I study how language models fail, then build systems that can detect, explain, and act on uncertainty.
LLM reliability research · cyber-intelligence platforms · autonomous systems
Hyderabad, India
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arXiv preprints LLM reliability |
National winner TattvaDrishti |
Application published Rakshak · 202541112724 A |
LeetCode top 2.53% 2,006 contest rating |
- Researching hidden-state and black-box hallucination detection as a Research Intern at LLM Lens.
- Building misinformation and cyber-intelligence systems with the AICTE Cyber Security Cell.
- Mentoring and evaluating student engineering work as a Web & ML Domain Expert at Recurse, KMIT.
- Studying Computer Science (AI & ML) at KMIT and Data Science at IIT Madras.
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Probing transformer hidden states and black-box behavior for signals that distinguish reliable answers from hallucinations.
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An analyst-facing cyber-intelligence platform for detecting AI-generated misinformation, mapping narratives, and preserving auditable decisions.
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A hybrid edge–cloud surveillance rover combining LiDAR, vision, GPS, autonomous navigation, and human takeover for perimeter monitoring. Project site ↗ · Interface repo ↗
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A privacy-first, local AI workspace with persistent memory, grounded document Q&A, streaming chat, and local model execution.
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Explore the complete project archive →
| Work | Focus | Evidence |
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| Weakly Supervised Distillation of Hallucination Signals into Transformer Representations | Five probe architectures trained directly on LLaMA-2-7B hidden states | arXiv:2604.06277 |
| BEACON: Behavioral Entropy Aggregation for Cross-Model Hallucination Detection | Black-box detection using entropy, embedding geometry, CoT consistency, and paraphrase stability | arXiv:2606.07528 |
Weekly coding activity
| Research & ML | PyTorch · Transformers · representation probing · evaluation · calibration · RAG |
| Systems | FastAPI · Next.js · WebSockets/SSE · PostgreSQL · MongoDB · Qdrant · Docker |
| Edge & robotics | Jetson Nano · Pixhawk · LiDAR · depth sensing · GPS · OpenCV · ROS concepts |
Open to research collaborations, deep-tech internships, and difficult systems worth building.
Email · LinkedIn · Portfolio · Repositories

