I'm a Software Developer and AI enthusiast interested in building practical software systems, exploring machine learning, and applying intelligent technologies to real-world problems.
- 🤖 Artificial Intelligence and Machine Learning
- 🧠 Large Language Models, RAG systems and AI agents
- 💻 Full Stack Application Development
- 🌍 Geospatial AI and remote-sensing data analysis
- 🔬 Research, experimentation and open-source development
- ⚙️ Software engineering, APIs and data-driven applications
I use my repositories to document implementations, experiments, project development and collaborative work.
The badges below are technology labels, not proficiency ratings. Hover over a badge to see its name. They are deliberately not wrapped in links.
Keep only technologies you have actually used or are actively exploring. Verify the list against your code before publishing.
Project descriptions below preserve your original project list. Confirm each repository and implementation before treating the listed features as completed.
AI-powered Urban Heat Intelligence Platform
GeoPulse AI focuses on geospatial data and AI-assisted analysis of urban heat patterns to support climate-aware decision-making.
Areas of work
- 🗺️ Geospatial data visualization
- 🌡️ Urban heat analysis
- 📡 Environmental data processing
- 🤖 AI-assisted insights
Technologies: Vue.js Leaflet Python AI/ML
AI-powered Nutrition Assistant using LLMs and RAG
A conversational AI project focused on contextual nutrition information using language models and retrieval-augmented generation.
Areas of work
- 🧠 Conversational AI
- 📚 Knowledge retrieval
- 🔎 RAG pipeline
- ⚡ Contextual responses
Technologies: Python FastAPI Gemini RAG
Smart Expense Tracking Application
A mobile application concept for personal expense tracking and financial management.
Areas of work
- 💰 Expense tracking
- 📊 Financial summaries
- 🔐 Authentication
- 🔔 Notifications
Technologies: Flutter Spring Boot MySQL
Machine Learning for Geological Prediction
A machine learning project focused on wellbore and geological prediction using structured data.
Areas of work
- 📈 Predictive modelling
- 🧠 Machine learning
- 📊 Data analysis
- ⚙️ CatBoost experiments
Technologies: Python CatBoost Machine Learning
Repository: ROGII Wellbore Prediction
Conversational AI Recommendation Engine
A recommendation-system project focused on semantic search and vector-based retrieval.
Areas of work
- 🔍 Semantic retrieval
- 🧠 Recommendations
- 📚 Vector search
- 🤖 Conversational interfaces
Technologies: FastAPI FAISS LLMs
Security Scanner and Certificate Analysis Platform
A project focused on inspecting TLS configurations and certificate information.
Areas of work
- 🔒 TLS configuration inspection
- 📜 Certificate analysis
- 🛡️ Security checks
Technologies: React FastAPI
These repositories are surfaced from my GitHub profile. Open each repository for its actual implementation, README, language breakdown and current development status.
| Repository | Source |
|---|---|
| TraceBack-AI | View repository |
| EasyLearning | View repository |
| ExploreAutomotiveAI | View repository |
| TraceForge | View repository |
| SysVerse | View repository |
| Morrow.ai | View repository |
| Orbit-Mobile | View repository |
| Velora.ai | View repository |
| verbatim-rag | View repository |
| ResearchPortfolio | View repository |
| Portfolio-AK | View repository |
| AI-CarVerse | View repository |
| neetcode-submissions | View repository |
| AgentOps-AI | View repository |
My open-source activity includes repository development, issue investigation, testing and pull-request work.
For example, verbatim-rag is a fork of KRLabsOrg/verbatim-rag. Contributions to the upstream project should be attributed to the relevant pull request and merge status rather than inferred from the fork alone.
The following cards retrieve public GitHub statistics through a third-party service. They may be cached, temporarily unavailable, or limited by API access. They are not a complete audit of contributions.
How to interpret the graphs
- The account card summarizes statistics available to the card service; it does not certify your engineering ability.
- The language card estimates language usage across eligible repositories. It does not establish proficiency or identify who wrote every line.
- The contribution calendar and PR pages on GitHub are the appropriate places to inspect actual activity and merge status.
- 🤖 AI agents and tool-using systems
- 🧠 Large Language Models
- 📚 Retrieval-Augmented Generation
- 🌍 Geospatial AI and remote sensing
- ⚡ Reliable AI applications
- ☁️ Cloud-native application development
AI & Machine Learning
|
+-- AI Agents
+-- Large Language Models
+-- RAG Systems
+-- Intelligent Automation
Software Engineering
|
+-- Full Stack Development
+-- REST APIs
+-- Enterprise Applications
+-- Cloud Systems
Research & Data Analysis
|
+-- Geospatial AI
+-- Remote-Sensing Data
+-- Machine Learning Experiments
+-- Model Evaluation
Building, testing, learning, and improving — one repository at a time.