Jaya Amit Sai Gurrala 
jg6660@nyu.edu

I have completed my masters in CS at New York University during May 2023. I worked as Software Delivery Optimization intern at IPC Systems in DevOps team. Previously I worked as Recitation Leader for Computer System Organization course under Prof. Hasan Aljabbouli , Prof. Jean Claude Franchitti and Prof. Douglas Moody at NYU Courant. I have completed my undergraduate degree in Computer Science from NIT Andhra Pradesh in 2020, with honors advised by Prof. Nagesh Bhattu Sristy

I have also completed my internship at BDL Bhanur in Hyderabad as a Project Student intern, where I built an E-Commerce medical application for BDL Hospital

I have experience in a variety of programming languages and frameworks.

  • Programming Languages: C++, Python, Java, C, HTML, CSS, Javascript
  • Libraries and Tools: AWS, React, Pytorch, Tensorflow
  • Relevant courses: Computer Programming, Data structures, Algorithms, Software Engineering, Operating Systems, Computer Networks, Cloud Computing, Database systems, Distributed Systems, Artificial Intelligence, Machine Learning

I am currently looking for full-time software engineer roles starting in 2023, so if you have a position available or just want to say hi, you can always mail me.

CV  /  Github  /  Presentation

profile photo
Experience
IPC Systems
Software Delivery Optimization Intern  
Fairfield, CT, USA   ·   June 2022 - Aug 2022

  • Prioritized testing for efficient switch from onsite to cloud environment accomplishing 30% reduction in cost
  • Spearheaded project implementation of RTC business rules for JIRA, BitBucket , Zephyr, Jenkins, Splunk, Maven leading to 80% improvement in user experience
  • Conceptualized with DevOps Team to implement integration of efficient management of software development life cycle

Technologies: Jira, BitBucket, Jenkins, Maven, Splunk

Bharat Dynamics Limited
Project Student Intern  
Hyderabad, India   ·   June 2019 - July 2019

  • Deployed an e-commerce medical application for BDL Hospital using Flutter by achieving an accuracy of 82% for the model
  • Conceptualized on "Inventory Forecasting and Supply Chain Management" and built a recommendation system to recommend medicines leading to an increase click rate by 20%
  • Consolidated the data used for forecasting algorithms (LSTM) leading to increased efficiency throughout the inventory

Technologies: Flutter, Python, PyTorch

Pravahya Consulting Private Limited
Software Development Engineer Intern  
Bengaluru, India   ·   May 2018 - July 2018

  • Designed news portal website Telugu Rajyam utilizing Node.js increasing website search result by 50%
  • Diagnosed, refactored and troubleshooted user interface of website improving extendibility to audience

Technologies: Node.js, HTML, CSS

New York University Courant
Graduate Student Assistant (Recitation Leader, Course Assistant, Grader)  
Remote   ·   Jan 2022 - Current

  • Facilitated tracking and monitoring goals for the progress of a cohort of 90 students and advised office hours
  • Examined topics such as Schedulers, Memory Management, File Systems and syllabus code debugging/assignments leading to increase of average GPA by 25%

Education
New York Univesity
Masters in Computer Science & Engineering   ·   3.82 / 4.0
New York City, NY   ·   2021 - 2023
NIT Andhra Pradesh
B.Tech in Computer Science & Engineering   ·   8.98 / 10.0 (3.97/4.0)
Tadepalligudem, India   ·   2016 - 2020
Projects
FoodGPT
  • Developed a frontend interface utilizing Large Language Models (LLMs) to generate diverse cuisine recipes
  • Implemented a robust data flow architecture integrating GPT-4 Vision, GPT-4 Turbo and DALL-E LLMs backend systems, and reduced API communication latency by 20%

Technologies: React, CSS, OpenAI LLM
Github: link
Demo: link
Bon-Appetit
  • Developed a react application hosted on Amplify which recommends recipes to users based on items present in pantry
  • Utilized AWS Cognito for user authentication, AWS Sage Maker to train recipe data and recommend recipes, Lambda functions to get ingredients and get recipes, DynamoDB to store user data, SQS to achieve scalability, SES to notify users about ingredients which are about to expire, API Gateway, OpenSearch

Technologies: Python, AWS, Pytorch, React, HTML5, CSS, YAML
Github: link
Dining Concierge Chatbot
  • Implemented a restaurant recommendation chatbot by using 7000+ restaurant data across different cuisines using Yelp API
  • Analyzed and developed serverless and microservice driven web application to improve customer outreach by 95%
  • Deployed the chatbot website on AWS S3 bucket, and utilized REST service interface, API Gateway with Swagger, DynamoDB, Lambda, Elasticsearch achieving scalability and efficiency of 80%

Technologies: Java, AWS, JavaScript, HTML5, CSS, YAML
Github: link
University Management System
  • Modeled the data for University Management System and deployed the database on PostgreSQL
  • Implemented a web based portal for the University Management System using python libraries streamlit and psycopg2 and connected it to PostgreSQL

Technologies: Python, PostgreSQL, Streamlit, Psycopg2
Github: link
Recipe Book
  • Implemented a prototype which classifies a relevant recipe as dessert and studied the features contributing to it and analyzed the performance against existing Machine Learning Algorithms (KNN, Support Vector Classifier, Gradient Descent, Logistic Regression)
  • Expedited optimization and analysis of different ML algorithms thereby achieving 95% performance
  • Enhanced features of the dataset resulting in 85% customer user experience by integrating the system with tableau dashboard

Technologies: Python, Pandas, Grid Search CV, Tableau
Github: link
Weather Forecast
  • Implemented a Java based weather forecasting application using OpenWeather API Connection
  • Utilized Java Swing, Maven Dependencies, REST API, JSON Data for developing the project
  • Weather will be predicted for the next 7 days based on user's input for the location

Technologies: Java Swing, Rest API, Maven, JSON
Github: link
Mini Linux Shell and Disk Performance
  • Streamlined and executed functionality and scalability for system terminal therefore improving user workflow by 85%
  • Devised a framework for I/O disk operations that augmented process execution and improve computation speed by 90%

Technologies: Python, C++
Github: link
Private Tag Recommendation System
  • Implemented a randomized noise differential privacy scheme for the model built in the context of topic modelling using python where an efficient concurrent parallel implementation is carried out in a distributed environment
  • Using Rényi Differential Private mechanism in topic modeling it maintained the privacy and also the utility of the model and performs better than linear composition and advanced composition in terms of cumulative privacy loss
  • Efficient parallel implementation of privacy aware topic modeling maintained the privacy of individuals with optimal cost

Technologies: Python, PyTorch

Thanks to Jon Barron for the nice template!