Scholar
Gintare Karolina Dziugaite
Google Scholar ID: 5K1QB_8AAAAJ
Google DeepMind
Deep Learning
Statistical Learning theory
Generalization Theory
Neural Network Sparsity
Data Sparsity
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
6,232
H-index
27
i10-index
38
Publications
20
Co-authors
20
list available
Contact
Email
gkdz@google.com
CV
Open ↗
GitHub
Open ↗
LinkedIn
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Publications
4 items
Detoxifying LLMs via Representation Erasure-Based Preference Optimization
2026
Cited
0
Less is More: Undertraining Experts Improves Model Upcycling
2025
Cited
0
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
2025
Cited
0
Torque-Aware Momentum
2024
Cited
0
Resume (English only)
Research Experience
Senior Research Scientist, Google Brain
Led Trustworthy AI program at Element AI / ServiceNow
Member, Institute for Advanced Study (Princeton), 2020 – Special Year on Optimization, Statistics, and Theoretical Machine Learning
Long-term participant, Simons Institute (UC Berkeley), Winter 2017 – Foundations of Machine Learning program
Simons Fellow, Summer 2019 – Foundations of Deep Learning program
Returning to Simons Institute in 2022 for Learning and Games program
Background
Senior Research Scientist at Google Brain, based in Toronto
Adjunct Professor at McGill University School of Computer Science
Associate Industry Member of Mila – Quebec AI Institute
Research combines theoretical and empirical approaches to deep learning, focusing on generalization and network compression
Previously led the Trustworthy AI program at Element AI / ServiceNow
Co-authors
20 total
Daniel M. Roy
Research Director, Vector Institute; Prof., U. Toronto (Statistics, CS)
Jonathan Frankle
Databricks
Michael Carbin
Massachusetts Institute of Technology
Co-author 4
Surya Ganguli
Associate Professor, Stanford University
Zoubin Ghahramani
Professor, University of Cambridge, and VP of Research, Google DeepMind
Jeffrey Negrea
University of Waterloo
Ashish Khisti
Professor, University of Toronto
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