Tim Menzies
Research

$19M in grants from NASA, NSF, NSA, LexisNexis, Microsoft, Meta, National Archives, etc:

Cumulative grants in 2026 dollars (3% inflation) → $19.9M total

Approximate funder breakdown

300+ papers, 25,000+ citations (h-index=75):

Top venues, full career
Other ~81

Most-Cited Papers

Top by citation count via Google Scholar.

• TSE'07 Data Mining Static Code Attributes to Learn Defect Predictors [pdf] · 1,969 cites
• PROMISE'12 The PROMISE Repository of Empirical SE Data [pdf] · 1,471 cites
• EMSE'09 Cross-Company vs. Within-Company Data for Defect Prediction [pdf] · 897 cites
• ASEJ'10 Defect Prediction from Static Code Features [pdf] · 619 cites
• ICSM'08 Automated Severity Assessment of Software Defect Reports [pdf] · 432 cites
• FSE'21 Bias in Machine Learning Software: Why? How? What to do? [pdf] · 369 cites
• IST'18 What is Wrong with Topic Modeling? [pdf] · 351 cites
• TSE'07 Problems with Precision (response paper) [pdf] · 344 cites
• TSE'11 On the Value of Ensemble Effort Estimation [pdf] · 340 cites
• TSE'06 Selecting Best Practices for Effort Estimation [pdf] · 335 cites

AI, for Less

Simpler, optimized models yield exceptional results while remaining transparent and trustworthy.

• SSBSE'26 Zoom, Don't Wander: Regional Search vs. Pareto vs. Global Optimization [pdf]
• FSE'26 Data-Light SE Challenge [pdf]
• VERIFAI'26 Exploiting Software Sparsity [pdf]
• TOSEM'26 LLMs Warming-Up Active Learning [pdf]
• CACM'25 The Case for Compact AI [pdf]
• TOSEM'24 Learning from Very Little Data
• EMSE'24 Co-Training for Defect Prediction
• IEEE Access'24 Partial Ordering for Model Reasoning
• EMSE'22 Minimizing Tech Debt Labeling Cost

LLMs

Where LLMs and deep learning help — and where they hurt.

• EMSE'26 Improving LLM Annotations [pdf]
• MSR'26 Domain Knowledge for LLM Optimization [pdf]
• IEEE IC'23 Variances in Robust DL
• TSE'22 Oversampling for DL Defect Prediction
• MSR'22 Improving DL for SE Analytics
• MSR'22 GANs for Security Class Imbalance

Security

Vulnerability detection and cyberthreat intelligence via active learning and adversarial ML.

• KAIS'25 Mining CTI Attack Patterns [pdf]
• ICDM'24 Temporal Cyberattack Patterns
• EMSE'22 Ensembles Against Evasion Attacks
• EMSE'21 Security Bug Report Classification

Analytics

Better predictors for software quality, project health, and technical debt.

• IST'26 Data-Centric Fuzzing for JS Engines [pdf]
• MSR'26 Multi-Objective Optimization Repo [pdf]
• TSE'25 Is HPO Different for SE? [pdf]
• TSE'25 Static Code Mining Retrospective [pdf]
• SIGSOFT SEN'25 Replications & Negative Results
• ESA'23 Expert System for Cloud SE
• EMSE'22 Process vs. Product Metrics
• EMSE'22 Predicting OSS Project Health
• MSR'22 Stabilizing Models Across Projects
• ICSE'21 Early Life Cycle Defect Prediction

Trust

Verify, audit, and correct AI outputs — ensuring decisions can be inspected, reproduced, and challenged.

• JSS'26 Explaining Optimization Heuristics [pdf]
• IEEE SW'25 AI in State Courts [pdf]
• EMSE'25 Causal Graphs in SE [pdf]
• EMSE'23 Interpreting Model-Based Opt.
• TSE'24 Equalized Odds via Pre-Processing
• IEEE Access'24 Scalability, Privacy, & Performance

Other

• ICSE'26 SE Journals in 2036 [pdf]
• TSE'24 Scoping SE for AI
• IST'24 Contributions of Guenther Ruhe
• CACM'23 (Re)Use of Research Results
• IEEE Computer'22 AI and SE: Are We Ready?