I am an Assistant Professor in the Department of Statistics at the University of Illinois Urbana-Champaign. I am also affiliated with the Department of Electrical and Computer Engineering.
Previously, I was a Distinguished Postdoctoral Fellow at Columbia University, Department of Statistics. I received my PhD in Electrical Engineering and Computer Science from MIT under the wonderful guidance of David Gamarnik. At MIT, I was affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS).
You can find my CV here.
Planted Random Number Partitioning Problem
Eren C. Kızıldağ
Under review, 2024+
[Paper]
Sharp Phase Transition for Multi Overlap Gap Property in Ising p-Spin Glass and Random k-SAT Models
Eren C. Kızıldağ
Under review, 2024+
[Paper]
Shattering in the Ising Pure p-Spin Model
David Gamarnik, Aukosh Jagannath, Eren C. Kızıldağ
Under review, 2024+
[Paper]
Algorithmic Obstructions in the Random Number Partitioning Problem
David Gamarnik, Eren C. Kızıldağ
Annals of Applied Probability, 2023
[Paper] [Slides] [Talk] [Poster]
Conference version in ISIT 2022
Stationary Points of Shallow Neural Networks with Quadratic Activation Function
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
Mathematics of Operations Research, 2024
[Paper] [Slides] [Talk]
Symmetric Binary Perceptron with Random Labels: Capacity, Universality, and Overlap Gap Property
Eren C. Kızıldağ, Tanay Wakhare
Preprint, 2023
Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
IEEE Transactions on Signal Processing, 2022
[Paper] [Slides]
Conference version in ISIT 2021
Computing the Partition Function of the Sherrington-Kirkpatrick Model is Hard on Average
David Gamarnik, Eren C. Kızıldağ
Annals of Applied Probability, 2021
[Paper] [Slides]
Conference version in ISIT 2020
Inference in High-Dimensional Linear Regression via Lattice Basis Reduction and Integer Relation Detection
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
IEEE Transactions on Information Theory, 2021
[Paper]
Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena
Matt Emschwiller, David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
Preprint, 2020
[Paper]
A Random CSP with Connections to Discrepancy Theory and Randomized
Trials
Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2024
[Extended Paper] [Slides]
Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization
David Gamarnik, Eren C. Kızıldağ, Will Perkins, Changji Xu
Conference on Learning Theory (COLT), 2023
[Paper]
Symmetric Perceptron with Random Labels
Eren C. Kızıldağ, Tanay Wakhare
International Conference on Sampling Theory and Applications (SampTA), 2023
[Paper] [Slides]
Algorithms and Barriers in the Symmetric Binary Perceptron Model
David Gamarnik, Eren C. Kızıldağ, Will Perkins, Changji Xu
IEEE Symposium on Foundations of Computer Science (FOCS), 2022
[Paper] [Slides] [Poster]
The Random Number Partitioning Problem: Overlap Gap Property and Algorithmic Barriers
David Gamarnik, Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2022
[Paper]
Self-Regularity of Output Weights for Overparameterized Two-Layer Neural Networks
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
IEEE International Symposium on Information Theory (ISIT), 2021
[Paper] [Slides]
Computing the Partition Function of the Sherrington-Kirkpatrick Model is Hard on Average
David Gamarnik, Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2020
[Paper] [Slides]
High-Dimensional Linear Regression and Phase Retrieval via PSLQ Integer
Relation Algorithm
David Gamarnik, Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2019
[Paper] [Slides]
Algorithms and Algorithmic Barriers in
High-Dimensional Statistics and Random
Combinatorial Structures
Ph.D thesis, Massachusetts Institute of Technology, 2022
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