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Basics

Name Mihir Agarwal
Label Data Science Graduate Student & Software Engineer
Email ma4874@columbia.edu
Phone +1 (646) 235-7363
Summary Software Engineer with experience in Machine Learning and Data Science, currently pursuing a Master's in Data Science at Columbia University. Proven track record at Shell and research labs in building AI-powered automation, predictive maintenance models, and optimizing cloud infrastructure.

Work

  • 2022.08 - 2025.08

    Bengaluru, India

    Software Engineer
    Shell
    Engineered AI/ML solutions for HR automation and test case prioritization.
    • Built an AI-powered HR Chatbot using a Retrieval-Augmented Generation (RAG) pipeline with LangChain and GPT, indexing Shell HR policy documents for quick, context-aware responses.
    • Automated 70% of HR employee inquiries, streamlining internal communications, cutting response times by 50%, and saving $100k annually in operational costs.
    • Implemented document chunking, embedding generation, vector indexing, and semantic retrieval for robust intelligent automation systems.
    • Developed a web application for Test Case Prioritization using clustering and supervised learning, improving test suite accuracy and efficiency.
    • Engineered machine learning models leveraging execution history and step complexity, leading to a 35% reduction in execution time and cost savings of $10k.
  • 2022.01 - 2022.08

    Paris, France (Remote)

    Researcher
    LISITE Lab Isep
    Research focused on ML-based resource management in fog computing.
    • Co-authored and published a Springer journal paper on ML-based resource management in fog computing, proposing latency-reduction strategies.
    • Designed and evaluated scalable deployment models by estimating infrastructure requirements and performance metrics, ensuring optimized allocation of computing resources.
  • 2020.07 - 2022.08

    London, UK (Remote)

    Machine Learning Intern
    Vidrona
    Developed predictive maintenance solutions using computer vision.
    • Developed predictive maintenance solutions for insulator caps and guy adjusters by processing drone-captured images with deep learning models (YOLOv3/5/8, Faster R-CNN).
    • Enhanced model accuracy through advanced image preprocessing techniques, including Histogram Equalization, noise reduction, and contrast adjustment.
    • Optimized detection pipelines by fine-tuning thresholds and anchor boxes, enabling large-scale automation and saving 300+ hours of manual labor weekly.

Volunteer

  • - Present

    Bengaluru, India

    Vice President
    Shell Toastmaster Club
    Leadership role focused on public speaking and event organization.
    • Completed Level 3 and conducted 45+ events to enhance public speaking and leadership skills.

Education

  • 2025.08 - 2026.12

    New York, NY

    Master's
    Columbia University
    Data Science
    • Unsupervised Learning
    • Competitive Coding
    • Applied Deep Learning
    • Probability and Statistics
  • 2018.07 - 2022.07

    India

    Bachelor's
    Vellore Institute of Technology
    Computer Engineering

Awards

  • Best Domain Prize
    IvyHacks
    Won Best Domain prize in IvyHacks: a joint hackathon hosted by 6 Ivy League universities.

Publications

Skills

Programming Languages
Python
C/C++
Java
JavaScript
SQL
HTML/CSS
PHP
XML
Frameworks & Libraries
Transformers
TensorFlow
Pytorch
Scikit-Learn
Numpy
Pandas
Matplotlib
OpenCV
APIs & Backend
REST API
FastAPI
Flask
Node.js
.NET 8
ML & AI
Machine Learning
Deep Learning
Transformers
BERT
GPT-4
NLP
RAG
Large Language Models
Computer Vision
Feature Engineering
BLEU
ROUGE
Encoder Models