Vivek Maskara

Vivek Maskara

GRA at The Luminosity Lab, ASU | Ex Senior Software Engineer, Zeta | Volunteer, Wikimedia Foundation

Arizona State University

Hello!

I am currently pursuing my Masters in Computer Science from Arizona State University. I completed my bachelor’s in Software Engineering from Delhi Technological University. I love writing code, developing apps and creating websites.

As a full stack Software Engineer at Zeta, I helped in building a suite of products for digitizing office cafeterias used by ~700 corporates and attributing to 1 million+ monthly transactions. With strong Computer Science fundamentals and experience across multiple engineering verticals, I always tend to bring a unique perspective when solving business problems.

I have been associated with the Wikimedia Foundation as a volunteer for the past 3 years, contributing to their Wikimedia Commons Android app.

Interests

  • Artificial Intelligence
  • Computer Vision
  • Android app development

Education

  • Master of Science, Computer Science, 2021

    Arizona State University

  • Bachelor of Technology, Software Engineering, 2016

    Delhi Technological University - New Delhi, India

Experience

 
 
 
 
 

Graduate Research Assistant

The Luminosity Lab, ASU

Mar 2020 – Present Tempe, Arizona

Responsibilities include:

  • Developing a machine learning model for detection of Neuroblastoma using histopathological images for PCH hospital.
  • Researched and built the MVC for indoor parking automation using YOLO and DeepSort for real time vehicle tracking.
  • Contributed to the backend for ASU’s end to end PPE response network for producing and delivering medical supplies.
  • Built a Customer 360 dashboard for Bank of West using Neo4J graph database, Flask backend and React for frontend.
  • Published a gamified supply chain management learning app funded by USAID, ShipShape for iOS and Android.
 
 
 
 
 

Senior Software Engineer

Zeta, Directi

Jun 2016 – Nov 2019 Bangalore, India
  • Built NFC based contactless payments & custom ordering solution for POS attributing to 1 million+ monthly transactions.
  • Contributed to over 20+ projects in Zeta spanning across Android, Raspberry Pi and backend microservices.
  • Responsible for optimizing query performance for PostgreSQL and building throughput and service health monitoring dashboards using Grafana and Kibana.

Recent Posts

Tabular Synthetic Data Generation using CTGAN

In this post we will talk about generating synthetic data from tabular data using Generative adversarial networks(GANs). We will be using the default implementation of CTGAN [1] model. Introduction In the last post on GANs we saw how to generate synthetic data on Synthea dataset.
Last updated on Dec 18, 2020 3 min read Deep learning, GANs
Tabular Synthetic Data Generation using CTGAN

Covid-19 Diagnosis using Radiography Images

In this notebook, we will try to classify images from the Covid-19 Radiography Dataset[1] using a pre-trained ResNet-18 network. We will be using the PyTorch library for building our network.
Last updated on Dec 19, 2020 3 min read Deep learning, Image Classification
Covid-19 Diagnosis using Radiography Images

Literature Survey: Human Action Recognition

Over the last couple of months, I have been going through a lot of literature about human action recognition using computer vision. In this post, I will share a brief survey of Human Action Recognition.
Last updated on Jul 22, 2020 14 min read Deep learning, Action Recognition
Literature Survey: Human Action Recognition

Generating Tabular Synthetic Data Using GANs

In this post, we will see how to generate tabular synthetic data using Generative adversarial networks(GANs). The goal is to generate synthetic data that is similar to the actual data in terms of statistics and demographics.
Last updated on Dec 18, 2020 6 min read Deep learning, GANs
Generating Tabular Synthetic Data Using GANs

Implementing YOLOV2 from scratch using Tensorflow 2.0

In this notebook I am going to re-implement YOLOV2 as described in the paper YOLO9000: Better, Faster, Stronger. The goal is to replicate the model as described in the paper and train it on the VOC 2012 dataset.
Last updated on Oct 21, 2020 15 min read Deep learning, Object Detection
Implementing YOLOV2 from scratch using Tensorflow 2.0
See all posts

Projects

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All Apps Data Viz

Data Viz: San Diego Burritos

The project uses zoomable circle packing visualization below shows the burritos and their ratings in San Diego.
Data Viz: San Diego Burritos

Data Viz: Trump Approval Ratings

This project uses a pair of visualizations to promote opposing viewpoints using the same base dataset
Data Viz: Trump Approval Ratings

Data Viz: Mystery at the Wildlife

This project was done as part of CSE 578 course. The primary goal of this project is to identify reasons behind the decline in the population of the Rose-crested Blue Pipit bird in the city of Mistford.
Code Slides Video
Data Viz: Mystery at the Wildlife

Wikimedia Commons

An open-source app allowing the Wikimedia community to contribute content to Wikimedia Commons.
Code
Wikimedia Commons

Spaced

AR App for Zeta’s design meetup 2019
Spaced

ShipShape

A gamified approach to educate on supply chain skills in an engaging manner.
ShipShape

Ppe Response

A decentralized production network to print, sterilize and deliver personal protective equipment (PPE) for those on the front lines of the coronavirus response.
Ppe Response

Zeta

Contributed in building products for Zeta Express, an end to end solution for digitizing cafeterias
Zeta

Certification

Neural Networks and Deep Learning

Coursera Jul 2020
Course on Neural Networks by DeepLearningAI
See certificate

TensorFlow in Practice Specialization

Coursera Mar 2020
Introduction course on using Tensorflow
See certificate

Convolutional Neural Networks

Coursera Feb 2020
Course on CNN by DeepLearningAI
See certificate