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Problem: Traditional anomaly detection systems often struggle with limited data scenarios and can lack the ability to explain their detections. Addressing these challenges is crucial for advancing the field and expanding its application range. Solution: This project proposes the integration of Vision Language Models (VLMs) into the anomalib framework using OpenAI's API. The goal is to enhance anomaly detection capabilities through few-shot and zero-shot learning techniques. This integration involves creating a new model class, 'LVM_openAI', as a subclass of 'AnomalyModule', and incorporating unique parameters like API_key and custom prompts. The model will leverage OpenAI’s API for processing and interpreting data, and will handle error catching, response parsing, and anomaly detection. Methodology: The project will start with a deep dive into Anomalib and OpenAI’s ChatGPT API, followed by a design and prototyping phase. The development will be in phases, with each phase focusing on different aspects of the integration, including testing with various datasets (e.g., MVTec AD and LOCO) and comparing against other models. Additionally, a comprehensive documentation, including a detailed notebook for setting up and using the model, will be created. Deliverables: An integrated VLM-based anomaly detection system within anomalib. Complete documentation and a set of experiments demonstrating the efficacy of the approach. An optional user interface for enhanced model interaction.
PyTensor is a Python library that allows you to define, optimize/rewrite, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is based on Theano and integrates with NumPy, C/JAX/Numba, and has a tight API documentation. The project aims to integrate PyTorch as a new backend for PyMC, this would bridge the gap between the PyTorch and PyMC ecosystems. This integration will provide users with access to GPU hardware, enhance performance. Key deliverables include implementing a PyTorch Linker, creating dispatch functions for type conversion, and adding support for linear algebra, element-wise, and sparse operations in PyTorch. The goal is to establish a foundation for future contributions and foster community engagement, ultimately improving the accessibility and functionality of PyMC within the PyTorch ecosystem.
I aim to deploy OWTF on AWS for easier use by users and to ease its development for developers. Also, I will improve its Docker installation, which I have been working on. I also want to add a new plugin to scan the cloud storage of any web service according to the OWASP web security guide.
<p>The idea of playing games on the Liquid Galaxy has already been explored by some developers, there are currently two classic retro games that have been implemented: pong and snake, but there is no easy way to install and run these games on a Liquid Galaxy. By creating a basic app with icons representing each game any person with a tablet could easily control which game is being displayed on the screens and even quickly switch between them.</p> <p>Besides that, the Pac-Man game is another classic retro game that has been around or over 40 years and is one of the most famous of all time. What if there was a remake of the game for a more modern and multiplayer version on the Liquid galaxy to be included in this new app? Not only would it bring nostalgia to people all over the world, but also bring a lot of visibility to the Liquid Galaxy in a more fun and casual way.</p>
<p>The UI Migration project is an effort focused on generating the new component-based architecture with the integration of the APIs. To make the project more <strong>efficient</strong> and <strong>easily accessible</strong>, an entire code base shift from Symfony-Twig to React.js is proposed. React.js features an incrementally adaptable architecture that focuses on declarative rendering and component composition. React.js component system will enable us to organize the current working APIs appropriately.</p> <p>The main <strong>objectives</strong> of this project are:</p> <ol> <li>Working on good interactive design, with a modern look.</li> <li>Integrating the APIs to the new component-based UI structure.</li> <li>Seamless routing and page transitions.</li> <li>Giving the power of the node engine to our UI. Making all NPM accessible.</li> <li>Write appropriate documentation.</li> </ol>
<p>This project aims to validate the possibility of using pre-conditioners in compressing ROOT file formats (TTree and RNTuple); to understand how we can improve the functionality in the context of both lossy and lossless compression algorithms; and to investigate new BYTE_STREAM_SPLIT encoding.</p>
<p>Storing, sharing and accessing the vast volumes of data being generated in modern research and healthcare settings is extremely daunting. With the Data Repository Service (DRS) schema, the GA4GH has developed an API specification that provides access to data stored in the cloud, via a uniform experience. The DRS schema is part of the GA4GH Cloud Work Stream, which allows users to execute FAIR workflows on FAIR data in the cloud. However, it currently does not allow data to be dynamically added, which is a limitation to some use cases for federated computing.</p> <p>The goal of this project is to develop an open-source, generic (i.e., not tied to any specific data provider), distributable and highly reusable DRS microservice implementation with various, diverse and unique use cases in the operationalization of the GA4GH Cloud Work Stream, such as enabling user upload in client applications or on-site caching, temporary/intermediate storage functionality for execution endpoints and as a lightweight and maintainable demo service for GA4GH Cloud interoperability testing.</p>
<p>The aim of the proposal is to convert existing Grafana dashboard's static JSON files to Jsonnet files, which will help dynamically generate JSON as per requirement.</p>
