Dr. Masoom Jethwa
Planetary Scientist | Computational Physicist | Open source advocate
Planetary Scientist | Computational Physicist | Open source advocate
Hi, I'm Masoom – a Planetary Science Researcher, Open Source Advocate, and Python enthusiast. I completed my PhD in Planetary Atmospheres and am always looking for collaborations and research opportunities. I specialize in observational astronomy and planetary systems analysis, with expertise in computational methods for space science research.
Advancing educational research, curriculum design, AI-enabled learning, and astronomy education. I create physical and digital teaching materials grounded in empirical research, with a focus on equitable, inclusive, and community-driven impact for underprivileged learners and educators.
Visualizing academic reach and contribution to planetary science.
Physics of upper-atmospheric emissions from space- and ground-based observations.
Modeling planetary atmospheres, dynamics, and chemistry—extending to exoplanets.
Algorithm-driven analysis of NASA, ESA, ISRO, and JAXA mission data.
High-performance workflows combining numerical methods, visualization, and machine learning.
Open-source advocacy, mentoring, and computational literacy in planetary science.
Interactive and statistical tools to extract insight from complex astronomical data.
Bridging complex research and global knowledge through accessible, cross-platform content.
Architecting reproducible code for atmospheric science. I share technical deep-dives on transforming raw mission telemetry into scientific insights using Python and high-performance computing.
Translating complex astrophysics into accessible research. These articles explore the intersection of data science and orbital research, covering NASA/ESA mission data and the future of space exploration.
Connecting space technology with society. A curated repository of educational resources, from planetary cycles and Venusian studies to community-based STEM activities for the next generation.
A comprehensive technical stack spanning systems programming, data intelligence, and scientific computing.
Core languages for systems and scientific development.
Data handling, analysis, and visualization stack.
Higher-level AI capabilities and applied intelligence.
Visual data processing and image intelligence.
Structured data storage and querying.
Performance, simulations, and scalable computation.