The Data Science Lunch Seminar Series is an informal weekly gathering of NYU Data Science affiliated persons to discuss data science related topics. Each week there is a 30 minute presentation, over lunch (provided), with additional time for conversation and questions. The series meets Wednesdays from 12:30-1:30 PM at the Center for Data Science.



February 1, 2017
Justin Salamon, “Audio Source Identification in Urban/Bio-Acoustic Environments”.

February 8, 2017
Alexander Bock, “OpenSpace — Moving from What to How in Science Communication”

February 15, 2017
Nicola Barbieri, Tumblr

February 22, 2017
Yannis Liodakis, “Revealing the intrinsic timescale distribution in the most active of galaxies”

March 1, 2017
Piotr Brodka, Wroclaw University of Science and Technology (Poland), “Current Challenges in the Area of Spreading Processes in Multilayer Networks”

March 8, 2017
Jaime Earnest, DoD, “Future State: Big Data and Analytics for Better Governance”

March 15, 2017
Spring Break – No lunch seminar

***SPECIAL DAY AND TIME*** March 23, 2017, 1:30-2:30
Noemi Derzsy, RPI, NASA DataNauts, “Open NASA Data: From API to Data Analysis”

March 29, 2017
Partha Mithra

April 5, 2017

April 12, 2017
Yana Volkovich, AppNexus

April 19, 2017
Hannah Wallach, Data and Society

April 26, 2017
Ciro Cattuto, Fondazione ISI

May 3, 2017
Mor Naman, “Patterns of Large-Scale Attention”

MAY 10, 2017
Enrico Bertini


2016-2017 Series

September 14, 2016
Juliana Freire, Executive Director of Moore-Sloan Data Science Environment

September 21, 2016
Eleni Zacharatou, “Indexing the Brain”

September 28, 2016
Michael Z. Gill, “The Economic Benefits of Conflict? Estimating Defense Firm Responses to Major Events in U.S. Foreign Policy”

October 5, 2016
Ravi Shroff

October 12, 2016 (special time 1:00-2:00pm)

October 19, 2016
Anil Kocak

October 26, 2016
***No lunch, MSDSE 2016 Data Science Summit***

November 4, 2016 (special day, Friday)
Shankar Iyer, Quora

November 9, 2016
danah boyd, Microsoft Research

November 16, 2016
Max Sklar, Foursquare

November 21, 2016 (special day, Monday)
Mike Williams, Fast Forward Labs ***CANCELED***

November 30, 2016
Manuel Garcia-Herranz, UNICEF Innovation

December 7, 2016
Jason Anastasopoulos

December 14, 2016
Rossano Schifanella, University of Torino

2015-2016 Series

November 9th
Meredith BroussardAssistant Professor, Journalism
Topic: Data for Democracy: Uncovering Stories in Government Data

November 16th
Juan BelloAssociate Professor, Music Technology

November 23rd
No meeting

November 30th
Mohamed ZahranClinical Associate Professor, Computer Science
Topic: Hardware Advances Benefiting Data Science

December 7th
No Meeting

December 14th
Emily Miraldi, Postdoctoral Researcher, Simons Center for Data Analysis

January 27, 2016
Lightning talks by Data Science Fellows and Postdocs, NYU, Center for Data Science

February 3, 2016 (special time: 12-1pm)
Heiko Müller, NYU, CDS

February 10, 2016
Kyle Cranmer, NYU, Physics

February 17, 2016
Lars Backstrom, Facebook

February 24, 2016 (special time: 12-1.30pm)
Joint PRIISM/CDS talk: Michael Betancourt, University of Warwick

March 2, 2016
Alfred Spector, CTO of Two Sigma

March 9, 2016
Uri Shalit, NYU, Computer Science

March 16, 2016
No seminar (Spring break)

March 23, 2016
Michael Blanton, NYU, Physics

March 31, 2016 (special day: THURSDAY)
Daniel Fernández, NYU, CDS

April 6, 2016
Rumi Chunara, NYU, CS & Engineering, Global Institute of Public Health

April 13, 2016
Andy Guess, NYU, Social Media Lab

April 20, 2016
Boris Leistedt, NYU, Center of Cosmology and Particle Physics

April 27, 2016
Sunandan Chakraborty, NYU, CDS

May 4, 2016
Daphna Harel, NYU, Steinhardt

May 11, 2016
Laura Norén, NYU, CDS

2014-2015 Series

October 28th
Ken Benoit, Visiting Professor from the London School of Economics
Topic: Quantitative Text Analysis for the Social Sciences (Using R): Natural language processing and quantitative analysis of social and political texts, using an R package called quanteda ( that he is developing.

November 5th
Jonathan GoodmanProfessor of Mathematics
Topic: The hermeneutics of MCMC sampling: points of view about samplers, some of which don’t depend on your point of view.

November 13th
Greg DoblerResearch Scientist at CUSP and a Research Assistant Professor of Physics at NYU
Better Cities through Imaging: I will describe how persistent, synoptic imaging of the NYC skyline can be used to better understand the city (in analogy to how persistent, synoptic imaging of the sky can be used to better understand the heavens), giving specific examples related to energy consumption, public health, and air quality which can lead to improved city functioning and quality of life.

