Björn Sandstede

About

Björn Sandstede is the Alumni-Alumnae University Professor of Applied Mathematics in the Division of Applied Mathematics at Brown University. His research focuses on applied dynamical systems, data science, and computational and mathematical biology. Before moving to Brown, he held faculty positions at The Ohio State University and the University of Surrey. Sandstede has received numerous awards including an Alfred P Sloan Research Fellowship, the SIAM JD Crawford Prize, a Royal Society Wolfson Research Merit Award, the Elsevier Jack Hale Award, and teaching and mentoring awards from Brown University. He was also selected as a Fellow of the Society for Industrial and Applied Mathematics. At Brown, he has served as Department Chair for nine years and as Director of Brown's Data Science Initiative for two years.

Research topics

• Artificial Intelligence
• Machine Learning
• Data Mining
• Computer Science
• Theoretical computer science
• Programming language
• Algorithm

Selected publications

• SCOT: Single-Cell Multi-Omics Alignment with Optimal Transport

  Journal of Computational Biology · 2022 · 127 citations

  Recent advances in sequencing technologies have allowed us to capture various aspects of the genome at single-cell resolution. However, with the exception of a few of co-assaying technologies, it is not possible to simultaneously apply different sequencing assays on the same single cell. In this scenario, computational integration of multi-omic measurements is crucial to enable joint analyses. This integration task is particularly challenging due to the lack of sample-wise or feature-wise corres…

  DOI

• Parameter Identifiability in PDE Models of Fluorescence Recovery After Photobleaching

  Bulletin of Mathematical Biology · 2024-03-02 · 21 citations

  articleSenior author
  PublisherDOI

• Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion

  npj Systems Biology and Applications · 2023-09-14 · 21 citations

  articleOpen access

  Different cell types aggregate and sort into hierarchical architectures during the formation of animal tissues. The resulting spatial organization depends (in part) on the strength of adhesion of one cell type to itself relative to other cell types. However, automated and unsupervised classification of these multicellular spatial patterns remains challenging, particularly given their structural diversity and biological variability. Recent developments based on topological data analysis are intri…

  PublisherOA PDFDOI

• Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation

  PLoS Computational Biology · 2025-05-08 · 7 citations

  articleOpen access

  Inferring gene regulatory networks from gene expression data is an important and challenging problem in the biology community. We propose OTVelo, a methodology that takes time-stamped single-cell gene expression data as input and predicts gene regulation across two time points. It is known that the rate of change of gene expression, which we will refer to as gene velocity, provides crucial information that enhances such inference; however, this information is not always available due to the limi…

  PublisherDOI

• Quantifying Different Modeling Frameworks Using Topological Data Analysis: A Case Study with Zebrafish Patterns

  SIAM Journal on Applied Dynamical Systems · 2023-11-29 · 4 citations

  article

  .Mathematical models come in many forms across biological applications. In the case of complex, spatial dynamics and pattern formation, stochastic models also face two main challenges: pattern data are largely qualitative, and model realizations may vary significantly. Together these issues make it difficult to relate models and empirical data—or even models and models—limiting how different approaches can be combined to offer new insights into biology. These challenges also raise mathematical q…

  PublisherDOI

Recent grants

• Dynamics near coherent structures

  NSF · $600k · 2009–2014

• Nonlinear stability of patterns

  NSF · $342k · 2014–2018

• RTG: Integrating Dynamics and Stochastics (IDyaS)

  NSF · $2.1M · 2012–2019

Frequent coauthors

• Arnd Scheel

  University of Minnesota

  44 shared

• Katherine M. Kinnaird

  31 shared

• Alexandria Volkening

  Purdue University West Lafayette

  31 shared

• Ruth Wertz

  Valparaiso University

  30 shared

• Karl Schmitt

  Trinity Christian College

  30 shared

• Linda L. Clark

  25 shared

• Melissa McGuirl

  Brown University

  24 shared

• Rebecca Santorella

  23 shared

Education

• Doctor of Philosophy, Fachbereich Mathematik

  Universität Stuttgart

  1993

• Master of Science, Institut für Mathematik

  Universität Heidelberg

  1990

Awards & honors

• Alfred P Sloan Research Fellowship
• SIAM JD Crawford Prize
• Royal Society Wolfson Research Merit Award
• Elsevier Jack Hale Award
• Fellow of the Society for Industrial and Applied Mathematics

Similar researchers at Brown University

• Matthew Harrisonh-54
• Zhicheng Wangh-40
• Hongjie Dongh-38