Nic Dalmasso, PhD
About
AI Research Lead at J.P.Morgan AI Research with a Ph.D. in Statistics from Carnegie Mellon University, where I was fortunate to be advised by professor Ann B. Lee. I develop and implement innovative AI solutions in finance, focusing on statistical machine learning, uncertainty quantification, and algorithmic fairness, which I actively publish at AI conferences. My research interests lie in deep generative models, time series analysis, temporal point processes, stochastic optimization and large language models.
Prior to CMU, I have worked for a couple of years in London as Analyst for Zynga (NaturalMotion) after pursuing an M.Sc. in Statistics at Imperial College London, where I have worked on Bayesian hierarchical models for cosmology under the guidance of Dr. Daniel Mortlock and Dr. Stephen Feeney. Before that, everything started with a B.Sc. in Mathematics and a Diploma in Government and Natural Sciences from University of Turin, Italy.
Interests
- Statistical Machine Learning
- Uncertainty Quantification
- Algorithmic Fairness
- Stochastic Optimization
- Deep Generative Models
Education
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PhD in Statistics, 2021
Carnegie Mellon University
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MSC in Statistics, 2014
Imperial College London
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BSc in Mathematics, 2010
Università degli Studi di Torino
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Diploma in Natural Sciences, 2010
Scuola di Studi Superiori 'Ferdinando Rossi' SSST