Dan Mikulincer
Scholar

Dan Mikulincer

Google Scholar ID: Y-hkBNcAAAAJ
Weizmann Institute
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
427
 
H-index
12
 
i10-index
15
 
Publications
20
 
Co-authors
0
 
Contact
CVOpen ↗
Publications
3 items
The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently
2026
Cited
0
Fast mixing in Ising models with a negative spectral outlier via Gaussian approximation
2025
Cited
0
Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions
2025
Cited
0
Resume
Academic Achievements
  • Published numerous papers across top conferences and journals such as COLT, NeurIPS, and others, covering topics like stochastic analysis, Ising models, and random walks.
Research Experience
  • Currently the Brian and Tiffinie Pang Assistant Professor at the University of Washington; previously an Instructor (postdoc) at MIT Mathematics; spent summer 2019 at Microsoft Research AI, hosted by Sébastien Bubeck.
Education
  • Ph.D. from Weizmann Institute under the supervision of Ronen Eldan; B.Sc. in Mathematics and Computer Science from Ben-Gurion University, with additional studies in Cognitive Neuroscience.
Background
  • Broadly interested in the intersection of high-dimensional geometry, probability, statistics, information theory, and their applications to data science and learning theory. Particularly focused on normal approximations and dimension-free phenomena.