Data Scientist | AI Researcher | Responsible AI & AI Security Practitioner
Sai works at the intersection of applied AI, responsible AI, computer vision, LLM safety, and research-driven open-source tooling. His work focuses on building trustworthy AI systems that can be evaluated, audited, and deployed with greater confidence.
- Responsible AI and trustworthy machine learning
- AI security, LLM safety, and agentic AI risk assessment
- ML, LLM, and agentic system auditing, evaluation, and red-teaming
- Bias detection, fairness assessment, and explainability
- Computer vision dataset quality, robustness, and model reliability
- Scientific AI for astronomy, healthcare, and other high-impact domains
- Research-backed open-source tools for AI evaluation, monitoring, and governance
| Project | Description |
|---|---|
rai-audit |
Python package suite for evidence-grade audits of responsible, secure, and trustworthy AI systems |
promptsanitizer |
Security-focused Python toolkit for detecting and mitigating secrets, PII, prompt injection, and RCE risks in AI pipelines |
agentdog |
Pytest-style evaluation toolkit for testing and assessing AI agent behavior |
cv-quality |
Computer vision dataset quality toolkit for identifying annotation, image, and dataset issues |
Enhancing-Ground-Based-Astronomy-using-GenAI |
Generative AI approach for improving ground-based astronomy image quality |
Sai publishes and reviews technical work across AI, responsible AI, computer vision, medical imaging, astronomy, and applied machine learning. His work focuses on connecting research, engineering, and practical AI governance.
- DZone: https://dzone.com/users/5431914/erukude.html
- Google Scholar: https://scholar.google.com/citations?user=j9Iggx8AAAAJ&hl=en&oi=ao
- LinkedIn: https://www.linkedin.com/in/sai-teja-erukude
Sai is interested in open-source collaboration, research-driven engineering, and applied AI systems that create measurable real-world impact.
The goal is to make AI systems easier to evaluate, audit, secure, and report across practical engineering workflows.