Who am I?

Hi, I’m currently a graduate student at Lakehead University My coursework is mostly realted to Machine Learning and Deep Learning.However, I’m always curious! I love to learn in general especially a new stack/technology. My focus right now is to learn the most I can in terms of different technologies and specialize later!

I love cs, so I do cs

I am really interested in:

  • programming competitions
  • technology

  • algorithms & data structures

  • AI & machine learning

I am just an enthusiast, but a really motivated one :D

Feel free to message me about anything related to tech, I’m always open to a conversation!

Education

Master’s in Computer Science Aug. 2019 – Dec. 2021

Coursework: A.I., Big Data, Deep Learning, NLP

Lakehead University,(Avg: 90%) Thunder Bay, ON

Bachelor’s in Computer Engineering Aug. 2015 – April 2019

Dharamsinh Desai University, (Avg: 84%) Nadiad, Gujarat

Work Experience

Web Developer (part-time) April 2021 – June 2021

Vingo Consulting Brampton, ON

  • Developed Single Page Applications at various scales with React. Used Gatsby and GrpahQL to build websites powered by the JAMStack.
  • Build React Components and pages with content coming from a headless CMS (Contentful).
  • Performed various SEO optimizations.

Python Automation Engineer May 2020 – Dec. 2020

Royal Bank of Canada (RBC) Toronto, ON

  • Worked as a part of QE Anti Money Laundering (AML-IT) team developing test automation for financial applications. Worked with various technology stack and testing frameworks like Nodejs, Pyspark, Selenium, Ready API, and Robot Framework.
  • Developed test automation for data-heavy back-end applications and interacting with different ETL pipelines and Unix servers.Implemented End-to-End test automation with proper test setup and tear down to ensure all tests were consistent and repeatable. Setup triggers with CI/CD pipeline. Achieved 90% Test coverage.
  • Developed a Web tool to parse propitiatory format files that helped reduce the manual testing effort for the client.

Project Research Intern Jan. 2019 – April 2019

PRL, Department of Space, India Ahmedabad, Gujarat

  • Developed a fully automated solution to collect spectral emission data using night-glow emission spectrograph. The goal was to automate it to collect the data from sunset to sunrise based on location and day of the year.
  • Analyzed the collected data from spectrograph to predict the temperature of the upper atmosphere during the period using various signal analysis algorithms. Generate analysis report in postscript format to observe/monitor the effect over a long period of time
  • The spectrograph is deployed at PRL Observatory and the whole project was done in MATLAB and the SDK provided by the manufacturer.

SWE Summer Intern May 2018 – June 2018

Infostretch, India Ahmedabad, Gujarat

  • Developed MEAN Stack application for the company’s Internal assessment platform. Worked extensively with Nodejs and MongoDB to rebuild and improve their existing technology stack.
  • Designed the database, Developed Restful APIs, and algorithms to efficiently solve problems.
  • Worked with various industry experts and gained some insights into the tech industry through personal discussions and talks.

Technical Skills

Languages:Python, Javascript, C/C++, SQL (Postgres), HTML/CSS, CSharp, MATLAB.
Frameworks: React, Node.js, NextJS, Gatsby
Libraries: Pandas, NumPy, Matplotlib, Tensorflow, Pytorch
Developer Tools: Git, Docker, Jenkins, Google Cloud Platform, VS Code, VIM , PyCharm
Testing Frameworks:Robot Framework, Selenium, Ready API, Mocha, Chai, Pytest
Industry Knowledge: Data Structures and Algorithm, Object Oriented Design, MVC pattern, Linux, REST,
GraphQL, Cloud infrastructure, Agile

Projects

Image Classifier on SUN397 dataset|Python, Pytorch, FastAI Fall 2020

  • Developed a DCNN Classifier to Classify images from SUN397 dataset into 397 different classes using transfer learning.
  • Learned to use Tensorflow/Keras and Pytorch, how to deal with huge dataset without causing memory overflow, training model on cloud and to use various keras callbacks to optimize training time.
  • Used various techniques such as Transfer Learning, Data Augmentation, Feature Fusion Technique, Discriminative Learning Rate, One-cycle Policy to improve accuracy of the model.

Crime Analysis and Forecasting|Python, Numpy, Pandas, Sci-kit learn Fall 2019

  • The project focuses to use past records of crime incidents in Vancouver to pre- dict(classify) danger of specific type of crime occurrence at specific Neighbourhood for certain day of week and time.
  • We try to predict most probable location of crime based on previous reportings for given Date,Time,Neighbourhood and Crime Type. Worked with Various Machine learning frameworks like Numpy, Pandas, Sci-kit learn, ..etc.

Gujarati Wordnet Python API|Python, Numpy, Pandas, NLTK Winter 2019

  • Developed a Python wordnet API for Gujarati language using Indo-Wordnet Database. The API can be used by anyone who is interested in doing NLP Research with Gujarati Language.
  • You can use the API to get word similarity, antonynms, synonyms, root word ..etc. The module is developed using Numpy, Pandas, NLTK framework.