Software Engineer

Reet Chatterjee

Phoenix, AZ +1-480-***-**** **************@*****.*** . https://www.linkedin.com/in/rtct/ Education

Arizona State University, Tempe, USA August 2019 to May 2021 Masters in Computer Science

Courses: Statistical Machine Learning, Distributed Database Systems, Mobile Computing, Data Mining, Perception in Robotics, Foundations of Algorithms.

CGPA : 3.8/4

R.V College of Engineering, Bangalore, India August 2014 to June 2018 Bachelors in Computer Science & Engineering

CGPA : 8.3/10

Skills

Languages and Libraries: Python, Java, C, C++, HTML, CSS, JavaScript, MySQL, PostgreSQL, Node.js, MongoDB, Scala, SQL, Linux, Shell. Tools/Frameworks: React, Django, Flask, Elastic, AWS, Google Cloud, Spark, Hadoop, Docker, GIT, Apache, Redis, Nginx, Selenium, Android. Machine Learning: Keras, NLTK, OpenCV, Scikit-Learn, TensorFlow, MATLAB, PyTorch, Deep-Q Learning. Professional Experience

Arizona State University Software Engineer – Platform Backend May 2020 – Present Python, MySQL, JavaScript, Selenium, Node.js, Django, Nginx

• Designed and implemented a plugin for ASU CMS, correcting previous bugs and improving enrolment speed by 75% through in-memory indexing.

• Modified open-source library ‘nbgrader’ in Python to add randomisation feature that enabled instructor to distribute different versions of assignments to thousands of students and auto-grade them.

• Designed and Administered the MySQL database for Actuarial Analysis.

• Designed dynamic web applications with Bootstrap and vanilla Javascript and deployed on in-house servers with Nginx.

• Responsible for Maintaining IT infrastructure for the School with End-point System Management Tool JAMF and Bash Scripting. Mypustak Software Engineer Intern – Full Stack January 2019 - July 2019 Python, React, Django, PostgreSQL, Elastic, AWS

• Worked with the development team to create the e-commerce platform for the company.

• Used Python (Django) REST-based API along with React components at the front-end.

• Implemented token-based authorisation from scratch to strengthen security.

• Integrated Elastic Search to improve the efficiency and accuracy of user search queries by 80%. Conscript Software Engineer Intern – Artificial Intelligence September 2018 - December 2018 Python, NLTK, OpenCV, AWS, Flask

• Developed Emotion Recognition and Natural Language Processing modules with NLTK and OpenCV for an AI Interview Bot to automate the Video Interview process.

• Integrated the modules with other components to serve as a Python Application and deployed to cloud through AWS. IBM Software Engineer Intern – Web Development June 2016 - July 2016 Java, Spring, HTML, CSS, JavaScript, Bootstrap

• Created Web Application ‘Public Information Retrieval System’ modules using Java J2EE and Spring Framework.

• Designed the Front-End with Bootstrap and the Backend With Servlets.

• The functionality allowed for admins to improve efficiency by optimising resource allocation. Projects

• Artificial Pancreas - Bolus Insulin Determination from CGM Data. January 2020 to May 2020 Implemented several modelling techniques to determine the quantity of meal taken by a person through raw CGM data. Supervised and Unsupervised models like SVM, Random Forests, K-Means, DB-Scan, etc. were used to predict the measurement of Insulin required to handle the intake. Pre- processing steps involved extracting relevant features like Coefficient of Variation and FFT from raw signal data.

• Pursuit Evasion Game. January 2020 to May 2020

Designed the algorithm using ROS and Gazebo to make a turtle bot follow a person in different environments while avoiding several obstacles using only a camera as a sensor to the environment and performed 3D pose estimation on objects with a pair of images from stereo cameras.

• Hot-spot Analysis from Geo-Spatial Data. August 2019 to December 2019 Set up our own cluster consisting several AWS Elastic-Beanstalk server nodes and executed jobs of applying spatial statistics to spatial-temporal big data in order to identify statistically significant spatial hot spots using Apache Spark and Hadoop File System. The task is from ACM SIGSPATIAL GISCUP 2016.

• Sign-Language Prediction from Skeletal Data. August 2019 to December 2019 Generated skeletal data from video using PoseNet and trained several models on the sequential data to detect the sign-language in videos. Achieved accuracy of 78% from small training set while deploying the models as a REST API and consuming the APIs with an Android Mobile Client.

• Self-Driving Car Model Simulation January 2019 to March 2019. Designed a sensor-based self-driving car agent in simulation with Reinforcement Learning using PyTorch which can reach its destination avoiding various two-dimensional obstacles in complex environments.

• IOT Based Automated Toll Booth Management System. August 2016 to November 2016 Implemented a Model of Automated Toll Booth with Verification and Payment through RFID Tags with Arduino Microprocessor using C++.

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