December 1st
Pablo BarberaPhD Candidate in Politics
Topic: How Social Media Reduces Mass Political Polarization: 
Using a new method to estimate the ideological positions of social media users and their communication networks over time, I provide evidence that exposure to dissonant political messages on social media induces political moderation. For the paper, click here.

December 9th
Mike O’NeilAssistant Professor, School of Engineering and Courant Institute
Topic: Fast Algorithms for Gaussian Processes

February 5th
Ying LuAssistant Professor of Applied Statistics at NYU and
Dr. Preeti RaghavanAssistant Professor at NYU Medical Center
Topic: Quantifying Feedforward Control: A Linear Scaling Model for Fingertip Forces and Object Weight
In this paper, we fit a linear growth curve to the biomechanical data of grasping  in order to understand the relationship between fingertip forces and object weight among healthy subjects. Our results show evidence of feedforward control during the grasping task when healthy subject grasp/lift an object with familiar weights.

February 23rd
Daniela HuppenkothenMoore Sloan Data Science Fellow at NYU
Topic: Exploring the Violent Universe: Astrophysical Data (Analysis) at High Energies
This talk will give an introduction into astronomy at very short wavelengths, where we see the universe’s most extreme phenomena, and showcase typical data analysis problems—some of which we are working on at the CDS—which we have to solve in order to understand the underlying physical processes.

March 3rd
Aaditya RanganAssociate Professor of Mathematics at NYU
Topic: Efficient Methods for Detecting Low Rank Structure
Discussion of some methods for finding low-rank submatrices within gene-expression data; It will be necessary to correct for case-control status as well as covariates.

March 11th
Tae Hong ParkAssociate Professor of Composition and Music Technology at NYU
Topic: CityGram: Sensing Urban Soundscapes
Dynamic mapping of non-ocular spatio-acoustic energies.

March 27th
Lakshminarayanan SubramanianAssociate Professor of Computer Science at NYU
Topic: Societal Network Science
Predicting Socio-economic indicators from real-time news streams

April 8th
Patrick WolfeProfessor of Statistics and Honorary Professor of Computer Science at University College London
Topic: Network Analysis and Nonparametric Statistics
Networks are ubiquitous in today’s world.  Any time we make observations about people, places, or things and the interactions between them, we have a network.  Yet a quantitative understanding of real-world networks is in its infancy, and must be based on strong theoretical and methodological foundations.  The goal of this talk is to provide some insight into these foundations from the perspective of nonparametric statistics, in particular how trade-offs between model complexity and parsimony can be balanced to yield practical algorithms with provable properties.

April 13th
Karen AdolphProfessor of Psychology and Neural Science at NYU
Topic: Databrary and Datavyu: Coding, Sharing, and Repurposing Video
A description of the promises and challenges of coding, sharing, and repurposing video data

April 23rd
Yoni HalpernGraduate Student in the Computer Science Department at NYU
Topic: Provable Methods for Discrete Factor Analysis
This talk will cover methods for structure and parameter learning in latent variable models and discuss an application for learning diagnosis models from unstructured data in electronic medical records.

April 29th
Joshua TuckerProfessor of Politics at NYU
Topic: Using Social Media to Study Politics
How can we use social media to study the political behavior of masses and elites?  What we can do, what we can sort of do, and what we’d like to be able to figure out how to do…

May 5th
Dan BrownAssociate Professor of Computer Science at the University of Waterloo
Topic: Do better lyrics make a hit?  Complexity of rhymes in music lyrics

2013-2014 Series

September 14th
Jean-Daniel Fekete, Senior Research Scientist, INRIA Saclay
Topic: Progressive Analytics: A New Programming Paradigm for Large-Scale Data Exploration

September 21st
Kyunghyun ChoAssistant Professor, Computer Science and Data Science
Topic: Lost in Interpretability
I hear from non-ML as well as ML researchers once a while that they find it difficult to work with neural networks due to the lack of interpretability compared to other simpler models which are in many cases some variants of linear models. This has always made me wonder if there is a natural tradeoff between interpretability and modelling accuracy. In this talk, however, I argue that no such tradeoff exists, which has been argued already more than a decade ago by Breiman (2001). Furthermore, I present some recent results from deep learning showing that seemingly complex models, such as deep neural nets and recurrent neural nets, are in fact interpretable, if we try hard enough.

September 28th
Arthur Spirling, Associate Professor, Politics and Data Science

October 5th
No meeting

October 12th
Kenneth J. Kurtz, Associate Professor, Psychology at SUNY Binghamton

October 19th
No meeting, see special time Thursday of that week

October 22nd (Thursday, special time)
Bingni BruntonAssistant Professor, Biology and Data Science at University of Washington

October 26th
Rachid OunitPh.D Candidate, Computer Science, UC Riverside
Topic: Classification of metagenomic sequences: how to make it faster and more accurate

November 2nd
Dan CervoneData Science Fellow, Center for Data Science