Hello!
I'm a fourth-year undergraduate at Rutgers University studying Physics and Computer Science. My primary research interest is Martian paleomagnetism and impact processes. I also like rock climbing :)
Contact me: zain.eris.kamal@rutgers.edu.
Here are summaries/links to my repositories:
RedPlanet — A Python package which provides accessible, easy-to-use, and out-of-the-box tools for working with various Mars geophysical datasets. Examples include:
- Crustal heat flow & Curie depth calculations from gamma-ray spectroscopy (GRS) data.
- Digital elevation models up to 200m resolution, with parallelization/chunking for high-performance.
- Crater database which unifies [1] Robbins & Hynek 2020 database of craters D>=1km, [2] Robbins, Hynek, Lillis, & Bottke 2013 age-modeled craters via isochron-fitting, and [3] official IAU crater names/nomenclature up-to-date.
- Custom crustal thickness models based on Weiczorek's "InSight Crustal Thickness Archive" (~23K options parameterized by any north/south crustal density, 16 reference interior models, and any crustal thickness at InSight)
- MAVEN magnetometer data, filtered for nighttime and low-altitude (COMING SOON).
Expected v1 release in January 2025 or earlier.
Mars Geophysics — Rutgers Dept. Planetary Sciences
- Investigating the depth/formation/timing of crustal magnetic sources and implications for history of the Martian dynamo via impact craters. Mentored by Professor Lujendra Ojha.
High Energy Physics, Muon Scattering — Rutgers Dept. Physics/Astronomy
- Performing analysis/software development for the MUon Scattering Experiment (MUSE) group to investigate the proton radius puzzle. My primary contribution was developing a fast calorimeter simulation framework with Generative Adversarial Networks. Mentored by Professor Ronald Gilman.
Atmospheric/Solar Physics — NJIT Dept. Solar Physics
- Analyzed cloud-radiation feedback systems during hurricanes with new BBSO Earthshine solar reflectance data. Mentored by Professor Andrew Gerrard.
Physics Simulations with VPython
- Interactive simulations of the N-body problem, Rutherford scattering, magnetic vector fields, etc.
- Analyzing Solar System orbits using NASA’s SPICE library.
Searching for Exoplanets with Lightkurve
- Analyzing Kepler/TESS time series data for star brightness in search of transits.
Asteroid Spectra Classification with Machine Learning
- Training multi-class Support Vector Machines (SVMs) to classify asteroid spectra.
Integrated Water Hardness Meter
- MVP for a device that homeowners can install and use to monitor water hardness trends in pipes.
Learn Data Analysis with Python
- We run a cluster for the Rutgers Physics department. This is one of our Spring 2023 workshops on learning basic data analysis with Python.