Srini Iyer
Scholar

Srini Iyer

Google Scholar ID: jNjde2wAAAAJ
FAIR
Language ModelingNL to CodeQAExplainabilitySummarization
Citations & Impact
All-time
Citations
7,193
 
H-index
30
 
i10-index
48
 
Publications
20
 
Co-authors
0
 
Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • Published multiple papers in the fields of natural language processing, code generation, and semantic parsing. Notable works include 'Learning to Map Natural Language to General Purpose Source Code' and 'JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation.' Received the Outstanding Paper award at NAACL 2018.
Research Experience
  • Worked briefly at Facebook in the Ads Ranking and Optimization team before joining Facebook AI Research. Conducted PhD research at the NLP group at the University of Washington.
Education
  • PhD in Computer Science from the University of Washington, advised by Luke Zettlemoyer and Alvin Cheung; Master's degree in Computer Science from Stanford University, with a focus on BioInformatics and Theoretical CS.
Background
  • Interested in a broad range of areas within NLP, including language modeling, explainability, summarization, generation, and question answering. Currently a Research Scientist at Facebook AI Research.
Miscellany
  • Enjoys summiting peaks, traveling to national parks, and photography.
Co-authors
0 total
Co-authors: 0 (list not available)