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
60%
HTML & CSS
85%
Javascript
90%
React.JS
80%
Next.JS
85%
REST API
75%
Docker
60%
System Design
70%

Experience

Headstarter 07/2024 - 08/2024

Software Engineer Fellow

  • Developed and merged a pull request for API integration with Microsoft Dynamics 365 Sales CRM, leveraging RESTful services to automate data synchronization, boosting data accuracy by 30% and optimizing workflow efficiency by reducing manual input by 40%.
  • Built 3+ AI-engineered, full-stack applications leveraging large language models (LLMs), utilizing a diverse technology stack to create scalable solutions that significantly enhanced user engagement and application performance.
  • Innovated a predictive analytics engine for a pantry management system using Python and PostgreSQL, leveraging Docker for containerization and implementing advanced data modeling techniques to optimize inventory tracking and automate resource management.

Hewlett Packard Enterprise 09/2021 - 07/2023

Software Engineer

  • Spearheaded the design and deployment of custom automation scripts, integrating cloud infrastructure and optimizing resource management. Achieved an 80% reduction in deployment time and significantly improved system scalability.
  • Engineered a fault-tolerant system that modernized legacy array processes and enhanced workload recovery efficiency by 92% during failures while improving resilience and minimizing downtime for business continuity
  • Architected custom monitoring solutions, automating critical system checks and improving operational control for distributed systems, reducing system outages and manual interventions by 85%.
  • Automated cloud infrastructure management with Python and Bash using IaC principles, reducing testing and setup times by 60% while enhancing scalability, resilience, and fault tolerance on AWS and Azure

Hewlett Packard Enterprise 02/2021 - 08/2021

Research and Development Engineer

  • Developed an automated support matrix webpage, seamlessly integrating database updates, resulting in a 90% reduction in manual data entry and ensuring accurate and up-to-date information for customers.
  • Configured an alert system using Python and Oracle DBMS, promptly notifying users of critical failures; reduced downtime and improved overall system reliability.
My Work

what have I done?

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.

Contact

Get In Touch!

413 472 0926
ankithasures@umass.edu