Melissa Dowd Begg serves as Professor of Biostatistics at CUIMC and Vice Provost for Academic Programs at Columbia University. She received her ScD in Biostatistics from Harvard University. As Vice Provost, her office oversees university accreditation, approval processes for all new educational programs university-wide, educational agreements with domestic and international partner institutions, cross-school fellowships and awards, the support of interdisciplinary research and teaching, selected faculty leadership development programs, and the regular review of schools and institutes at Columbia. Begg served as co-director of the Irving Institute for Clinical and Translational Research, funded by a Clinical and Translational Science Award from NIH, from 2006 through 2018. Her areas of research focus include: advancing interdisciplinary science, training, and mentorship; graduate health professional education; and biostatistical methods in mental and oral health research. She has developed and directed a number of NIH-funded training programs, including two career development programs to promote diversity: one aimed at college undergraduates, introducing them to careers in the public health sciences (the BEST Program); and one aimed at diverse junior faculty, providing grant-writing advice, career support, and mentorship (the PRIDE Program). Another of her programs offered mentorship in comparative effectiveness research methods to junior and mid-level faculty (the IMMERSE in CER Program). Begg received the university-wide Presidential Award for Outstanding Teaching and the Mailman School Teaching Award from the Graduating Class in 2006. In 2012, she was elected a Fellow of the American Statistical Association and received the Lagakos Distinguished Alumni Award in Biostatistics from the Harvard School of Public Health.
Honors & Awards
Presidential Teaching Award, Columbia University, 2006
Award for Teaching Excellence, Mailman School of Public Health, 2006
Fellow of the American Statistical ASsociation, elected 2012
Lagakos Distinguished Alumni Prize from Harvard School of Public Health Department of Biostatistics, 2012
Omicron Kappa Upsilon, Dental Honor Society, inducted 2012
Areas of Expertise
Begg MD, Fried LP, Glover JW. Delva M, Wiggin M, Hooper L, Saxena R, de Pinho H, Slomin E, Walker JR, Galea S (2015). Measuring the impact of curricular change: Short-term results from the new Columbia Core Curriculum. American Journal of Public Health 105: e7-e13.
Begg MD, Bennet LM, Gadlin H, Moss M, Tentler J, Schoenbaum E (2015). Graduate Education for the Future: New Models and Methods for the Clinical and Translational Workforce. Clinical and Translational Science 8: 787-792.
Pfirman SL, Begg MD (2012). Perspective: Troubled by Interdisciplinarity? Science Career Magazine, Issue for April 06, 2012, accessed 06.21.2012 at http://sciencecareers.sciencemag.org/career_magazine/previous_issues/articles/2012_04_06/caredit.a1200040.
Meyers FJ, Begg MD, Fleming M, Merchant C Strengthening the Career Development of Clinical Translational Scientist Trainees: A Consensus Statement of the Clinical Translational Science (CTSA) Research Education and Career Development Committees Clinical and Translational Science 5(2) 132-137 2012
Begg MD, Vaughan RD Are biostatistics students prepared to succeed in the era of interdisciplinary science? (And how will we know?) The American Statistician 65(2) 71-79 2011
Kulage KM, Larson EL, Begg MD Sharing Facilities & Administrative Cost Recovery to Facilitate Interdisciplinary Research Academic Medicine 86(3) 394-401 2011
Huskins WC, Silet K, Weber-Main AM, Begg MD, Fowler VG, Hamilton J, Fleming M Identifying and Aligning Expectations in a Mentoring Relationship Clinical and Translational Science 4(6) 439-447 2011
Begg MD, Parides MK Separation of individual-level and cluster-level covariate effects in regression analysis of correlated data Statistics in Medicine 22 2591-2602 2003
Begg M Analyzing k(2x2) tables under cluster sampling Biometrics 55 302-307 1999
Desai M, Begg MD A comparison of regression approaches for analyzing clustered data American Journal of Public Health 98 1425-1429 2008