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Data Analyst

Kitchener, ON, Canada
April 17, 2020

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Specialized in Machine Learning and Deep Learning

[ Ó 647-***-**** Waterloo, Canada EXPERIENCE




June 2014 – May 2018 New Delhi, India

Worked on the development of unmanned

aerial vehicle. Responsibilities included system

designing, integration & embedded program-


Worked on ANPR - Automatic car number

plate recognition software. SVM and ANN

algorithms were used for numberplate recog-

nition and optical character recognition.


Sentiment Analysis of Yelp Review Dataset

Built and explored various ML models for clas-

sification using KNN, XGBoost, Decision Tree,

Naive Bayes, Random Forest, SVM, Gradient

Boost, LSTM and MLP.

Major challenges were class imbalance, using

different word vectorizer and hyperparameter

tuning to achieve better accuracy score than

academic journels.

Ship Detection in Optical Satellite Imagery

Developed, modified and implemented pattern

recognition for ship detection and localiza-

tion in satellite images using classical machine

learning algorithms like SVM and Random For-

est for classification and for generating feature

vector using LBP, HoG and saliency map.

Cognitive Engineering Case Analysis:

Google Maps Application on Android

Examined the "Google Maps on Android" as

the problem to find out decision making ca-

pabilities and interface usage. the impact of

these human behaviour by user experience

level and usage process. Experiments were

performed using CTA & CD.

Automatic Number Plate Recognition Soft-


Developed a classical machine learning SVM

model in C++ & Qt for recognizing the En-

glish characters from the segmented images

extracted from video frames. SVM model is

trained using Google tesseract OCR dataset

available in public domain.

Anomaly Detection in Autonomous vehi-


The project is to find anomalies in the au-

tonomous vehicle dataset using classical ma-

chine learning algorithm and LSTM neural net-

work, thereby developing a prediction model

for the parameters and finding anomalies in

the dataset.


Experience with Machine Learning skills - tensorflow, scikit-learn, NLTK, Pandas, Matplotlib and data visualization technique using Tableau, Python and R.

Developed Classical Machine Learning and Neural network Model for Sentiment analysis of yelp Food review dataset of 1 million to achieve higher results than academic papers.

Used image processing technique to generate feature vector using HoG, LBP, Color Histogram and combination of these, which was used to Classify the ships in satel- lite images. PCA was used to reduce feature size and classification score of 82% achieved with Pattern recognition methods SVM and Random Forest.

Used Python to perform ETL of dataset from Postgres & SQL database and devel- oping neural network model like LSTM.

6+ years of experience in C/C++ programming with Data structure, algorithms and SQL queries. And 3+ years of experience in machine learning. ACHIEVEMENTS

Winner of Telus Challenge at UofT Hackathon - Solved a Social problem

Participated in NASA Space App Challenge

Former Vice-president of Yantra Society


"ANPR Indian system using Surveillance Cameras" 2015 Eighth International Con- ference on Contemporary Computing (IC3), 20-22 Aug. 2015. EDUCATION / COURSES

M.Eng in System Design Engineering

University of Waterloo

May 2018 – October 2019 Waterloo, Canada

Methods and Tools for Software Engineering

Pattern Recognition

Data and Knowledge Modeling and Analysis

Intelligent Systems Design

Text Classification

B.Tech in ECE

Indraprastha University

August 2010 – July 2014 New Delhi, India



C C++ Python R Tableau Shell MYSQL Powershell LAT EX Jupyter

Ancillary Technologies

Linux Keras Tensorflow Scikit-learn NLTK PostgreSQL Git/Gitlab SolidWorks Qt Google Cloud Platform SPSS Data Cleaning

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