About Me
I'm a 21-year-old Machine Learning enthusiast based in Bengaluru, currently pursuing my B.E. in Artificial Intelligence and Machine Learning at CMR Institute of Technology.
Skilled in Python, SQL, and full-stack development using React. I have practical experience in building data science pipelines and implementing machine learning algorithms.
I am passionate about leveraging AI to solve real-world challenges, with a strong foundation in deep learning, generative models, and applied AI research. My goal is to build intelligent systems that drive meaningful impact.
Languages & Frameworks
AI & Machine Learning
Data & Tools
Platforms & Other
◆ Education
Expected 2026
B.E. in Artificial Intelligence & ML
CMR Institute of Technology, Bengaluru.
CGPA: 8.51
2022
Pre-University Course - Science (PCMB)
St Joseph's Pre University College, Bengaluru.
Score: 83.3%
2020
10th Grade – ICSE
Cambridge School, Bengaluru.
Score: 81.8%
◆ Experience
Jan 2026 – May 2026
Data Scientist Intern
Cheerans Global Solutions Pvt Ltd.
Designed and implemented the frontend for a cafe billing software. Executed data analysis, cleaning, and built interactive dashboards.
Selected Work
Full-Stack • Real-time
JourneySync App (Startup Idea)
A comprehensive platform for live ride coordination and journey management. Features real-time maps, sophisticated user lobbies, ride radar, and a join-request approval flow designed to streamline shared travel.
APP
WS/API
DB
MAPS
React • Node.js • NLP
AI Resume Screener & Chatbot
Automates resume screening and candidate engagement. Uses Hugging Face & spaCy NLP to semantically match candidates, providing explainable scores and real-time chatbot feedback.
REACT
NODE
NLP
OUTPUT
Python • Flask • GenAI
T&C Summarizer (n8n & FAISS)
Generates plain-language summaries of complex legal terms using Hugging Face Transformers. Scales via n8n workflows and FAISS vector search for accessible legal transparency.
DOC
FLASK
N8N
FAISS
Python • MySQL • Pandas
Student Mental Health Analytics
Advanced data analysis pipeline tracking correlations between demographics and mental health. Includes ETL scripts and normalized relational SQL schemas with complex aggregation.
DATA
PANDAS
SQL
DASH