Scholar
Hongzhou Lin
Google Scholar ID: 8Phz8n4AAAAJ
Amazon
Artificial Intelligence
LLM
Optimization
Theory of Deep Learning
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Citations & Impact
All-time
Citations
1,245
H-index
12
i10-index
13
Publications
20
Co-authors
12
list available
Contact
Email
hongzhou.lin89@gmail.com
CV
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Publications
7 items
Awakening the Sleeping Agent: Lean-Specific Agentic Data Reactivates General Tool Use in Goedel Prover
2026
Cited
0
Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction
2025
Cited
0
QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
2025
Cited
0
Ineq-Comp: Benchmarking Human-Intuitive Compositional Reasoning in Automated Theorem Proving on Inequalities
2025
Cited
0
Task Generalization With AutoRegressive Compositional Structure: Can Learning From $d$ Tasks Generalize to $d^{T}$ Tasks?
2025
Cited
0
Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving
2025
Cited
0
From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency
arXiv.org · 2024
Cited
0
Resume (English only)
Background
Applied Scientist at Amazon, part of the AGI Foundation team
Focuses on large language models (LLMs) with specialization in mathematical reasoning and problem-solving, both informal and formal (e.g., LEAN)
Contributed to Amazon's Nova models for advanced multimodal tasks across text, images, and video
Previously worked on supply chain management, price modeling, and LLM applications across domains
Strong foundation in optimization, predictive modeling, and AI for real-world problem solving
Co-authors
12 total
Julien Mairal
Inria - Univ. Grenoble Alpes
Zaid Harchaoui
University of Washington
Stefanie Jegelka
TUM and MIT
Jingzhao Zhang
IIIS, Tsinghua University
Ali Jadbabaie
JR East Professor of Engineering, MIT
Suvrit Sra
TUM
Courtney Paquette
McGill University
Danqi Chen
Princeton University
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