<p>Develop an automated system that performs analyses on newly sequenced genomes.</p>
<p>LibreCores.org lists free and open source “IP Cores” on the website for the community to view and use. All listed projects are backed by a git repository. Currently, LibreCores.org websites extract the project README and LICENSE and render them on the project page, along with links to the project homepage and git repository.</p> <p>A user browsing for cores on LibreCores will be interested search for a specific category of projects to determine which projects will come under which classification. A user may want to search for a project through a list of projects. The indexing of all the IP Cores and Improving the search experience in LibreCores in terms of discoverability. The IP Cores details will be classified and indexed for making search experience better and more efficient.</p> <p>This project aims to add classification system for better categorization of a project and to implement a search engine for a better searching experience of projects on LibreCores.org.</p>
<p>The goal of this project is to further optimize the user interface. The structure of the overview pages shall be improved. For a better structure, the collected data shall be presented in own UI sections. Last but not least, the current Developer Statistics dialog will be moved to an Eclipse view.</p>
<p>Objective: To implement ‘the fast bilateral solver’ in OpenCV, which can be generally taken as an efficient bilateral filter.<br> To implement diverse tutorial examples with ‘the fast bilateral solver’, e.g. de-noising, colorization and stereo.</p> <p>Introduction: The bilateral solver is a novel algorithm for edge-aware smoothing that combines the flexibility and speed of simple filtering approaches with the accuracy of domain-specific optimization algorithms. This algorithm was presented by Jonathan T. Barron and Ben Poole as an ECCV2016 oral and best paper nominee. Algorithm details and applications can be found in <a href="https://arxiv.org/pdf/1511.03296.pdf" target="_blank">https://arxiv.org/pdf/1511.03296.pdf</a> [1]</p> <p>Significance: The naive bilateral filtering functions in OpenCV are generally computationally expensive and often insufficient for solving more challenging computer vision tasks. By contrast, the bilateral solver is 10-1000× faster than existing domain-specific approaches with comparable accuracy, and produces higher-quality output than lightweight filtering techniques with comparable runtimes.</p>
<p>The goal of this project is to develop and implement a scheme to verify a library crate's adherence to the semantic versioning specification in the Rust language. This would allow to simplify the process of stabilizing and releasing libraries on <a href="https://crates.io" target="_blank">crates.io</a>, as many mistakes can be automatically guarded against.</p>
<p>This project is focused on implementing methods to accurately compute the accurate standard errors of risk and performance measures in PerformanceAnalytics when asset returns that are non-normally distributed and/or serially correlated.. The project will leverage existing numerical standard error methods that exist in the “nse” package, but will also implement new methods based on the influence functions for risk and performance measures.</p>
<p>Implementing precise collection as a first step towards a better garbage collector.</p>
<p>Our objective is to determine the best architectural and parallelization options for the BLonD future C++ code base. Project includes:</p> <ul> <li>Existing simulations performance profile data and component interaction diagrams.</li> <li>Micro benchmark data selection for regional stress testing that can reveal of currently existing architectural pitfalls.</li> <li>Prototypes for potential architecture evolution that are exclusively designed for BLonD performance optimization covering wide amount of task and data parallelization technics: from local SMID optimizations and coprocessor kernels to cluster technics.</li> </ul> <p>Main project deliverable will be a report covering possible architecture directions rooted in profile data, performance tests and future possibilities. This report will include UML diagrams showing architectural blueprints for concurrency and parallelism directions, structured performance analysis of performed tests and created prototypes, a table comparing selected technologies in terms of:</p> <ul> <li>Top available simulation scale.</li> <li>Integration into current architectural model.</li> <li>Prototype testing results.</li> <li>Profiling tools.</li> <li>Publically available information and documentation.</li> <li>Hardware requirements.</li> </ul>
<p>Allowing users to run jobs on their own machines and submit the result.</p>
OWTF's current architecture has four systemic bottlenecks: workers that sit idle between single-task fetches, a FIFO scheduler with no priority or adaptive feedback, fragile plugin execution with no retry or timeout control, and an outdated tool ecosystem missing industry-standard scanners. This project replaces the flat task queue with a priority-based adaptive scheduler using a min-heap, where tasks are scored by plugin weight, risk factor, target priority, and a real-time feedback boost that re-prioritizes the queue when vulnerabilities are discovered. The worker model is upgraded with batch fetching, async pre-fetching, dynamic scaling, and target-affinity batching to eliminate idle gaps. A resilient execution harness adds configurable timeouts, retry with exponential backoff, subprocess isolation, and structured logging to every plugin run. Five modern tools are integrated using a self-contained plugin pattern: Nuclei, httpx, Subfinder, Katana, and ffuf. Deliverables: working adaptive scheduler, optimized worker pool, resilient plugin harness, five new tool plugins, HTML reporting with CVSS severity grouping, and comprehensive benchmarks showing measurable improvements in scan time and coverage.
