News & Events

Employment

 
 
 
 
 
May 2018 – August 2018
Yorktown Heights, NY

AI Research Intern

IBM Research

Convolutional deep neural networks pruning for multiple objectives, in PyTorch.
 
 
 
 
 
October 2014 – June 2016
London

Game Analyst - Data Science Team

Zynga (Naturalmotion LTD)

Data processing and modeling for live and in development games, mainly Dawn of Titans. Main projects:

  • Behavior-based clustering for the user base;
  • Supervised classification task mainly targeting user retention and monetization;
  • Automatic KPI reporting for company-wide distribution;
  • ETL data pipelines in Python for live internal dashboards.

Recent Publications

. Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. International Conference on Machine Learning (ICML), 2020.

Preprint Code

. Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations. International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

Preprint Code

. Predictive Inference of a Wildfire Risk Pipeline in the United States. In NeurIPS 2019 Tackling Climate Change with Machine Learning Workshop (Spotlight), 2019.

Preprint Code Video

. Feature Engineering for Entity Resolution with Arabic Names: Improving Estimates of Observed Casualties in the Syrian Civil War. In NeurIPS 2019 AI + HADR Workshop (Spotlight), 2019.

Preprint Code Video

. When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments. In NeurIPS 2019 Causal Machine Learning Workshop, 2019.

Preprint

. Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference. In Astronomy and Computing, 2019.

Preprint PDF Code DOI

. A Flexible Pipeline for Prediction of Tropical Cyclone Paths. In ICML 2019 CCAI Workshop, 2019.

Preprint Code

. Architectural Distant Reading Using Machine Learning to Identify Typological Traits Across Multiple Buildings. In CAAD Futures, 2019.

PDF Code

. Lebesgue Regression. In NeurIPS 2018 CRACT Workshop, 2018.

Preprint

. Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder. In MNRAS, 2018.

Preprint PDF Code

Skills

Statistics

Machine Learning

Data Analysis

R

Python

2.7 - 3.6

SQL

MySQL - Vertica SQL

Teaching and
Mentoring

Aug 2016

Advising and Mentoring

Department of Statistics & Data Science, Carnegie Mellon University

Supervised research carried out by undergraduates students in different occasions:

  • Summer Undergraduate Research Experience (SURE, Summer 2017) - Advised a team working on automatic typing discrimination and handwritten signature analysis
  • Data Science Initiative (DSI) Fellow (Fall 2018) - Advised two undergraduate teams working with Principal Financial.
Aug 2016

Teaching Assistant

Department of Statistics & Data Science, Carnegie Mellon University

In-class tutorials, office hours and grading for the following classes:

  • 36-303 Sampling, Survey and Society (Head TA)
  • 36-315 Statistical Graphics and Visualization (Head TA)
  • 36-401 Modern Regression
  • 36-402 Undergraduate Advanced Data Analysis
  • 36-492 Financial Data Science I
  • 36-493 Financial Data Science II
  • 36-708 Statistical Methods in Machine Learning (PhD Level Class)
  • 36-750 Statistical Computing (PhD Level Class)
Jul 2012 – Jul 2016

Lecturer

Campus FMS

Taught a multitude of classes during summer and winter courses for high school students, located in the Turin area (Italy). Courses and tutorials included:

  • Mathematical analysis in one, two and higher dimensions
  • Game theory
  • Probability theory and Statistics
  • Dynamical systems
  • Mathematical Logic

Honors and
Awards

Contact Me

  • ndalmass AT stat DOT cmu DOT edu
  • 5000 Forbes Avenue, Pittsburgh, PA, 15213