Ahmed El Alaoui

About

Ahmed El Alaoui is an assistant professor of statistics and data science at Cornell University. His research interests revolve around high-dimensional phenomena in statistics and probability theory, statistical physics, algorithms, and problems where these areas meet. Prior to joining the Cornell faculty in 2021, he was a postdoctoral researcher at Stanford University, hosted by Andrea Montanari. He received his Ph.D. in electrical engineering and computer sciences from UC Berkeley in 2018, advised by Michael I. Jordan.

Research topics

• Physics
• Combinatorics
• Nuclear physics
• Atomic physics
• Mathematics
• Particle physics
• Quantum mechanics
• Geometry
• Mathematical physics

Selected publications

• Optimization of mean-field spin glasses

  arXiv (Cornell University) · 2021 · 27 citations

  1st authorCorresponding

  Mean-field spin glasses are families of random energy functions (Hamiltonians) on high-dimensional product spaces. In this paper, we consider the case of Ising mixed p-spin models,; namely, Hamiltonians HN:ΣN→R on the Hamming hypercube ΣN={±1}N, which are defined by the property that {HN(σ)}σ∈ΣN is a centered Gaussian process with covariance E{HN(σ1)HN(σ2)} depending only on the scalar product ⟨σ1,σ2⟩. The asymptotic value of the optimum maxσ∈ΣNHN(σ) was characterized in terms of a variational p…

• The Kikuchi Hierarchy and Tensor PCA

  Journal of the ACM · 2025-08-27 · 6 citations

  preprintOpen access

  For the tensor principal component analysis (tensor PCA) problem, we propose a new hierarchy of increasingly powerful algorithms with increasing runtime. Our hierarchy is analogous to the sum-of-squares (SOS) hierarchy but is instead inspired by statistical physics and related algorithms such as belief propagation and AMP (approximate message passing). Our level-ℓ algorithm can be thought of as a linearized message-passing algorithm that keeps track of ℓ-wise dependencies among the hidden variab…

  PublisherOA PDFDOI

• Shattering in Pure Spherical Spin Glasses

  Communications in Mathematical Physics · 2025-04-12 · 5 citations

  article1st authorCorresponding
  PublisherDOI

• Hardness of Sampling Solutions From the Symmetric Binary Perceptron

  Random Structures and Algorithms · 2025-07-01 · 2 citations

  articleOpen access1st authorCorresponding

  ABSTRACT We show that two related classes of algorithms, stable algorithms and Boolean circuits with bounded depth, cannot produce an approximate sample from the uniform measure over the set of solutions to the symmetric binary perceptron model at any constraint‐to‐variable density. This result is in contrast to the question of finding a solution to the same problem, where efficient (and stable) algorithms are known to succeed at sufficiently low density. This result suggests that the solutions…

  PublisherOA PDFDOI

• Sampling from mean-field Gibbs measures via diffusion processes

  Probability and Mathematical Physics · 2025-07-21 · 1 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• E. Voutier

  Université Paris-Saclay

  343 shared

• F. Sabatié

  CEA Paris-Saclay

  306 shared

• S. Niccolai

  Université Paris-Saclay

  263 shared

• C. Muñoz Camacho

  Université Paris-Saclay

  238 shared

• R. Dupré

  Laboratoire de Physique des 2 Infinis Irène Joliot-Curie

  231 shared

• M. Guidal

  Université Paris-Saclay

  230 shared

• A. D’Angelo

  223 shared

• H. Hakobyan

  University of California, Riverside

  189 shared

Labs

• Graduate Student GroupsPI

Education

• Ph.D., electrical engineering and computer sciences

  UC Berkeley

  2018

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