I’m Mandar Mahesh Bhat, an Artificial Intelligence & Data Science undergraduate at M. S. Ramaiah Institute of Technology, focused on building practical software systems that combine AI/ML, data, and modern application engineering.
My experience spans end-to-end AI systems, full-stack web applications, cross-platform mobile development, NLP, real-time systems, and data analytics. I enjoy taking an idea from architecture and implementation through to a usable product.
I’m particularly interested in:
- Software Engineering — scalable application architecture, APIs, real-time systems, and product development
- AI / Machine Learning — NLP, predictive analytics, sentiment analysis, model evaluation, and applied AI
- Full-Stack Development — React, TypeScript, Flask, Node.js, MongoDB, REST APIs, and WebSockets
- Data Science — EDA, feature engineering, statistical analysis, visualization, and predictive modeling
- Product Engineering — solving real-world problems with practical, user-focused technology
AI/ML Internships · Software Engineering Internships · Full-Stack Development · Data Science · Open Source · Research & Engineering Projects
AI / Data: Scikit-learn · TensorFlow · Pandas · NumPy · Matplotlib · Seaborn · NLP · OpenCV · DeepFace · ChromaDB · Streamlit
Engineering: REST APIs · WebSockets · Socket.IO · JWT · MERN Stack · Flutter · Dart
| Domain | Proficiency | Details |
|---|---|---|
| Machine Learning | Intermediate | Scikit-learn, predictive analytics, model evaluation |
| Natural Language Processing | Intermediate | NLP pipelines, text processing, fuzzy matching, language rules |
| AI Systems | Intermediate | Modular AI assistants, memory systems, LLM integration |
| Computer Vision | Intermediate | OpenCV, OCR, face matching, identity verification |
| Data Science | Intermediate | EDA, feature engineering, statistical analysis, visualization |
| Model Evaluation | Intermediate | Precision, Recall, F1-Score and analytical evaluation |
| Generative AI | Developing | LLM-powered applications and AI-assisted analytics |
| Real-Time AI Applications | Developing | Event-driven systems, live analytics and interactive AI workflows |
🚗 CampusPool — AI-Powered Campus Carpooling Platform
A full-stack campus carpooling platform combining geolocation, graph algorithms, identity verification, authentication, and real-time communication.
| Category | Details |
|---|---|
| Stack | Flutter · React · TypeScript · Flask · MongoDB · OpenCV · DeepFace |
| Scale | End-to-end mobile + web + backend architecture |
| Performance | Dijkstra shortest-path matching + greedy passenger-rider matching |
| Security | JWT authentication · OCR · Face Matching · Identity Verification |
| Impact | Streamlines campus ride discovery and passenger-rider matching |
| Repository | GitHub |
- Built a Flask + MongoDB backend supporting a Flutter mobile application and React + TypeScript web client.
- Implemented geolocation-based ride matching using Dijkstra’s shortest-path algorithm.
- Added greedy passenger-rider matching and clustering techniques.
- Integrated OCR-based ID verification using
pytesseract. - Implemented face matching using DeepFace.
- Added JWT authentication and real-time communication using Socket.IO.
🎯 FocusTracker Pro — Real-Time Distraction Detection
A real-time productivity system that identifies whether active desktop applications are study-focused or distracting, with a live analytics dashboard.
| Category | Details |
|---|---|
| Stack | Python · Flask · React · TypeScript · Socket.IO · WebSockets |
| Scale | Desktop monitoring + real-time web dashboard |
| Performance | Event-driven real-time activity classification |
| Security | Backend API architecture + real-time communication |
| Impact | Provides live productivity insights and distraction alerts |
| Repository | GitHub |
- Built a distraction-detection system using
win32guito classify active windows. - Developed a Flask + Socket.IO backend.
- Created a React + TypeScript analytics dashboard.
- Implemented live analytics, alerts, and SMS notification workflows.
- Used WebSockets for real-time application updates.
