Jyothi Vaidyanathan

A Computer Science enthusiast for whom the love to learn never ends!!

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Hi there! This is my portfolio website. Here you can find general info about me, my work, projects and a lot more!

I have previously worked at Atlassian and Micro Focus, and currently, I am a graduate student pursuing Computer Science at San José State University. My areas of interest include Software Engineering, Machine Learning, and Enterprise Systems.

Typically, I love learning about new technologies related to Computer Science.

Languages

Python
Java
SQL
C++
JavaScript
Go

Databases

MongoDB
Oracle
MySQL
PostgreSQL

DevOps and Cloud

Amazon Web Services
Google Cloud Platform
Docker
CircleCI
Vercel

Web Application

Streamlit
Flask
React.js
Node.js
Next.js
Material-UI

IT Integrations

Workday Integrations
Workday Studio
Robocorp
Workato
UiPath
Kainos
Splunk

Data Science and Big Data

Deep learning
Generative AI
Machine learning on Graphs
Python
Streamlit
Big Query
Hadoop
OpenRefine
Tableau

Tools and Software

Agile
Scrum
Twilio
Jira
Confluence
Trello
TortoiseSVN
VMware ESXi
Postman

Below, you will find links to project demos, applications, and GitHub repositories for my projects based on Software Engineering and Machine Learning.

Software

Resume Organizer

A Python program where resumes are organized into folders based on role and company name, enabling candidates to apply to jobs quickly.

Support Assistant

A versatile application using Next.js and OpenAI, capable of fetching precise answers

Flashcards

A web application built using React to learn 3+ languages through flashcards.

Expense Tracker

A web application to track expenses. Built using HTML, CSS, Flask, and MongoDB.

Pantry tracker

A Next.js and Firebase based app that enhances overall household management and reduces grocery costs

Email tracker

A smart mobile application designed to optimize email communication by tracking recipient engagement, and ensuring timely follow-ups.

GlobiAlarm

An Android app that lets you set alarms even beyond 24 hours, very helpful to remember important dates of the year.

Machine Learning

Knowledge Graph Builder

A Next.js chat application that leverages LlamaIndex to generate knowledge graphs for any term, enabling users to receive accurate, context-based responses to their queries.

Similar Food Finder

An app built using Vertex AI, Vector database, RAG concepts, and Streamlit, that can help nutritionists, consumers, and food delivery companies find foods similar to a given image of a dish.

Restaurant Recommender System

A system with user reviews and connections’ data, to recommend restaurants based on Yelp dataset. Built using Python, Collaborative filtering, link prediction, and GraphRec.

Fake Reviews Detection

An ML system built using an e-commerce dataset to identify fake reviewers. Built using Python, Hadoop, and OpenRefine.

Movie Recommender System

A conversational application to recommend movies using LLMs (Open AI and Gemini AI), Streamlit, and Python.

Hackathons

AI for Good Hackathon (3rd Prize)

Captain Quill - A user-friendly AI-powered platform enabling tutors to effortlessly provide automatic, high-quality feedback on student work, either by typing in transcriptions or uploading text files.

CalHacks

Chillbert - A voice-powered agent designed to engage users and mental health patients in casual, mood-lifting check-ins throughout the day.

Publications

AAAI Symposium 2025

Co-authored a paper titled 'Survival Analysis for Cancers of the Brain, CNS and Bone using Retrieval Augmented Generation on the SEER Database' and presented it at the AAAI Spring Symposium 2025 (AI for Health). Paper will be published soon.

Stat4Onc Annual Symposium 2025

Our work on cancer survival analysis was accepted for presentation at the 8th Annual Stat4Onc Symposium, held at the Stanford University School of Medicine.

Achievements

Grad Slam Finalist

Grad Slam is a competition where graduate students present their research to a live audience and a panel of judges.

Contact