Michael Kuchnik
Scholar

Michael Kuchnik

Google Scholar ID: 0vbCjDEAAAAJ
Meta
computer systemsmachine learning
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
517
 
H-index
11
 
i10-index
11
 
Publications
20
 
Co-authors
3
list available
Contact
CVOpen ↗GitHubOpen ↗
Publications
7 items
AIRA_2: Overcoming Bottlenecks in AI Research Agents
2026
Cited
0
KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta
2025
Cited
0
PRISM: Probabilistic Runtime Insights and Scalable Performance Modeling for Large-Scale Distributed Training
2025
Cited
0
Quagmires in SFT-RL Post-Training: When High SFT Scores Mislead and What to Use Instead
2025
Cited
0
Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls
2025
Cited
0
AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench
2025
Cited
0
Revisiting Reliability in Large-Scale Machine Learning Research Clusters
arXiv.org · 2024
Cited
0
Resume (English only)
Co-authors
3 total
Co-author 1
Co-author 1
Virginia Smith
Virginia Smith
Carnegie Mellon University
Nathan DeBardeleben
Nathan DeBardeleben
Research Scientist, Los Alamos National Laboratory