Scholar
Vijayaraghavan Murali
Google Scholar ID: wlp0v4kAAAAJ
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Citations & Impact
Citations
1,179
H-index
16
i10-index
17
Publications
20
Co-authors
26
list available
Publications
Resume (English only)
Academic Achievements
- Agentic Program Repair from Test Failures at Scale: A Neuro-symbolic approach with static analysis and test execution feedback, arxiv (2025)
- AI-Assisted Fixes to Code Review Comments at Scale, arxiv (2025)
- Moving Faster and Reducing Risk: Using LLMs in Release Deployment, ICSE 2025 (SEIP) - Distinguished Paper Award
- AI-Assisted SQL Authoring at Industry Scale, ICSE 2025 (SEIP)
- Multi-line AI-assisted Code Authoring, FSE 2024 (Industry Track)
- AI-assisted Code Authoring at Scale: Fine-tuning, deploying, and mixed methods evaluation, FSE 2024 - Highlight by Meta CEO Mark Zuckerberg
- Learning to Learn to Predict Performance Regressions in Production at Meta, AST 2023
- Detecting Privacy-Sensitive Code Changes with Language Modeling, MSR 2022 (Industry Track)
- Counterfactual Explanations for Models of Code, ICSE 2022 (SEIP)
- Improving Code Autocompletion with Transfer Learning, ICSE 2022 (SEIP)
- Explaining mispredictions of machine learning models using rule induction, FSE 2021
- Industry-scale IR-based Bug Localization: A Perspective from Facebook, ICSE 2021 (SEIP) - Distinguished Paper award
- Scalable Statistical Root Cause Analysis on App Telemetry, ICSE 2021 (SEIP)
- Scaffle: bug localization on millions of files, ISSTA 2020
- Debugging crashes using continuous contrast set mining, ICSE 2020 (SEIP)
- Neural query expansion for code search
Research Experience
- Works as a researcher at Meta, involved in multiple projects that have had significant industrial impact at Meta.
Background
- An applied ML and software engineering researcher at Meta, working on developing AI-based solutions to industry-scale software engineering problems. Research focuses on code generation/synthesis, code review, bug attribution, root cause analysis, etc.
