Alexandru Meterez

Alex Meterez

Hey, I'm Alex, and I am a CS PhD student at Harvard co-advised by Prof. Sham Kakade and Prof. Cengiz Pehlevan. I am fortunate to be supported by a Kempner Fellowship in my research. My main interests are in Deep Learning theory and neural network optimization.

Publications and preprints (*: equal co-first, †: equal co-last)

ICLR 2026 Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling
A. Meterez*, D. Morwani*, J. Wu, C. Oncescu, C. Pehlevan, S. Kakade
(NeurIPS Workshop) OPT 2025 A Simplified Analysis of SGD for Linear Regression with Weight Averaging
A. Meterez*, D. Morwani*, C. Oncescu, J. Wu, C. Pehlevan, S. Kakade
COLM 2025 Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining
R. Zhao*, A. Meterez*, S. Kakade, C. Pehlevan, S. Jelassi†, E. Malach†
ICLR 2025 The Optimization Landscape of SGD Across the Feature Learning Strength
A. Atanasov*, A. Meterez*, J. Simon*, C. Pehlevan
NeurIPS 2024 Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning
L. Noci*, A. Meterez*, T. Hofmann, A. Orvieto
ICLR 2024 Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
A. Meterez*, A. Joudaki*, F. Orabona, A. Immer, G. Rätsch, H. Daneshmand
RECOMB 2023 Aligning distant sequences to graphs using long seed sketches
A. Joudaki*, A. Meterez*, H. Mustafa, R. Groot Koerkamp, A. Kahles, G. Rätsch