Sara Lopez-Pintado, PhD

Associate Professor
  • Department of Health Sciences
  • Faculty

Résumé/CV:
Office: 316 RB
Phone: 617.373.8249
Email: s.lopez-pintado@northeastern.edu

Dr. Lopez-Pintado has been focused since the beginning of her career on the study, development and teaching of statistical methodologies and their applications to fields such as Biomedicine. She obtained a BS in Mathematics (major in Statistics) from the University of Seville, Spain (1994-1998) and a Ph.D. in Statistics from the University Carlos III of Madrid, Spain (1998-2005). Her Ph.D. thesis ‘On the concept of depth for functional data’ received the best thesis of the year award. She spent one year as an Instructor and Postdoctoral Associate in the Department of Statistics at Rutgers University, and after returning to Spain she was appointed Assistant Professor in the Department of Quantitative Methods and Statistics at University Pablo de Olavide in Seville. In 2007-2008 she visited the Department of Biostatistics in the Mailman School of Public Health at Columbia University, supported by a grant from the Spanish Government. Subsequently, in 2010 Dr. Lopez-Pintado was appointed as Assistant Professor in the Department of Biostatistics at Columbia University. During her time as an Assistant Professor at Columbia, she combined methodological and collaborative research with teaching and service duties. She is currently an Associate Professor in the Department of Health Sciences at Northeastern University. Her research is focused on the development of robust nonparametric and computational methods for ranking and analyzing high-dimensional data such as functions, medical images and time series. She has published several relevant and well cited papers in the field of robust functional data analysis. Her goal is to develop new robust methods for analyzing and modeling high-dimensional data sets, such as those made available by the technological advances in medical and health sciences. Dr. Lopez-Pintado is interested in collaborating in interdisciplinary research projects in Biomedicine. She is also passionate about teaching statistics and its applications to undergraduate and graduate students.

 

Education:

  • September, 2005 – August 2006, Postdoctoral training, Department of Statistics, Rutgers University, New Jersey, USA.
  • September, 1998 – August, 2005, PhD (Statistics) July, 2005, Department of Statistics and Econometrics, University Carlos III of Madrid, Spain.

– Thesis title: On the concept of depth for functional data, Advisor : Juan Romo

– Best thesis award in University Carlos III of Madrid, 2005

  • October, 1994 – July, 1998, BA Mathematics (field statistics), University of Sevilla, Spain.

 

Research Interests:

  • Functional data analysis, nonparametric statistics, data depth, robust statistics, imaging data, growth curves, mental health

 

Selected Honors & Awards:

  • Nominated on December 2017 as ‘women in science spotlight’ by a Columbia University student group of women scientists
  • Calderone Prize Award for Junior Faculty in 2013. Columbia University. New York
  • August 2012, Fellowship to participate as an invited speaker in ICORS12, Vermont, USA
  • March 2011: Invitation with financial support to participate in the Workshop: Level sets and depth contours in high-dimensional data. Oberwolfach, Germany
  • Best thesis award in 2005. University Carlos III of Madrid, Spain

 

Selected Recent Publications:

  • Lopez-Pintado S and Wrobel J (2017). Robust nonparametric tests for imaging data based on data depth. Stat, 6, 405-419.
  • Wilson PT, Baiden F, Brooks JC, Morris MC, Giessler K,  Punguyire D, Apio G, Agyeman-Ampromfi A, Lopez-Pintado S,  Sylverken J,  Nyarko-Jectey K, Tagbor H and Moresky RT (2017). Continuous positive airway pressure for children with undifferentiated respiratory distress in Ghana: an open-label, cluster, crossover trial. Lancet Global Health, 5: 615-623.
  • Lopez-Pintado S, Sun Y, Lin JK and Genton MG (2014). Simplicial Band depth for multivariate functional data. Advances in Data analysis and Classification 8: 321-338.
  • Alonso A, Casado D, Lopez-Pintado S, Romo J (2014). Functional data based methods for time series classification. Journal of Classification, 31: 325-350.
  • Lopez-Pintado S and McKeague I (2013). Recovering gradients from sparsely observed functional data. Biometrics, 69(2):396-404.

 

Selected Public Service:

  • Senior statistician from 2015-2018 in Clinical and Translational Research Award at Irving Institute at Columbia University
  • Associate Editor of Journal of Computational and Graphical Statistics since August 2018
  • 2015-2018 Member of the Master Admission Committee, member of Qualifying Exam Committee, member of Recruitment Committee at the Department of Biostatistics, Columbia University and organizer of the seminars in the Department of Biostatistics during spring 2016
  • Fall 2018. Member of the Population and Health Committee at Department of Health Sciences, Northeastern University