I am Rawan, a senior student at Nile University in Egypt, specializing in Artificial Intelligence. Currently, I am employed as a part-time Junior ML Engineer at VAIS Company, where I contribute to the implementation of AI solutions in agriculture utilizing satellite imagery.

I am skilled in ML using GIS data. My expertise lies in satellite data analysis, particularly with hyperspectral data from Enmap, Prisma, EO-1 Hyperion (from NASA) satellites, multispectral data such as Sentinel-2 and Landsat-8, Open Soil Spectral Library (OSSL) database. I possess hands-on experience in NIR and SWIR data preprocessing and smoothing techniques, alongside proficiency in atmospheric correction methods for Landsat-8 and Sentinel-2 fusion, and spectral unmixing of data from PlanetLabs.I also have experience in dealing with Google Earth Engine APIs.

In my journey, I have adeptly utilized Python libraries for satellite data processing, including rasterio, pyproj, and gdal, along with data analysis libraries such as pandas, numpy, and scipy. Additionally, I have honed my skills in machine learning frameworks such as PyTorch and scikit-learn.

Currently, I am engaged in two significant projects:

Now I am working on 2 Projects:

1. Sentinel-2 multispectral data enhancement (Super-Resolution) using GANS as a part of my graduation project.
2. "PatchDrop: Adaptive High-Resolution Data Usage for Cost-Effective Image Processing" using images from sentinel satellites.

I am happy to contribute to this project.

I am Rawan, a senior student at Nile University in Egypt, specializing in Artificial Intelligence. Currently, I am employed as a part-time Junior ML Engineer at VAIS Company, where I contribute to the implementation of AI solutions in agriculture utilizing satellite imagery.

I am skilled in ML using GIS data. My expertise lies in satellite data analysis, particularly with hyperspectral data from Enmap, Prisma, EO-1 Hyperion (from NASA) satellites, multispectral data such as Sentinel-2 and Landsat-8, Open Soil Spectral Library (OSSL) database. I possess hands-on experience in NIR and SWIR data preprocessing and smoothing techniques, alongside proficiency in atmospheric correction methods for Landsat-8 and Sentinel-2 fusion, and spectral unmixing of data from PlanetLabs.I also have experience in dealing with Google Earth Engine APIs.

In my journey, I have adeptly utilized Python libraries for satellite data processing, including rasterio, pyproj, and gdal, along with data analysis libraries such as pandas, numpy, and scipy. Additionally, I have honed my skills in machine learning frameworks such as PyTorch and scikit-learn.

Currently, I am engaged in two significant projects:

Now I am working on 2 Projects:

1. Sentinel-2 multispectral data enhancement (Super-Resolution) using GANS as a part of my graduation project.
2. "PatchDrop: Adaptive High-Resolution Data Usage for Cost-Effective Image Processing" using images from sentinel satellites.

I am happy to contribute to this project "Astronomical data enhancement with DL".

Each year the Astronomical Data Analysis and Software Systems (ADASS) scientific organizing committee requests nominations for the annual software prize and each year I nominate Richard White and Perry Greenfield at STScI. Without their foresight, planning and project management during the early days of its development, Python would not be the predominant programming language in astronomy or science in general. Please help me in getting them this award by going to the following link and giving "Python for Astronomy" an up vote. It has been over 25 years and I believe that it is well past time that they receive this award.

https://www.tricider.com/admin/2RbDHdEp4d3/EFh7uDjfxt5

In reply to @DavidPS:matrix.org

Each year the Astronomical Data Analysis and Software Systems (ADASS) scientific organizing committee requests nominations for the annual software prize and each year I nominate Richard White and Perry Greenfield at STScI. Without their foresight, planning and project management during the early days of its development, Python would not be the predominant programming language in astronomy or science in general. Please help me in getting them this award by going to the following link and giving "Python for Astronomy" an up vote. It has been over 25 years and I believe that it is well past time that they receive this award.

https://www.tricider.com/admin/2RbDHdEp4d3/EFh7uDjfxt5

Hi Open Astronomy, I'm Ying, a senior undergraduate in Monash University, Australia, majoring in computer science and geo-science.

I have experience working in a student rocket team(yep it's pretty cool), where I was responsible for conducting dynamic simulations and predicting rocket trajectories, as well as maintaining a student-developed software called Saturn. Therefore, I have a strong sense of teamwork and extensive experience in open-source projects. Last semester, I took an astronomy unit, and the feeling of not being alone in the vast universe fascinated me. Combined with my strong interest in space and spacecraft, I immediately chose Open Astronomy when browsing GSoC projects. The two following projects attract me so much:

1. Common API for large molecular databases

2. Solar Eclipse analysis with sunpy

I am looking forward to contributing to the open-source community and exploring the secrets of the universe for the benefit of all. I am proficient in Python, Java, TypeScript, as well as Oracle and MongoDB databases, but I believe Python is more needed for our purposes here. Since I became aware of GSoC relatively late, I hope that I have enough time to submit my proposal before April 4, so I need some advice on how to get started as soon as possible. Is there anyone willing to help me? That would be so helpful! 🥹

Here are two questions I couldn't find answers to on the websites of GSoC and OpenAstronomy. I'll be glad if someone could help:

1. Is the proposal about my own plan for executing the project? However, without prior experience with OpenAstronomy, it would require lots of effort to familiarize myself with it, including code reading and such stuff, possibly taking one or two weeks. Should I undertake this before the proposal, or can I include it in the proposal as part of my overall project?

2. How can I determine how competitive my project is? How do mentors evaluate whether a proposal is good or not good? Because there are hundreds of students applying for one project, and if they are not very familiar with the project code, their proposals might be similar. For example, initial project understanding and small application tests, mid-term checks, etc. How do mentors consider these? What are the points that you think is important for a proposal?

Thank you so much😃