All posts by Henry Adams

Conference on Geometric Data Analysis, May 20-23, 2019, on the University of Chicago main campus in Hyde Park

Conference on Geometric Data Analysis, May 20-23, 2019, on the University of Chicago main campus in Hyde Park.

This conference will bring together experts from around the world in the combination of geometrical or topological methods with probabilistic and statistical ones for the study of data.  Different ideas have been found valuable in the handling of different kinds of data, and we hope to promote discussions of what works and what fails, and when and why.

Invited Speakers

Yuliy Baryshnikov, Electrical and Computer Engineering, University of Illinois

Mikhail Belkin, Computer Science, Engineering and Statistics, Ohio State University

Paul L. Bendich, Mathematics, Duke University

Omer Bobrowski, Electrical Engineering, Technion, Institute of Technology, Israel

Jeff Brock, Yale University

Gunnar Carlsson, Mathematics, Stanford University

Daniela Egas Santander, Topology and Neuroscience, Ecole Polytechnique Fédérale de Lausanne, Switzerland

Tamal Krishna DeyComputer Science and Engineering, Ohio State University

Tingran Gao, Statistics, University of Chicago

Herbert Edelsbrunner, Computer Science and Mathematics, Institute of Science and Technology, Austria

Clément Levrard, Probabilités, Statistique et Modélisation, Université Paris Diderot, France

Mauro Maggioni, Mathematics, John Hopkins University

Facundo Mémoli, Mathematics, Computer Science and Engineering, Ohio State University

Bertrand Michel, Informatique et Mathématiques, Ecole Centrale de Nantes, France

Ezra Miller, Mathematics, Duke University

Sayan Mukherjee, Statistical Science, Duke University

Takashi Owada, Statistiques, Purdue University

Gennady Samorodnitsky, Operations Research and Information Engineering, Cornell University

Benjamin Schweinhart, Mathematics, Ohio State University

Amit Singer, Applied and Computational Mathematics, Statistics and Machine Learning, Princeton University

Jonathan Taylor, Statistics, Stanford University

Katharine Turner, Mathematical Sciences, National University, Australia

Details about the conference are available on our website:

Please note: 

  • Travel funds are available to PhD Students, Postdoctoral Students and Early CareerAcademics.  Please submit your application by January 9, 2019.

You will be asked to submit your CV, a brief research statement (up to 250 words), and a brief statement explaining why and how attending this conference will contribute to your research (up to 250 words). In addition, please ask someone who is familiar with your work (your academic advisor or your mentor) to send a brief letter supporting your application to, by January 9, 2019. The letter should be addressed to the GDA 2019 Selection Committee.

  • Poster sessions will be organized. If you'd like your poster to be considered, please submit your application by January 9, 2019.

If you have any questions, please email Sylvie at

We hope to see you in May!

Scientific Committee: Robert Adler (Technion), Frederic Chazal (INRIA), Shmuel Weinberger (Chicago)

Postdoc in applied topology at Swansea

Swansea University in Wales in currently advertising a 2 year postdoctoral research position in topological data analysis.

As part of the major EPSRC-funded Oxford-Swansea-Liverpool Centre for Topological Data Analysis, we are looking for a postdoctoral researcher to join the Swansea team in investigating applications of topology to data science and physics. The Swansea team consists of Pawel Dlotko, Jeff Giansiracusa, Biagio Lucini, and PhD students.

We are particularly interested in applicants with background in any of these areas:
* Computational topology / geometry
* Computational physics and lattice gauge theory
* Data science or machine learning

The ideal candidate will have some computer coding experience and be willing to learn new things.

Full details and application instruction can be found here:

Salary: from £33,518 to £38,833

Closing date: 4 November 2018

Please contact
Pawel Dlotko ( ) or
Jeff Giansiracusa ( )
if you are interested.

Applied Mathematical Modeling with Topological Techniques, ICERM, August 5-9, 2019

We are happy to announce an ICERM topical workshop on “Applied Mathematical Modeling with Topological Techniques”, August 5-9, 2019. Please see our webpage

Mathematical modelers face a variety of challenges, including summarizing large data sets to understand and explore a system of interest, inferring the model parameters most accurate for describing a given data set, and assessing the goodness-of-fit between data sets. Computational topology provides a lens through which these challenges may be addressed. At the same time, just as topological techniques provide opportunities for modelers, the challenges that modelers face give rise to opportunities for applied topologists. For instance, topologists may develop techniques that make model predictions based on the topology of experimental or simulation data, that analyze time-varying data, or that turn model outputs into formats suitable for machine learning.

This workshop brings together the applied mathematical modeling and applied topology communities, aiming to give modelers exposure to topological techniques still not commonly used in their community, and to give topologists exposure to modeling challenges that might stimulate the development of new techniques.

