About me
I am in my fifth year of my PhD at the MIT Operations Research Center, where I am very fortunate to be advised by Prof. David Gamarnik.
I will be joining NYU's Center for Data Science (CDS) as a CDSMooreSloan Fellow in September 2019!
My primary research interests are in probability theory, high dimensional statistics and theory of machine learning.
From June 2017 to August 2017 I was an intern at the Microsoft Research Lab in New England, mentored by Jennifer Chayes and Christian Borgs . Prior joining MIT, I completed a Master of Advanced Studies in Mathematics (Part III of the Mathematical Tripos) at the University of Cambridge and a BA in Mathematics from the Mathematics Department at the University of Athens.
News
Research Papers
Manuscripts
Publications

Sparse HighDimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm
Annals of Statistics (Major Revisions)
with David Gamarnik

The AllorNothing Phenomenon in Sparse Linear Regression (Slides, Poster)
Proceedings of the Conference on Learning Theory (COLT), 2019
with Galen Reeves, Jiaming Xu

Improved bounds on Gaussian MAC and sparse regression via Gaussian inequalities
Proceedings of the International Symposium on Information Theory (ISIT), 2019
with Christos Thrampoulidis, Yury Polyanskiy

A simple bound on the BER of the MAP decoder for massive MIMO systems
Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
with Christos Thrampoulidis, Yury Polyanskiy

HighDimensional Linear Regression Using Lattice Basis Reduction (Slides, Poster, Video)
Advances in Neural Information Processing Systems, (NeurIPS), 2018
with David Gamarnik

Revealing Network Structure, Confidentially: Improved Rates for NodePrivate Graphon Estimation (Slides, Simons Talk by Adam)
Symposium of Foundations of Computer Science (FOCS), 2018
with Christian Borgs, Jennifer Chayes, Adam Smith

Orthogonal Machine Learning: Power and Limitations (Slides, Poster, Code)
Proceedings of International Conference of Machine Learning (ICML), 2018 (20 minute Presentation)
with Lester Mackey, Vasilis Syrgkanis

HighDimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transition (Slides, Poster, Talk)
Proceedings of the Conference on Learning Theory (COLT), 2017 (20 minutes Presentation)
with David Gamarnik

Mixed integer convex representability (Slides)
Submitted.
Conference version in Proceedings of the International Conference of Integer Programming and Combinatorial Optimization (IPCO), 2017
with Miles Lubin, Juan Pablo Vielma

Universal Padé approximants and their behaviour on the boundary
Monatshefte für Mathematik, Vol. 182, pp 173–193, 2017

Pade approximants, density of rational functions in A^(infinity)(V) and smoothness of the integration operator
Journal of Mathematical Analysis and Applications; Vol. 423, p.p. 1514–1539, 2015
with Vassili Nestoridis
Thesis/Notes/Survey Articles

Computational and Statistical Challenges in High Dimensional Statistical Models
PhD Thesis, Operations Research Center, Massachussets Institute of Technology, 2019

Private Algorithms Can Always Be Extended
Note on the extension of private algorithms
with Christian Borgs, Jennifer Chayes, Adam Smith

Noise Sensitivity with applications to Percolation and Social Choice Theory
Part III Essay, 2014
advised by Bela Bollobas
Awards

Honorable Mention for MIT Operations Research Center Best Student Paper Award, 2017
Paper: HighDimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transition

Senior Scholarship from Trinity College, Cambridge University, 2014

The Onassis Foundation Scholarship for Master Studies, 20132014

The Cambridge Home and European Scholarship Scheme (CHESS) award, 20132014.

International Mathematics Competition for University Students (IMC): First Prize, 2011, Second Prize, 2010

South Eastern European Mathematics Olympiad for University Students (SEEMOUS): Gold Medal, 2011, Silver Medal, 2010