Computer Vision & Deep Learning Enthusiast

Python developer with expertise in machine learning and computer vision. Proficient in backend development, automation, and creating realworld tools using FastAPI, OpenCV, and MediaPipe. Currently exploring ML frameworks such as PyTorch and TensorFlow to implement theoretical knowledge in practical applications.

Technical Skills

• Languages & Scripting: C, Python, JavaScript, Java
• Framework & Libraries React, Tailwind CSS, FastAPI, Next.js, Flask, OpenCV, scikit-learn, pandas, numpy, matplotlib
• Tools & Platforms Linux, GitHub, Git
• Databases Supabase, Firebase

Work Experience

OpenAstronomy — Contributor @ SunPy Project (Jan 2025 – Feb 2025)

• Resolved a critical bug in SunPy’s SRSClient by replacing outdated NOAA FTP endpoints with HTTPS, restoring 100% CI/CD pass rate across 30+ builds weekly.
• Coordinated with NOAAAPI maintainers to verify updated links, reducing future API breakage risk by 80%.
• Enhanced data reliability for 1,000+ monthly users and downstream scientific tools by merging code into SunPy’s core codebase.
• Fixed UI layout issues on OpenAstronomy.org, enhancing footer responsiveness, theme consistency, and visual flow across 10 pages.

Education

• Bachelors of Technology in Computer Science

  Techno India University (September 2029)

• High School Diploma, CS

  National English School (March 2024)

Projects

whispercast (March 2025 - April 2025)

GitHub | Website

• Built an AI-powered CLI tool for generating podcasts and audiobooks using Python, reducing manual content prep time by ~80%.
• Automated script creation via OpenAI LLMs and text-to-speech conversion using Coqui-TTS, enabling end-to-end audio generation in under 15 seconds.
• Integrated Wikipedia, Google News, and Reddit APIs into the AI podcasting tool, delivering real-time, topic-specific content updates for each audio segment and improving content freshness by 99%.
• Designed an interactive learning mode that let users query PDFs and Docs, increasing engagement by approx. 2x in test runs.
• Reduced file clutter by auto-managing playback files and temporary content, keeping storage usage under ~50MB per session.

melody.cli (May 2024 - Jun 2024)

GitHub | Website

• Created a terminal-based music player with ~0.5s average latency from command to playback.
• Integrated a smart caching system that reused previous downloads, cutting network usage by up to 60% across sessions.
• Designed for devs and low-resource systems, keeping RAM usage below 100MB even during continuous playback.
• Tested with 50+ tracks across genres to validate consistency and fault tolerance of autoplay queue logic.

meta-input (Feb 2023 - May 2023)

GitHub

• Built a gesture-based controller using OpenCV + MediaPipe that replaced traditional inputs with hand gestures, achieving ~90% gesture recognition accuracy.
• Enabled full mouse control, volume/brightness adjustment, and air typing with minimal latency (~1s response on average hardware).
• Tuned system to maintain stable tracking at 30 FPS, even in medium-light conditions, improving UX consistency.
• Reduced user reliance on peripherals by offering hands-free operation for basic OS tasks — tested successfully over 20+ live sessions.