn J.F., Kovacs M., George C. 2008. Long-term stability of electroencephalographic asymmetry and power in 3 to 9 year-old children. Int. J. Psychophys., 67, 70-77.

Kapoor A., Chow S., Bhargava R., Surti U., Rosenzweig M., Vuga M., Brufsky A. 2007. (Abstract) Topoisomerase II-alpha (TOP2A) gene co-amplification does not predict response to therapy and survival in Her-2 neu positive metastatic breast cancer. J. Clin. Oncol., 2007 ASCO Annual Meeting Proceedings Part I., 25, 18S:21108.

Vuga M., Fox N.A., Cohn J.F., George C., Levenstein R.M., Kovacs M. 2006. Long-term stability of electroencephalographic asymmetry in adults with history of depression, Int. J. Psychophys., 59, 107-115.

Galles S., Essl M., Santucci A., Cohn J.F., Fox N.A. 2004. (Abstract) Long-term stability of heart period and heart rate variability in adults with history of depression. Psychophysiology 41, Supplement 1, 31.

Essl M., Rappelsberger P. 1999. EEG coherence as a function of the recording technique: Is Laplacian a useful approach? Med. Biol. Eng. Comput. 37, Supplement 2, Part I, 478-479.

Essl M., Rappelsberger P. 1998. EEG coherence and reference signals: experimental results and mathematical explanations. Med. Biol. Eng. Comput., 36, 399-406.

Essl M. 1998. Simulation of EEG signals with auto-regressive models. In Rattay, F. ( Ed.) Proceedings TU-BioMed Symposium 1998, Brain Modelling, ARGESIM Report No. 10, 1998, 15-18.

Essl M., Rappelsberger P. 1998. EEG coherence and the reference problem: Simulation of signals with autoregressive models. In Boenick U., M. Schaldach (Eds.), Biomedizinische Technik, Band 43, Ergänzungsband 2, 37-39.

Essl M., Rappelsberger P. 1997. Dependence of coherence using different recording techniques. In: Quantitative and Topological EEG and MEG Analysis, Witte H., Zwiener U., Schack B., Doering A. (Eds.), Druckhaus Mayer Verlag, Jena, 440-442.