insiyeah

Insiyah Hajoori

I'm a machine learning enthusiast. From 2018, I've been learning more about the field by taking various courses online. From the math to implementation, machine learning is the field for which I can work continuously. Later on I shifted to integration of machine learning with web/android applications/extensions. The driving force for me is to make machine learning more accessible. Instead of python scripts, I want them to come alive. Integrating it to various applications expands the scope of ML to a whole new level. Instead of just training/testing on batch data, using it to make stuff happen is what I aim to achieve. Specifically, for this edition, I plan to work on its application in dev tools. The recent project I did was in Google summer of code under biomedical informatics, Emory University. I was assigned to make testing various deep learning models in the browser on client slide on the whole slide images. I worked with tensorflowjs. I learnt about memory management when integrating machine learning in web applications, webGL and about so many fields I still have to explore. I am passionate about developing applications which are of actual utility. The app I plan to develop is something I myself need to improve my productivity as a developer and hackathons provide the best platform and motivation to do so.

Projects

CryptoEstate

Convert your land into a crypto currency to invest your extra money in the growing market of real estate.Node.js

Patent Lite

A decentralized intellectual property acquiring system using permissioned ethereum blockchain with web and android interface.jQuery, JS, Android, Android Studio, Postman, Microsoft Azure

Skills

JavaScript
Node.js
TensorFlow
PyTorch
Machine Learning

Experience

  • Google - GSoC - Student Developer
    May 2019 - July 2019

    The following modules are to be integrated with caMicroscope:

    Creating a workflow to allow model developers to allow their model to be run on a selected image or region of interest by the client, to identify cellular features or cancer.
    Add the latest deep learning models researched in the area of digital pathology to caMicroscope to help the pathologists.
    Improve the segmentation app.
    A tutorial to enable users to make models compatible with caMicroscope.
    The motto of this project is to make the recent research in deep learning more accessible

    https://summerofcode.withgoogle.com/projects/#5485039276523520