The workshop will include tutorial sessions on modeling and on applied topology, during which participants will learn by doing hands-on computational exercises. Because the broad goal of this workshop is to encourage collaboration between members of the applied modeling and topology communities, a significant portion of the week will be devoted to participants initiating research on problems proposed by the organizers. The research problems will afford the potential for continued collaboration beyond the workshop.

The organizers
Henry Adams, Maria D’Orsogna, Rachel Neville, Jose Perea, Chad Topaz

TRIPODS Summer Bootcamp on Topology and Machine Learning, August 2018

We invite you to apply to attend the TRIPODS Summer Bootcamp on Topology and Machine Learning. The bootcamp will be hosted at ICERM during the week of August 6-10, 2018. Applications are currently being accepted, and will be accepted until July 5. For more information, please see the webpage at

Henry Adams, Colorado State University
Jeffrey Brock, Brown University
Melissa McGuirl, Brown University
Bjorn Sandstede, Brown University
Isaac Solomon, Brown University

Postdoctoral Research Associate: Large Scale Brain Network Computation

Postdoctoral positions are available for large-scale brain image and network analysis at the University of Wisconsin-Madison. The postdoctoral fellow will work with professor Moo K. Chung ( on developing new innovative statistical and machine learning methods for large scale brain images and networks.

Candidates should have received or expected to receive PhD degree or equivalent in mathematics, CS, EE, statistics, physics, biomedical engineering, psychology, neuroscience or related areas. Previous neuroimaging research experience is a plus but not necessary. Expertise in the following areas may be useful: matrix computation, time series analysis, manifold learning, topological data analysis, functional analysis, graph & network analysis.

Interested candidates should email CV (with the name of references) and two representative papers to Moo K. Chung (

GETCO 2018 Conference

Here is a conference announcement:

GETCO 2018
September 10-14, 2018
Oaxaca, Mexico
The GETCO conference series focus on applications of algebraic topology in computer science with special emphasis in concurrency, distributed computing, networking and other situations related to systems of sequential computers that communicate with each other. It is aimed at mathematicians and computer scientists working in or interested in these subjects, including researchers and graduate students.

A special issue of the Journal of Applied and Computational Topology will be dedicated to selected papers from the conference.

Armando Castañeda, Universidad Nacional Autónoma de México
Dmitry Feichtner-Kozlov, University of Bremen.
Eric Goubault, École Polytechnique, Paris.
Maurice Herlihy, Brown University, USA.
Ran Levi, University of Aberdeen.
Martin Raussen, Aalborg University.

Job opening in Applied and Computational Topology advertised by the Queen Mary, University of London

From Michael Farber:

Dear colleagues,

I want to attract your attention to the job opening in Applied and Computational Topology advertised by the Queen Mary, University of London (Lecturer/Senior Lecturer in Applied and Computational Topology - QMUL13442), see

The salary range is £40,865 - £60,109.

Closing date: 11 January, 2018.

Data science (especially topology position at The Henry M. Jackson Foundation


Position Description
Data Scientist

Position No: FLSA Status: Exempt
Grade: EEO Category/Job Group:

JOB SUMMARY We are seeking a Data Scientist to join the Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO). ACESO aims to identify host-based markers capable of accurately diagnosing and prognosing patients with severe infections in austere settings and transitioning those markers to point-of-care assay platforms. The Data Scientist is responsible for analyzing complex data and developing insights through the use of statistical models, data mining, and data visualization techniques.

This position is based at The Henry M. Jackson Foundation (HJF) in Bethesda, Maryland, although alternate arrangements will be considered. HJF provides scientific, technical and programmatic support services for the worldwide ACESO program.


1. Analyzes complex datasets including RNA sequence data, proteomic, phosphoproteomic, and metabolomics data. Applies advanced statistical and predictive modeling techniques and data visualization approaches. Develops innovative approaches to answer research questions.

2. Integrates and prepares large datasets, develops specialized database and computing environments as needed.

3. Provides subject matter expertise as needed, including recommendations on data collection and integration.

4. Communicates results on a regular basis with the science team and key stakeholders, and prepares presentations and reports as needed.

5. Performs other duties as required.

Required Knowledge, Skills, and Abilities:
 Experience with complex datasets
 Proficiency in statistical analysis, forcasting/predictive analytics, and algorithm optimization.
 Experience with data mining/pattern recognition approaches; experience with topological data analysis preferred
 Strong programming skills
 Able to develop solutions to loosely defined problems
 Able to communicate effectively

Minimum Education/Training Requirements: PhD in mathematics, statistics, computer science or related field. At least 2 years relevant experience.

Physical Capabilities: Extended periods of sitting

Required Licenses, Certification or Registration: n/a

Supervisory Responsibilities/Controls: May provide guidance to junior analysts

Work Environment: Office or laboratory environment

Any qualifications to be considered as equivalents, in lieu of stated minimums, require the prior approval of the Director of Human Resources