About
I am a third-year Computer Science student at PES University, currently an AIML Intern at AVEVA. I like problems where performance, correctness, and practical ML constraints meet.
Core Direction
Production LLM agents, systems programming, distributed infrastructure, ML systems, and applied research.
Research Interest
Epistemic uncertainty in RAG, RL post-training for ASR fairness, multi-modal learning, agentic memory, and video anomaly detection.
How I Work
I prefer measurable claims: benchmarks, accuracy, latency, failure modes, and maintainable implementations.
Experience
AIML Intern, AVEVA (Schneider Electric)
Building a production conversational AI agent that turns natural language into validated industrial KPI calculations, replacing form-based authoring workflows.
Designed a stateless multi-tool agent architecture with strict validation boundaries, diagnosed and fixed production bugs in schema handling, and presented the system in an internal knowledge-sharing session.
Research Intern, C-ISFCR
Designed and evaluated four multi-modal architectures for unsupervised video anomaly detection, reaching 75.48% classification accuracy on 16.5 hours of NWPU Campus Dataset footage.
Built a keyword-free composite anomaly scoring framework using semantic, visual, object distribution, and temporal signals, with F1 scores of 0.845-0.895 across test categories.
Teaching Assistant, PES CSE
TA for Big Data under Dr. Prafullata Kiran Auradkar.
TA for Microprocessors and Computer Architecture under Prof. Chitra GM. Prepared course material and the course project evaluation schema for 700+ students.
Skills
Distributed Systems
Rust, C/C++, Go, Python, Kafka, Redis, Linux, Bash
ML Systems
PyTorch, CUDA, LangGraph, Azure OpenAI, MCP, LanceDB, OpenCV, Whisper, Flower
Infrastructure
Docker, Kubernetes, GitHub Actions, FastAPI, Spark, Git