Hello!

I am Ankitha Suresh

Student, Developer & Wanderlust

About Me

Who am i?

Hey there! 👋 I'm a Master's student in Computer Science at UMass Amherst, and I've worked as a software engineer at HPE. I love diving into code, building algorithms, and creating cool tech solutions.

I'm passionate about building excellent software that improves the lives of those around me.

When I'm not studying or coding, you'll probably find me checking out the latest tech trends, solving puzzles, traveling, or watching a good thriller movie.

My Skills

What am I good at?

Python
90%
Java
80%
HTML & CSS
85%
Javascript
90%
REST
85%
System Design
90%

Experience

Headstarter 07/2024 - 08/2024

Software Engineer Fellow

  • Developed and merged a pull request for API integration with Microsoft Dynamics 365 CRM, leveraging RESTful services to streamline data synchronization, boosting data accuracy and revamping workflow efficiency by cutting manual input by 89%.
  • Built 3+ full-stack applications using React, integrating large language models (LLMs) for AI-driven features, enhancing user engagement and application performance.
  • Innovated a responsive pantry management system using HTML, CSS, JavaScript, AWS CDK, and MySQL, enabling efficient tracking of 1,000+ inventory items, and incorporated predictive analytics for real-time stock predictions, attained 500 Mbps throughput via load balancing.

Hewlett Packard Enterprise 09/2021 - 07/2023

Software Engineer

  • Optimized cloud deployment and CI/CD pipelines for HPE Serviceguard on AWS, by deploying Docker and Kubernetes, reducing release cycles by 75%. Automated workflows and refactored 2,000+ lines of code to boost scalability and system reliability.
  • Engineered a fault-tolerant system to migrate legacy array processes to a Kafka Framework, improving workload efficiency by 85% by reducing downtime from 30 minutes to 4.5 minutes during critical failures for HPE Serviceguard environments.
  • Accomplished successful development of a high-availability cluster management API, facilitating seamless automation of node failover. Integrated RESTful APIs with Serviceguard Manager, reducing manual intervention by 70%, supporting 50+ nodes in production.

Hewlett Packard Enterprise 02/2021 - 08/2021

Research and Development Engineer

  • Enhanced system reliability by integrating real-time database updates using MySQL, reducing manual data entry by 90% and ensuring timely, reliable data delivery to customers.
  • Delivered a custom user interface that automated manual maintenance tasks using Ansible, streamlining distributed system management, reducing operational costs by 25%.
My Work

what have I done?

Buddy: AI Chatbot Github

It is an intelligent conversational AI built with Next.js and React, using OpenAI’s models for accurate responses. It features Retrieval-Augmented Generation (RAG) to pull from a knowledge base, user login for personalized interactions, and a feedback mechanism for rating responses. Leveraging Pinecone for knowledge management and MongoDB for data storage, the application is efficiently deployed on Vercel.

Car Make and Model Classification Github

Engineered a highly efficient machine learning model using Convolutional Neural Networks (CNNs) to analyze a vast dataset of car images, achieving precise prediction of car make and model. By implementing the Inception-v3 model, I attained a 92% accuracy rate, which facilitated the development of an advanced image recognition system for automotive applications.

Portfolio GitHub

Developed a dynamic and interactive portfolio website using HTML, CSS, Javascript and PHP. This project showcases my skills and projects, providing an engaging user experience with smooth navigation and responsive design. The backend handles data efficiently, ensuring seamless content management and display.

Algocards GitHub

Algocards is an AI-powered tool that generates flashcards for mastering Data Structures and Algorithms (DSA). It offers three sets: Basic DSA, Algorithms, and Advanced DSA, along with assessments to test user knowledge. Built with Next.js and React, Algocards provides an interactive learning experience for DSA enthusiasts.

Crop Yield Prediction GitHub

Used Python, scikit-learn, and pandas to analyze a 5-year agricultural dataset. By adapting the Gradient Boosting Algorithm and employing feature scaling and selection techniques, I achieved a 91.8% accuracy in predicting crop yields. Additionally, I developed a Heroku-powered mobile app that determines suitable crops and predicts yield percentages based on user-provided location data, optimizing agricultural productivity by up to 75%.

Buddy: AI Chatbot Github

It is an intelligent conversational AI built with Next.js and React, using OpenAI’s models for accurate responses. It features Retrieval-Augmented Generation (RAG) to pull from a knowledge base, user login for personalized interactions, and a feedback mechanism for rating responses. Leveraging Pinecone for knowledge management and MongoDB for data storage, the application is efficiently deployed on Vercel.

Car Make and Model Classification Github

Engineered a highly efficient machine learning model using Convolutional Neural Networks (CNNs) to analyze a vast dataset of car images, achieving precise prediction of car make and model. By implementing the Inception-v3 model, I attained a 92% accuracy rate, which facilitated the development of an advanced image recognition system for automotive applications.

Portfolio GitHub

Developed a dynamic and interactive portfolio website using HTML, CSS, Javascript and PHP. This project showcases my skills and projects, providing an engaging user experience with smooth navigation and responsive design. The backend handles data efficiently, ensuring seamless content management and display.

Algocards GitHub

Algocards is an AI-powered tool that generates flashcards for mastering Data Structures and Algorithms (DSA). It offers three sets: Basic DSA, Algorithms, and Advanced DSA, along with assessments to test user knowledge. Built with Next.js and React, Algocards provides an interactive learning experience for DSA enthusiasts.

Crop Yield Prediction GitHub

Used Python, scikit-learn, and pandas to analyze a 5-year agricultural dataset. By adapting the Gradient Boosting Algorithm and employing feature scaling and selection techniques, I achieved a 91.8% accuracy in predicting crop yields. Additionally, I developed a Heroku-powered mobile app that determines suitable crops and predicts yield percentages based on user-provided location data, optimizing agricultural productivity by up to 75%.

Buddy: AI Chatbot Github

It is an intelligent conversational AI built with Next.js and React, using OpenAI’s models for accurate responses. It features Retrieval-Augmented Generation (RAG) to pull from a knowledge base, user login for personalized interactions, and a feedback mechanism for rating responses. Leveraging Pinecone for knowledge management and MongoDB for data storage, the application is efficiently deployed on Vercel.

Contact

Get In Touch!

413 472 0926
ankithasures@umass.edu