💡 Exploring:
- Fair Entity Matching
- Knowledge Graphs
- Vector Search & Retrieval
- Data-Centric AI
- Scalable Backend Systems
- Adaptive Fair Entity Matching
- Retrieval-Augmented Systems
- Knowledge Graph Reasoning
- Fairness-aware ML Systems
Fairness-aware entity matching with adaptive calibration and skew-aware evaluation.
Dependency-aware and multimodal knowledge graph system for intelligent reasoning.
Semantic retrieval and vector routing using FAISS and embedding pipelines.
Image-to-structured-question template extraction system.
Languages Java • Python • SQL • JavaScript
Systems & Backend Kafka • ElasticSearch • Microservices • REST APIs • AWS
ML & Data Entity Matching • Knowledge Graphs • Vector DBs • Retrieval Systems
- Built scalable billing systems handling production-scale workflows
- Worked on distributed microservices and event-driven architectures
- Designed AI-driven ingestion and document processing pipelines
- Improved search and retrieval systems using ElasticSearch & vector search
- Build impactful AI + Data Systems research
- Open-source scalable intelligent systems
- Pursue graduate research in Data-Centric AI
📌 GitHub: https://github.com/keshav12280-blip
⭐ Interested in scalable data systems, fairness-aware ML, and intelligent retrieval systems.