SuperVaani
Developed and deployed an LLM-powered information platform that integrates retrieval, feedback collection, and model evaluation workflows, significantly improving response quality and operational reliability.
2roles
30skills
3education
About
A dedicated B.Tech student specializing in Computer Science and Artificial Intelligence with hands-on experience in AI and data science internships. Manjree has a strong foundation in machine learning, model evaluation, and software development.
Experience
AI Intern
Dr. Reddy’s Laboratories
Jan 2026 - June 2026 (6 mo) · null
Developed a model evaluation and validation framework for Text2SQL systems, enhancing reproducibility and performance benchmarking. Built a production-grade conversational AI platform that integrated multiple scientific data sources, enabling scalable model inference. Architected containerized multi-agent ML workflows using modern technologies, significantly improving deployment efficiency.
Data Science Intern
DecisionTree Analytics & Services Pvt. Ltd.
May 2025 - July 2025 (2 mo) · null
Created end-to-end machine learning workflows for Marketing Mix Modeling, including data preprocessing and deployment through a Streamlit platform. Designed and evaluated various recommendation architectures, contributing to improved customer behavior prediction.
Education
Plaksha University
B.Tech, Computer Science & Artificial Intelligence
2022 - 2026
CGPA: 8.43
Lakshmipat Singhania Academy
12th CBSE, Science
2020 - 2022
Percentage: 89%
Lakshmipat Singhania Academy
10th CBSE
2018 - 2020
Percentage: 96.2%
Skills
PythonC/C++JavaScriptReactTypeScriptHTMLCSSSQLMATLABPyTorchTensorFlowStreamlitLangChainLangSmithModel Context Protocol (MCP)FastAPIDockerGoogle Cloud RunREST APIsGitCI/CDLinuxModel EvaluationData ScienceAnalytical SkillsFigmaCanvaVideo EditingWordPressMicrosoft Office Suite
Projects
Brain Injury Detection and Segmentation
Built an automated ML pipeline for brain injury classification and segmentation across six injury types, achieving state-of-the-art performance with a test accuracy of 99.74%.
Music Genre and Sentiment Analysis using ML
Designed an end-to-end ML pipeline for music genre classification and sentiment analysis, implementing various algorithms and achieving 71% accuracy with Random Forest.
Volunteering
Head of Travel and Stay Team
ConfAI
Sept 2025 - Nov 2025
Lead of Communications and Content Team
Kartavya (Social Service Club)
Sept 2024 - Aug 2025
Event Incharge, exe.BIT Fest
Lakshmipat Singhania Academy
Aug 2020 - Oct 2020
Member, Cultural Committee
Lakshmipat Singhania Academy
Apr 2019 - Mar 2020, Apr 2021 - Mar 2022
Event Incharge
exe.BIT Fest, Lakshmipat Singhania Academy
Aug 2020 – Oct 2020
Member
Cultural Committee, Lakshmipat Singhania Academy
Apr 2019 – Mar 2020, Apr 2021 – Mar 2022