🧠 Empathetic AI UX — Empathy OS
A modular AI assistant designed around emotion-aware interaction, long-term memory, multimodal inputs, and personalized responses.
| Category | Details |
|---|---|
| Stack | Python · NLP · LLM · ChromaDB · Streamlit · Voice |
| Scale | Modular AI assistant architecture |
| Performance | Persistent vector-based memory retrieval |
| Security | Modular component architecture |
| Impact | Context-aware and personalized AI interactions |
| Repository | GitHub |
- Built modular components for emotion detection, LLM responses, memory, PDF parsing, and voice I/O.
- Integrated ChromaDB for long-term memory.
- Enabled personalized, context-aware responses across sessions.
- Designed the application as an extensible AI assistant rather than a single-purpose model.
📝 Kannada Word Processor
A Kannada-focused text processing system implementing spell checking, compound-word detection, Sandhi rules, Vibhakti analysis, and fuzzy matching.
| Category | Details |
|---|---|
| Stack | Python · NLP · Fuzzy Matching · Custom Datasets · CLI · GUI |
| Scale | Kannada language-processing application |
| Performance | Rule-based processing + fuzzy word matching |
| Security | Local processing architecture |
| Impact | Practical NLP tooling for Kannada text processing |
| Repository | GitHub |
- Implemented Kannada spell-checking and compound-word detection.
- Developed rule-based Sandhi processing.
- Added Vibhakti analysis.
- Implemented fuzzy matching for intelligent word suggestions.
- Provided both CLI and GUI interfaces.
- Added automated tests for core processing functionality.
📱 Flutter Internship Application
A cross-platform mobile application developed during a Flutter training program with Firebase integration.
| Category | Details |
|---|---|
| Stack | Flutter · Dart · Firebase |
| Scale | Cross-platform mobile application |
| Performance | Native cross-platform application architecture |
| Security | Firebase-backed application services |
| Impact | Hands-on mobile engineering experience |
| Repository | GitHub |
- Built a cross-platform mobile application using Flutter and Dart.
- Integrated Firebase services.
- Applied mobile application architecture and UI development practices.
Forage · 2025
Completed a software engineering virtual experience focused on debugging Python applications and building data visualization interfaces.
- Fixed broken Python scripts.
- Worked with JPMorgan's Perspective library.
- Built a live data feed.
- Developed graph visualization functionality.
- Practiced debugging and software engineering workflows.
Python Data Visualization Debugging Perspective
Forage · 2025
Completed a simulated client analytics engagement involving forensic data analysis and reporting.
- Performed forensic data analysis.
- Worked with equality-score reporting.
- Built dashboards for a simulated client engagement.
- Applied analytical reasoning to business data.
Python Data Analytics Dashboarding Data Analysis
Forage · 2025
Completed a virtual experience focused on using generative AI to improve data storytelling and insight-generation workflows.
- Applied generative AI tools to analytical workflows.
- Explored AI-assisted data storytelling.
- Generated insights from business-oriented data.
- Applied GenAI concepts to practical analytics scenarios.
Generative AI Data Analytics Data Storytelling
| Recognition | Details |
|---|---|
| Kannada NLP Project | Built a Kannada Word Processor implementing language-processing features including Sandhi, compound-word detection, fuzzy matching, and Vibhakti analysis |
| JPMorgan Chase & Co. | Completed Software Engineering Virtual Experience through Forage |
| Deloitte | Completed Data Analytics Virtual Experience through Forage |
| Tata Group | Completed GenAI-Powered Data Analytics Virtual Experience through Forage |
| Flutter Development | Completed cross-platform Flutter mobile development training |
learning:
- Data Structures & Algorithms
- Advanced Machine Learning
- Natural Language Processing
- Software Engineering
- System Design Fundamentals
- Open Source Development
building:
- AI-powered applications
- Full-stack web systems
- Real-time applications
- Practical NLP systems
- Developer portfolio projects
exploring:
- Generative AI
- LLM applications
- Computer Vision
- Cloud & DevOps
- Production AI Engineering
- Open Source Contribution
open_to:
- AI/ML Internships
- Software Engineering Internships
- Full-Stack Opportunities
- Data Science Projects
- Open Source Collaboration
- Research & Engineering Projects