Data Science Master's student from the University of Chicago, with a strong foundation in Machine Learning and Applied Generative AI
- Languages & ML Frameworks: Python (NumPy, Pandas, Scikit-Learn, PyTorch, TensorFlow, Keras), SQL, PySpark, R
- GenAI & AI Tooling: LangChain, LangGraph, Agentic AI (A2A), Vector Databases (FAISS, Pinecone, ChromaDB), RAG Pipelines, Prompt Engineering, Whisper STT, TTS Models (Bark), Multi-Model Orchestration (MCP)
- Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, Excel
- Big Data & Cloud: Google Cloud Platform (GCP), AWS, Spark, Hadoop, Hive, Docker, MapReduce
- Key Skills: Supervised & Unsupervised ML, Predictive Modeling, Deep Learning, Feature Engineering, MLOps, LLM Applications & Agents
- Machine Learning
- Big Data and Cloud Computing
- Generative AI
- Data Structures and Algorithms
- Python for Data Science
- Statistics
- Probability
- Algorithmic Marketing
- Discrete Mathematics
- Linear Algebra
- Calculus
- Differential Equations
- Algebra
Currently working on:
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GenAI Audio-to-Audio E-commerce Chatbot: Voice-based product assistant using Whisper STT, ChromaDB vector search, and OpenAI TTS for context-aware recommendations.
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Multi-Agent Customer Service System leveraging A2A messaging and MCP for dynamic tool orchestration