π B.Tech graduate in Data Science & Artificial Intelligence
π Indian Institute of Information Technology, Dharwad
Iβm a Data Scientist and Generative AI Engineer with hands-on experience building production-scale AI systems. Over the past year, my focus has expanded from traditional ML and computer vision to LLMs, Retrieval-Augmented Generation (RAG), agentic AI workflows, and hybrid search systems.
I enjoy solving real-world problems by combining data, AI, and thoughtful system design, while keeping reliability, evaluation, and user experience at the center.
- Built end-to-end RAG pipelines over 100K+ documents
- Worked with LangChain, LangGraph, LangSmith, and Hugging Face
- Designed agentic AI workflows for enterprise and maritime intelligence
- Implemented hybrid retrieval (vector + keyword search)
- Reduced hallucinations using source-grounded generation & confidence checks
- Tuned chunking, reranking, and fallback retrieval paths for robustness
- Built an LLM Behavioral Evaluation Suite
- Evaluated models for:
- Hallucination
- Prompt injection & jailbreak resistance
- Context poisoning
- Reasoning consistency
- Designed baseline vs optimized prompts and ran controlled A/B evaluations
- Created an interactive dashboard to visualize LLM behavior differences
- Health misinformation detection using SciBERT
- Election misinformation analysis with graph-based clustering
- Voice-based multilingual NLP system for agricultural queries
- Semantic search over noisy real-world datasets
- ποΈ Virtual Mouse using Hand Gestures (OpenCV + MediaPipe)
- β½ Football Player Detection & Re-Identification (YOLO + ReID)
- π₯ Disease Prediction System (XGBoost, Random Forest, MLP β 97% precision)
- π Fraud Detection Dashboard with explainability (SHAP)
- π Quantum Communication Simulator (BB84, QKD)
- Python, SQL, NumPy, Pandas, Matplotlib, Plotly
- LLMs, Prompt Engineering, RAG, Agentic AI
- LangChain, LangGraph, LangSmith
- Hugging Face (Transformers, Tokenizers)
- Jina Reranker
- ElasticSearch (BM25, Fuzzy Search)
- FAISS, Vector Databases
- Semantic & Hybrid Search
- Scikit-learn, PyTorch, TensorFlow
- Power BI, Figma, Canva
- Git, Linux, Docker, VS Code
- Reliable & evaluated LLM systems
- RAG failure modes and mitigation
- Hybrid retrieval architectures
- Agentic AI and tool-using models
- Scalable AutoML & MLOps platforms
Iβve been selected twice for the Inter-IIIT Chess Team π
Iβm open to collaborating on LLMs, RAG systems, AI research, and real-world AI products.
π« LinkedIn: https://www.linkedin.com/in/mohammed-arsalan-58543a305
π Portfolio: https://arsalan-804.netlify.app