Hello World

I'm Ishmeen,
a Data Scientist building intelligent systems at the intersection of ML, NLP & healthcare.

Ishmeen Garewal portrait

About

I'm a Master's in Data Science student at Columbia University with a background in Computer Engineering (CGPA 9.64/10) and 5 peer-reviewed publications in IEEE and Springer. My work spans machine learning, NLP, and deep learning — applied to real-world challenges in healthcare, traffic safety, and social impact. I've interned at Deloitte and IIT Roorkee, and currently serve as a Graduate Student Assistant at the Northeast Big Data Innovation Hub at Columbia.

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Experience

Northeast Big Data Innovation Hub

Graduate Student Assistant · Columbia University

Jan 2026 – Present

Supporting student-focused programs and regional data science initiatives for one of four NSF-funded Big Data Innovation Hubs.

Indian Institute of Technology (IIT), Roorkee

Research Intern

May 2025 – Aug 2025

  • Processed 5,000+ vehicular trajectories for traffic data analytics and AI-driven compliance systems.
  • Formalized 120+ Indian traffic rules into machine-readable formats using LLMs, increasing rule-detection accuracy by 22%.

Deloitte Touche Tohmatsu India LLP

Internship Trainee

Jun 2024 – Jul 2024

  • Designed an automated FX deal valuation framework using Python & QuantLib, reducing manual workflows by 75%.
  • Built a Django-powered interactive visualization platform used by 40+ consultants.
  • Conducted comparative analysis of RBI and NBFC risk policies, identifying critical regulatory gaps.

FCRIT, University of Mumbai

Research Intern

Jul 2024 – Jan 2025

Published research at the intersection of NLP, Quantum Computing, and Blockchain in IEEE Xplore and Springer.

Education

Columbia University

Master of Science in Data Science

Aug 2025 – Dec 2026

Relevant Coursework: Probability & Statistics, Exploratory Data Analysis & Visualization (R), Applied Deep Learning, Machine Learning for Data Science, Statistical Inference & Modeling, Causal Inference, Forecasting, Analytics in Action.

Collaborating with Columbia Business School MBA students through Analytics in Action to solve real industry challenges.

University of Mumbai

Bachelor of Engineering in Computer Engineering

Jun 2021 – May 2025

CGPA: 9.64/10.0 — Graduated in the top 10% of the class; ranked 2nd in third year. Core coursework in Data Structures, Operating Systems, Machine Learning, Big Data Analytics, AI, Blockchain, and Cryptography. Published 5 research papers during undergraduate studies.

Skills & Technologies

The tools and technologies I work with every day.

Languages

Python R SQL Java C# JavaScript Solidity

Machine Learning & AI

PyTorch TensorFlow Scikit-learn Keras NLP (NLTK, spaCy) CNNs LLMs / Gen AI LDA / NMF Collaborative Filtering

Data & Visualization

Pandas NumPy Matplotlib Plotly D3.js ggplot2 Tableau Streamlit

Tools & Platforms

AWS (EC2, S3) Django Flask Git / GitHub Docker Unity (AR) Jupyter Linux

Publications

Peer-reviewed research published in IEEE and Springer venues.

IEEE Xplore
Emerging Applications and Challenges in Quantum Computing: A Literature Survey

Literature Survey

An extensive survey of current quantum computing applications, highlighting emerging opportunities and key challenges for future growth.

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IEEE Xplore
Topic Modeling for Identifying Emerging Trends on Instagram Using LDA and NMF

Research Paper

Investigates trend identification on Instagram by leveraging Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF), offering insights into evolving online trends.

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IEEE Xplore
Blockchain-Based Smart Contracts for Decentralized Vehicle-to-Grid (V2G) Load Management

Smart Contract Implementation & Research

Presents a decentralized V2G system using Solidity smart contracts on Ethereum to dynamically manage grid demand while ensuring secure energy transactions between EVs and the power grid.

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Springer LNNS
FoodMO: A Food Nutrient Analysis Application Using OCR and Machine Learning

Technical Paper

Details the development of FoodMO — a mobile application that uses OCR and machine learning to analyze food nutrients and provide healthier dietary recommendations.

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IEEE Xplore
Natural Language Processing: A Survey of Approaches, Applications, and Future Directions

Literature Review

A comprehensive survey of NLP techniques covering the latest approaches, real-world applications, and promising future directions for research.

View Paper →

Get In Touch

Whether you're exploring a collaboration, looking for a data-driven problem-solver, or just want to connect about ML, NLP, or data science — I'd love to hear from you.