Scholar
Zinan Lin
Google Scholar ID: 67nE-wQ_g_cC
Microsoft Research (Redmond), Carnegie Mellon University
machine learning
privacy
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Citations & Impact
All-time
Citations
3,165
H-index
23
i10-index
27
Publications
20
Co-authors
106
list available
Contact
Email
zinanlin@microsoft.com
CV
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GitHub
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Publications
22 items
DP-SAPF: Saliency-Aware Parameter Fine-tuning of Public Models for Differentially Private Image Synthesis
2026
Cited
0
SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations
2026
Cited
0
Differentially Private Contrastive Learning via Bounding Group-level Contribution
2026
Cited
0
NI Sampling: Accelerating Discrete Diffusion Sampling by Token Order Optimization
2026
Cited
0
Emergent Social Intelligence Risks in Generative Multi-Agent Systems
2026
Cited
0
DP-RFT: Learning to Generate Synthetic Text via Differentially Private Reinforcement Fine-Tuning
2026
Cited
0
CineScene: Implicit 3D as Effective Scene Representation for Cinematic Video Generation
2026
Cited
0
From Easy to Hard++: Promoting Differentially Private Image Synthesis Through Spatial-Frequency Curriculum
arXiv.org · 2026
Cited
0
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Resume (English only)
Co-authors
106 total
Giulia Fanti
Carnegie Mellon University, ECE Department
Vyas Sekar
Tan Family Chair in Electrical and Computer Engineering, Carnegie Mellon University
Xuefei Ning
Tsinghua University
Yu Wang (汪玉)
Department of Electronic Engineering, Tsinghua University, China
sewoong oh
Professor, University of Washington
Chulin Xie
Google DeepMind
Bo Li
University of Illinois at Urbana–Champaign
Dawn Song
Professor of Computer Science, UC Berkeley
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