The objective of this project is to develop an application that connects to a Liquid Galaxy installation. The application will be developed using Dart/Flutter and will be structured into two main components: a backend and a frontend. The CHE project offers a visual and interactive experience that allows users to explore different historical sites in a city or a country. In my case, the project is focused on the city of Lleida. The CHE project is developed on the Liquid Galaxy platform, where Google Earth is displayed continuously and synchronously creating a unified panoramic view. On top of this visualization, KML files are integrated to display information about the different historical places in the city, allowing users to easily locate and explore them in a simple and intuitive way.
I improved GNOME Crossword Editor's word suggestion algorithm, by re-implementing it as a forward-checking algorithm. Previously, our word suggestion algorithm only considered the constraints imposed by the intersection where the cursor is. This resulted in frequent dead-end word suggestions, which led to user frustration. To fix this problem, I re-implemented our word suggestion algorithm to consider the constraints imposed by every intersection in the current slot. This significantly reduces the number of dead-end word suggestions and leads to a better user experience. As part of this project, I also researched the field of constraint satisfaction problems and wrote a report on how we can use the AC-3 algorithm to further improve our word suggestion algorithm in the future. I also performed a competitive analysis of other crossword editors on the market and wrote a detailed report, to help identify missing features and guide future development.
This document proposes a detailed architecture on how to implement the Audio Switchboard API. This idea enables numerous features, including translation layers and lightweight breakout rooms, as described in the idea page. This proposal introduces a metadata-based mechanism to manage audio streams. The implementation involves extending jitsi-meet to handle metadata, and Jitsi Videobridge (JVB) to handle signaling from senders and filtering requests from receivers. Senders attach metadata to their streams, such as spoken language or breakout room identifiers, while receivers specify criteria for the streams they wish to receive. JVB processes these inputs, filtering and forwarding only the matching streams.
The "Superresolution for Strong Gravitational Lensing" project aims to enhance the resolution of astronomical images through advanced deep learning techniques. Gravitational lensing magnifies distant galaxies, offering insights into the universe's dark matter structure. However, the limited resolution of these images constrains our understanding. This project will develop superresolution models based on conditional diffusion models to transform low-resolution gravitational lensing images into high-resolution counterparts. These models will be tailored for astronomical data's unique challenges and integrated into the DeepLense framework for broader scientific use. Deliverables include a prototype superresolution model, integration tools and documentation for DeepLense, and comprehensive model development documentation. This effort will improve gravitational lensing image quality, aiding in the study of cosmic structures and dark matter.
The goal of this project is to enhance the speech recognition demo in Automotive Grade Linux by integrating Whisper AI for improved accuracy and expanding the natural language understanding (NLU) capabilities. Key Deliverables: Implement Whisper AI for speech-to-text conversion in both online and offline modes. Expand NLU to support more voice commands by integrating APIs like soundmanager, weather etc. Modify the existing Flutter app to accommodate the new features. Implement audible feedback for command execution. Potentially integrate voice control with other apps/services like navigation, phone, Wi-Fi (stretch goal).
The objective of this project is to design and implement a landing page for Pocket Paint on the Android Kotlin platform. The landing page will feature a gallery view where users can preview their saved images and quickly select one to continue editing or start a new drawing. By having a clear and organized landing page, users will have an intuitive and seamless experience with Pocket Paint. The landing page design will be inspired by the existing landing page in Pocket Code, ensuring consistency and familiarity for users. With the implementation of this landing page, Pocket Paint will become a complete app, providing a more comprehensive and efficient drawing experience.