Rumi Chunara

Associate Professor of Biostatistics

Associate Professor of Computer Science and Engineering, Tandon

Director of Center for Health Data Science

Professional overview

The overarching goal of Dr. Rumi Chunara's research is to develop computational and statistical approaches for acquiring, integrating and using data to improve population-level public health. She focuses on the design and development of data mining and machine learning methods to address challenges related to data and goals of public health, as well as fairness and ethics in the design and use of data and algorithms embedded in social systems.

At NYU, Dr. Chunara also leads the Chunara Lab, which develops computational and statistical methods across data mining, natural language processing, spatio-temporal analyses and machine learning, to study population health. Previously, she was a Postdoctoral Fellow and Instructor at HealthMap and the Children's Hospital Informatics Program at Harvard Medical School. She completed her PhD at the Harvard-MIT Division of Health Sciences and Technology and BSc at Caltech.

Education

BS, Electrical Engineering (Honors), Caltech

MS, Electrical Engineering and Computer Science, MIT

PhD, Medical and Electrical Engineering, MIT (Harvard-MIT Division of Health Sciences and Technology)

Honors and awards

Max Planck Sabbatical Award (2021)

speaker at NSF Computer and Information Science and Engineering Directorate Career Proposal Writing Workshop (2020)

Invited tutorial on Public Health and Machine Learning at ACM Conference on Health, Inference and Learning (2020)

Keynote at Human Computation and Crowdsourcing (2019)

Invited Speaker at Expert Group Meeting at United Nations Population Fund, Advances in Mobile Technologies for Data Collection Panel (2019)

Keynote at ''Mapping the Equity Dimensions of Artificial Intelligence in Public Health'', University of Toronto (2019)

Facebook Research Award (2019)

Gates Foundation Grand Challenges Exploration Award (2019)

NSF CAREER Award (2019)

MIT Technology Review Top 35 Innovators Under 35 (2014)

MIT Presidential Fellow (2004)

Areas of research and study

Health Disparities

Machine learning

Social Computing

Social Determinants of Health

Publications

Publications

Participatory epidemiology: Use of mobile phones for community-based health reporting

Freifeld, C. C., Chunara, R., Mekaru, S. R., Chan, E. H., Kass-Hout, T., Iacucci, A. A., & Brownstein, J. S. (n.d.).

Publication year

2010

Journal title

PLoS Medicine

Volume

7

Issue

12

10.1371/journal.pmed.1000376

Mass-based readout for agglutination assays

Chunara, R., Godin, M., Knudsen, S. M., & Manalis, S. R. (n.d.).

Publication year

2007

Journal title

Applied Physics Letters

Volume

91

Issue

19

10.1063/1.2806197

Abstract

Abstract

We present a mass-based readout for agglutination assays. The suspended microchannel resonator (SMR) is used to classify monomers and dimers that are formed during early stage aggregation, and to relate the total count to the analyte concentration. Using a model system of streptavidin functionalized microspheres and biotinylated antibody as the analyte, we obtain a dose-response curve over a concentration range of 0.63-630 nM and show that the results are comparable to what has been previously achieved by image analysis and conventional flow cytometry.

Phased array systems in silicon

Hajimiri, A., Komijani, A., Natarajan, A., Chunara, R., Guan, X., & Hashemi, H. (n.d.).

Publication year

2004

Journal title

IEEE Communications Magazine

Volume

42

Issue

8

Page(s)

122-130

10.1109/MCOM.2004.1321403

Abstract

Abstract

Phased array systems, a special case of MIMO systems, take advantage of spatial directivity and array gain to increase spectral efficiency. Implementing a phased array system at high frequency in a commercial silicon process technology presents several challenges. This article focuses on the architectural and circuit-level trade-offs involved in the design of the first silicon-based fully integrated phased array system operating at 24 GHz. The details of some of the important circuit building blocks are also discussed. The measured results demonstrate the feasibility of using integrated phased arrays for wireless communication and vehicular radar applications at 24 GHz.