André J. Butler

About

André J. Butler is an Industry Professor in the Civil, Urban, and Environmental Engineering Department at NYU Tandon School of Engineering, having joined the department in August 2022. Prior to this, he served as an associate professor and chair of the Environmental and Civil Engineering Department at Mercer University in Macon, Georgia. During his tenure at Mercer University, he received two School of Engineering Teacher of the Year Awards in 2003 and 2017, as well as the Minority Mentor Trailblazer of the Year Award for Excellence in Teaching in 2019. Dr. Butler’s teaching interests and research activities primarily focus on air quality and respiratory health. His research group has worked on understanding the spatio-temporal distributions of ozone and particulate matter in Georgia, improving access to clean drinking water in Malawi, Africa, and designing low-cost measurement techniques for indoor particulate matter in the Dominican Republic. His educational background includes a Ph.D. in Environmental Engineering from Georgia Institute of Technology, a Master of Engineering in Mechanical Engineering and Environmental Management from Carnegie Mellon University, and a Bachelor of Science in Mechanical Engineering from the University of Illinois-Urbana.

Research topics

• Artificial Intelligence
• Computer Science
• Biology
• Computational biology
• Immunology
• Genetics
• Bioinformatics

Selected publications

• Comprehensive Integration of Single-Cell Data

  Cell · 2019-06-01 · 16658 citations

  articleOpen access
  PublisherOA PDFDOI

• Integrated analysis of multimodal single-cell data

  Cell · 2021 · 15754 citations

  The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear c…

  PublisherOA PDFDOI

• Integrating single-cell transcriptomic data across different conditions, technologies, and species

  Nature Biotechnology · 2018-04-02 · 14555 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Developmental diversification of cortical inhibitory interneurons

  Nature · 2018-03-02 · 521 citations

  article
  PublisherDOI

• Integrated analysis of multimodal single-cell data

  bioRxiv (Cold Spring Harbor Laboratory) · 2020 · 484 citations

  Abstract The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset…

  PublisherOA PDFDOI

Frequent coauthors

• Rahul Satija

  68 shared

• Allison J. Greaney

  Fred Hutch Cancer Center

  40 shared

• Jesse D. Bloom

  Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa

  40 shared

• David J. Bacsik

  Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa

  40 shared

• Bernadeta Dadonaite

  37 shared

• Nicholas S. Heaton

  37 shared

• Efthymia Papalexi

  New York University

  26 shared

• John C. Marioni

  European Bioinformatics Institute

  21 shared

Awards & honors

• Mercer University Minority Mentor Trailblazer of the Year Aw…
• Mercer University School of Engineering Teacher of the Year…
• Mercer University School of Engineering Teacher of the Year…

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