This website serves as a comprehensive showcase of my professional journey, technical skills, and open-source contributions in the geospatial and data science domains. It provides potential employers, collaborators, and the community with easy access to my work, projects, and expertise. I believe in transparency and sharing knowledge, which is why I've made my projects and learning journey accessible to everyone.

The AstroKundali project was one of my early Python learning adventures, specifically designed to master Object-Oriented Programming concepts. It represents my willingness to explore completely different subjects and cultures. From a technical perspective, it helped me understand complex mathematical calculations, astronomical algorithms, and cultural data structures. This project demonstrates that I'm not afraid to step outside my comfort zone and learn from diverse knowledge systems.

Absolutely not. I am a Data Scientist and GIS Engineer who developed a technical tool for generating astrological charts. My approach to the AstroKundali project was purely from a software development and cultural learning perspective. I focused on the mathematical and algorithmic aspects of chart generation rather than interpretations or predictions. I respect the cultural significance of astrology while maintaining my scientific approach to problem-solving.

Never. I have deep respect for all cultures and belief systems. Astrology, in its original form, was more about understanding personality patterns and human behavior rather than blind adherence to rituals or remedies. Many ancient civilizations used astronomical observations for practical purposes like agriculture and navigation. My project focuses on the technical and mathematical aspects of chart generation, treating it as a fascinating intersection of astronomy, mathematics, and cultural heritage. I believe in approaching different knowledge systems with curiosity and respect, not mockery.

Open-source development aligns with my belief in democratizing technology and knowledge sharing. Through my PyPI packages and QGIS plugins, I aim to solve real-world problems and make geospatial tools more accessible to researchers, students, and professionals. Each contribution represents a learning opportunity and a way to give back to the community that has supported my growth. I believe that sharing knowledge multiplies its value.

I approach every project with respect for the cultural context it operates in. Whether working with traditional knowledge systems like astrology or modern satellite data analysis, I maintain a learner's mindset. I focus on understanding the underlying principles, mathematical foundations, and practical applications rather than making judgments about belief systems. This approach has enriched my perspective and made me a more well-rounded developer and data scientist.

I believe in hands-on learning through practical projects. Whether it's mastering PySpark for satellite data processing or understanding Swiss Ephemeris for astronomical calculations, I dive deep into the subject matter. I combine theoretical knowledge with practical implementation, often creating tools or packages that solve real problems. This approach has helped me successfully transition between different domains while maintaining technical depth.

Quality is paramount in all my projects. I follow best practices including comprehensive documentation, unit testing, version control, and continuous integration. Each PyPI package and QGIS plugin undergoes thorough testing before release. I actively maintain my projects, respond to user feedback, and continuously improve based on real-world usage patterns. User experience and reliability are my top priorities.

I'm excited about the intersection of AI and geospatial technologies. My current focus includes developing more sophisticated satellite data processing pipelines, exploring generative AI applications in geospatial analysis, and contributing to climate change solutions through technology. I'm also working on expanding my open-source contributions and potentially pursuing research opportunities in environmental monitoring and sustainable development.