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ShamikOfficial/README.md

Shamik Basu

Applied Data Science · Los Angeles, CA

Building intelligent systems at the intersection of machine learning, high-performance computing, and real-world impact

Portfolio LinkedIn GitHub Email Resume

About Me

MS Applied Data Science student at USC with 3+ years building production ML, LLM, and analytics systems. I take problems from raw data to deployable models — RAG pipelines, agentic AI platforms, GPU-accelerated workloads, and decision analytics.

Currently seeking Fall 2026 co-op and New Grad 2026 roles in Data Science, ML Engineering, and Applied AI.

Featured Projects

Project What it does Stack
Agentic Trend Orchestrator Agentic AI workspace for creators — trend discovery, team workflows, chat FastAPI, Next.js, TypeScript
EcoMate-AI Multimodal carbon footprint analyzer from receipts and daily activities Python, FastAPI, Streamlit, GenAI
CUDA Python Library GPU-accelerated matrix ops and image convolution benchmarks CUDA, C++, Python
Quant Trading Backtester End-to-end algo trading pipeline with XGBoost and backtesting Python, XGBoost, pandas
BizScout Location Intelligence Geo-intelligent restaurant site selection with heat maps Python, Streamlit, geospatial
Green Food Purchasing Analytics County-level sustainable food spending analysis (USDA data) Python, Jupyter, NoSQL

Highlights

Agentic Trend Orchestrator — Full-stack agentic platform with auth, workflow boards, team assistant, and real-time chat. Live demo

EcoMate-AI — Won recognition at sustainability hackathons. OCR + emission factors + GPT-powered recommendations. Portfolio case study

CUDA-Accelerated Python Library — Custom CUDA kernels benchmarked against CPU baselines with reproducible artifacts and project report.

Technical Skills

Languages Python SQL C++ TypeScript Bash

ML & AI PyTorch scikit-learn XGBoost Hugging Face LangChain RAG LLMs

Data pandas NumPy Spark Plotly Matplotlib Tableau

Engineering FastAPI Streamlit Docker CUDA AWS GCP Git

Currently

  • Applying for Data Science & ML roles — Fall 2026 co-op / New Grad 2026
  • Deepening LLMs, RAG pipelines, and agentic AI systems
  • Building projects that connect real datasets to deployable models

Open to opportunities · Portfolio · LinkedIn

Pinned Loading

  1. EcoMate-AI EcoMate-AI Public

    Multimodal AI carbon footprint decoder: transforms receipts and daily activities into environmental impact reports.

    Python 1 1

  2. CUDA-Accelerated-Python-Library CUDA-Accelerated-Python-Library Public

    GPU-accelerated matrix multiplication and image convolution benchmarks: CPU vs CUDA with reproducible artifacts.

    Jupyter Notebook

  3. bizscout-location-intelligence bizscout-location-intelligence Public

    Geo-intelligent restaurant location recommendation system with interactive heat maps and risk-capital strategies.

    Jupyter Notebook

  4. quant-trading-backtester quant-trading-backtester Public

    End-to-end algorithmic trading pipeline: data collection, XGBoost signals, backtesting, and performance analytics.

    Python