News & Events

Employment

 
 
 
 
 
June 2021 – Present
New York

AI & Machine Learning, Senior Research Associate

J.P.Morgan AI Research

 
 
 
 
 
June 2020 – August 2020
Online

AI & Machine Learning, Summer Associate

J.P.Morgan AI Research

Research and development of deep generative models for high-fidelity synthetic financial data.
 
 
 
 
 
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.

Selected Publications

(2022). Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance.

Preprint

(2022). When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments. In NeurIPS 2021 Algorithmic Fairness through the Lens of Causality and Robustness Workshop.

Preprint

(2021). Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage.

Preprint

(2021). Validating Conditional Density Models and Bayesian Inference Algorithms. Accepted at UAI 2021.

Preprint PDF Code

(2020). PayVAE: A Generative Model for Financial Transactions. In AAAI 2021 Workshop on Knowledge Discovery from Unstructured Data in Financial Services Workshop (Oral).

PDF

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

Preprint PDF Code Video

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

Preprint PDF Code Video

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

Preprint PDF Code DOI

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

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

  • 2021 Statistics & Data Science Student of the Year
  • 2019 Statistics & Data Science TA of the Year
    For the services offered as TA of 36-650\750 (Statistical Computing).
  • 2017 Citadel Data Open Datathon at Carnegie Mellon University
    Competed and won with fellow students Alan Mishler, Kwhangho Kim, and Chirag Nagpal (550+ student applications, around 125 students selected to compete).
  • 2012 Alfaclass Mathematics Team Competition
    First prize across 100 students selected based on GPA across mathematics and engineering department at University of Turin.
  • Full Scholarship - 2011, 2012, 2013
    Scholarship covering tuition fees, annual bursary and living expenses via the Scuola of Studi Superiori ‘Ferdinando Rossi’ and ‘Compagnia di San Paolo’

Contact Me

  • ndalmass AT alumni DOT cmu DOT edu
  • New York City, NY