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Implement distributed Dask arrays for generating true-color Rayleigh-corrected aerosol storm imagery in real time.

Implement automated demodulation routines in GNU Radio for CubeSat telemetry downlinks in UHF and S-band frequencies.

Add general relativistic acceleration perturbations and non-spherical solar radiation pressure drag models for deep space probes.

Optimize peer-to-peer micro-chunk distribution for petabyte-scale scientific application software repositories.

Implement GPU-accelerated non-equilibrium line-by-line spectral synthesis for high-temperature exoplanetary atmospheres.

Build fast PyOpenCL filtered back-projection (FBP) reconstruction filters for high-speed material science beamline measurements.

Build real-time MQTT 5.0 push notifications and GeoJSON trajectory streams for tracking orbital environmental sensors.

Build a mobile-first catalog of active scholarships, GSoC roadmaps, and interview preparation materials.

Simulate electrochemical Li-ion battery degradation cycles over 15-year orbital lifetimes under cyclic orbital eclipses.

Implement 3D tetrahedral adaptive remeshing routines for spacecraft heat-shield reentry thermal simulations.

NeoRoo currently talks to DHIS2 through raw HTTP calls with no offline support, so if a nurse loses connectivity while entering baby data, that data is just gone. I'm proposing to integrate the d2 Android SDK as the primary sync engine and build a Flutter abstraction layer on top of it that works across both Android and iOS. The main deliverables are: a Pigeon-based platform bridge to d2 (Android) and DHIS2 REST API (iOS), an offline-first sync queue using Drift/SQLite with automatic retry, a server-wins conflict resolution system with a review log, real-time sync status indicators in the UI, background sync with battery optimization, push notifications for server-side changes, and a testing + monitoring toolkit. By the end, healthcare workers should be able to use NeoRoo reliably regardless of connectivity.

This project aims to implement a WESTPAParser and a WESTPAReader in WESTPA which will expose WESTPA’s HDF5 Framework simulation data as a standard MDAnalysis Universe. Currently, users are required to write extensive boilerplate code to manually navigate the HDF5 simulation data via WESTPA’s w_crawl before any structural observables can be computed. This project replaces that manual process by allowing users to obtain an MDAnalysis Universe directly from a west.h5 simulation file. This native integration will be accessible through both a Python API and a new w_mdacrawl CLI tool, serving as a high performance drop-in replacement for existing workflows. The project will also allow users to use MDAnalysis’s AnalysisBase backend to perform analysis using parallelization. Furthermore, the project will also implement a method to save the resulting analysis results back into the HDF5 framework as auxdata. This will ensure that any computed properties remain compatible with the broader WESTPA ecosystem for use in future simulations or downstream analysis tools like w_ipa.

Time series forecasting is paramount in many domains, including finance, healthcare, energy, and climate science. This project suggests incorporating deep learning-based forecasting models—Informer, TCN, and DeepAR—into the aeon/tookit. The objectives are to construct an efficient and scalable framework for forecasting that accommodates top-performing models, is compatible with Aeon’s data management, and provides stable training, evaluation, and documentation. Through simplifying the availability of advanced forecasting software, the project would make it easier to utilize the toolkit to assist researchers with streamlined time series analysis.

This proposal seeks to extend the build system in Clang's driver to natively support module-based builds by leveraging Clang's existing support for scanning C++20 module dependencies between source files and adding support for generating the appropriate build steps.

FreeBSD's UFS is arguably the longest standing UNIX file system still under active development. It is well documented and has many interesting features. While UFS has been ported to Linux and Mac OSX, the ports are not very good or have been deprecated. Using fusefs as a userland option would let the filesystem be used on many other systems.

This project aims to develop a suite of command-line interface (CLI) modules tailored for Linux environments, enabling automation of common Google Groups operations. These modules, predominantly in sh, Perl, and Python, will leverage various Google APIs to facilitate tasks seamlessly. Primarily, the tool will serve as a bridge between Little Green Light (LGL), the organisation's central contact management system, and Google Groups. By integrating with LG's daily reports, the tool will enable automatic updates to Google Groups based on constituent data changes. This ensures that Google Groups remain synchronised with the single source of truth provided by LGL.

Training intricate machine learning models to achieve the desired level of proficiency can be time-consuming and require high computational resources. These challenges restrict the utilization of highly complex models in mlpack. To tackle this issue, one solution is to utilize pre-trained models available in the ONNX format. ONNX offers a standardized method for developers to define and exchange deep learning models across various frameworks like TensorFlow, PyTorch, and more.

The problem here is to migrate from gitbook to some other tool which provides us with the feature of generating website from some easy to use markup language like markdown in which the current gitbook is hosted. So, I propose to solve this using antora for website and using asciidoc as markup language for it as it fulfills the main requirments of having a website and ebook(epub). It also have option to customise the UI which could be used to make antora website look more attracting and I have listed why I used this in my proposal.

ENIGMA currently lacks third-party integration with various digital distribution platforms such as Steam, Xbox, or Origin. First-class support for these services would make it easier for Indie developers to publish ENIGMA-created games. Developers would like for it to be easier to monetize their games and enable them to release bigger and better updates to their users. An integrated architectural layer will be created between Steamworks ENIGMA's extension APIs and Steamworks SDK. ENIGMA's Asynchronous system will be updated. Currently, ENIGMA's Networking system is not stable so Steam Networking features will be postponed for later for now I will add support to these APIs: Management, General, Overlay, Leaderboards, Achievements, Cloud, and Social.

The Audio Overlay Filter aims to provide the functionality of replacing specified sections of an audio stream with other input audio streams. I will be designing and implementing the filter along with the necessary documentation for it to become a part of FFmpeg's libavfilter library.

This project integrates mfsBSD into the FreeBSD release tool set, creating an additional target of mfsBSD images (.img for disc and .iso for optical images) into the `/usr/src/release/Makefile`. Until now, mfsBSD only existed outside the FreeBSD release tool chain, and only the -release versions have been produced. With this project, mfsBSD images are now available at the official FreeBSD release page, and you can also build mfsBSD yourself by invoking `cd /usr/src/release && make release WITH_MFSBSD=1`, which will then create `mfsbsd-se.img` and `mfsbsd-se.iso` at `/usr/obj/usr/src/${ARCH}/release/`.

enviroCar Mobile is an Android application for smartphones that can be used to collect Extended Floating Car Data. The app communicates with an OBD2 Bluetooth adapter while the user drives. This enables read access to data from the vehicle’s engine control. The data is recorded along with the smartphone’s GPS position data.The driver can view statistics about his drives and publish his data as open data. The latter happens by uploading tracks to the enviroCar server, where the data is available under the ODbL license for further analysis and use. The data can also be viewed and analyzed via the enviroCar website.

Agora android application runs smoothly and works fine with all the functionalities. This summer I am planning to implement CI/CD pipeline to automate android release. As recently android 12 has been launched so I am going to make changes to our splash screen by giving it some animation. And I will also make our placeholders according to android 12. I am also going to update our material design libraries with material3.0. In this, I will first make our bottom navigation bar according to material 3.0. I have also added a few bugs and optimizations In my proposal so I will also work on that. And I am going to add new features for creating a poll. For doing this first I will add a welcome screen for the poll also. I will also do improvements in our election result sharing implementation so that users can share it with visualization. And after that, I am going to write down implementations for the remaining ballots. I will write our code according to MVVM architecture. I will work on a Test-Driven-Development environment and Write Unit tests for all the business logic implemented.