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As an agent-based modeling (ABM) framework, Mesa is easy to use and applicable for a wide range of simulations. But traditional ABM agents rely on simple rules and patterns that are chosen by the users themselves, which can limit their adaptability. The objective of this project is to develop an extension of Mesa that give agents access to LLMs for reasoning, decision-making, and communication, that can be used not only for simulations, but also to study the impact of different paradigms and reasoning modules in ABM. The work involves designing a very modular LLM-agent API (with memory, reasoning, and tool-use components), that integrate with Mesa’s existing architecture (Model, Agent, Scheduler), as well as studying and solving LLM-related problems like memory management, consistency and computing-related challenges.
This proposal aims to design and implement a canonical meta-agent architecture for Mesa. The project addresses the current gap between Mesa’s experimental meta-agent support and the needs of users who want to model overlapping group structures such as households, workplaces, alliances, and teams. The work will focus on building a single canonical backend for representing overlapping typed memberships, along with a clean Mesa-facing API for creating groups, updating memberships, handling lifecycle operations, and supporting group-level state aggregation. The expected deliverables are a canonical backend, a user-facing API, lifecycle and aggregation support, tests for correctness and overlapping memberships, and documentation with example-driven validation. The result will be a stronger foundation for multi-level modeling in Mesa and a better base for future group-level extensions.
<p>Polly is a high-level loop and data-locality optimizer and optimization infrastructure for LLVM based on the polyhedral model. This project aims to implement a mechanism of static expansion in Polly in oder to parallelize loop that can not be directly parallelized because of data dependencies.</p>
<p>The project is to improve ASCEND canvas GUI such that it is easier to use for public. In detail, tasks include creating usable simulation models, improving ASCEND language, adding load/save and undo/redo functions, and debugging for current ASCEND, etc.</p>
mesa is renowned as the premier Python framework for agent-based modeling, combining powerful functionality with ease of use. However, the framework's reliance on standard Python objects to represent agents poses scalability challenges, hindering performance as the number of agents grows. This limitation renders the execution of even modestly sized models, comprising a few thousand agents, impractical. The community has long requested a more performant version of mesa. While a refactor using Cython could address performance issues, it would introduce significant complexity and require users to adapt their methods to Cython, compromising Python's simplicity. The mesa-frames initiative proposes leveraging vectorized operations on dataframes, utilizing libraries such as pandas and polars, to enhance performance and scalability. This approach benefits from the optimized, out-of-the-box operations these libraries provide and their intuitive, well-documented APIs, which simplify custom agent creation.
<p>Currently, Polly’s performance is measured on PolyBench benchmark. PolyBench does not cover all of the possible kernels so we may miss out some kernels where a particular transformation does not perform well. This project will help to get new benchmarks for measuring Polly’s performance benefits. The benchmarks will be added to LLVM test suite.</p>
The Workflow Hardening of PEcAn project involves improving the existing integration testing framework by extending it to include a wider range of models, inputs, sites, and met within the integration tests, thus increasing system stability and ensuring more tests pass. It also involves improving the Status Board by adding more visualizations and fixing the existing issues.
This project is intended to improve the interoperability between LS‑DYNA and BRL‑CAD by enhancing the existing k‑g converter and by implementing a new g‑k converter. The primary goal is to facilitate a seamless data exchange between LS‑DYNA keyword files and BRL‑CAD geometry databases, ultimately streamlining workflows for users who need to transition between advanced simulation and detailed geometric modeling.
<p>The current visualization shiny apps of PEcAn 'Workflow Plot' and 'Global Sensitivity' is facing problems including instability and slow responsiveness.</p> <p>I suggest to improve stability and performance of apps by using lazy-loading to load large amount of model output data, improving performance of plots, caching plots within apps and improving app scalability with async programming.</p>
While filleting is a common and essential modeling technique, its implementation in existing mesh processing libraries is often limited or absent. This project aims to address this gap by developing a robust and efficient polygon fillet algorithm specifically for the Manifold library. The initial phase of the project will concentrate on the 2D domain, with the goal of providing a user-ready implementation. Future work will involve extending this algorithm to support 3D mesh filleting.
<h4>Project Goal:</h4> <p>Implement support for the 3MF file format in Slic3r and allow conversion into (AMF, OBJ, STL).</p> <p><strong>3MF</strong> is generally smaller than other comparable 3D formats where transforms and object references are supported.</p> <ul> <li>More about 3MF file format and its specification: <a href="http://3mf.io/" target="_blank">http://3mf.io/</a></li> </ul>
The project aims to incorporate AI features into Template Playground to facilitate the creation of Templates and Concerto models. The ability to generate Accord Project Templates from user submitted text will be implemented. Users will be able to chat with their chosen LLM and get an understanding of how the whole ecosystem of Accord Project works in tandem to produce agreements. The editors in Template Playground will be enhanced with the ability of providing AI powered inline suggestions.
<p>SBGNViz.js is an open source web application based on Cytoscape.js to visualize the pathway models represented by SBGN Process Description Notation . Its current version can visualize SBGN-PD maps and it is getting equipped with editor features. In this project, I propose to develop several key extensions to the editing capabilities of SBGNViz.js. Contributions that I propose to make are mentioned in a detailed way in the problem description section of my proposal.</p>
BEELINE is a bench marking tool that evaluates different methods and models that infer Gene Regulatory Networks (GRN) from Single cell gene expression data. The BLRun package currently incorporates 12 inference algorithms. The primary goal of this project is to expand this to 15 by adding the latest algorithms and test it on new datasets as well. The new algorithms would first be implemented and added to BEELINE as docker containers. These will then be evaluated for performance using the BLEval package and its metrics.
Enable popular Keras Hub GenAI/LLM pipelines for the OpenVINO backend in Keras 3 and optimize their performance. This project focuses on implementing missing operations in the OpenVINO backend to support and accelerate Gemma, Mistral, and GPT-2 pipelines for efficient inference. Additionally, it adds support for exporting these models to OpenVINO IR format using any backend. The final deliverables include 3 fully enabled and optimized pipelines running on Keras 3 with OpenVINO, along with reliable export functionality.
This project aims to refactor the core PEcAn workflow by decoupling heavy computational logic from disk I/O. Currently, data is passed via hidden .RData files, making the system difficult to test and maintain. I will modularize the Trait-Meta-analysis-Configuration chain to allow for in-memory data passing while maintaining data provenance as an opt-in persistence feature. Key deliverables include a "pure" version of get.trait.data.pft(), a standalone design matrix generator, and updated PDA/SDA workflows to support the new modular architecture, ensuring a more transparent and testable pipeline for ecological modeling.
<p>Over the last few years, the programming language Rust has seen a surge in popularity. This has primarily been the case due to its more robust memory management and faster execution when compared to C/C++. Rust’s features are advantageous while building scientific software since there’s often a large amount of data to analyse, and performance is one of the most critical concerns. Hence, Rust is now being applied to the development of bioinformatics tools as well. In the future, these tools will be increasingly used online, and implementation in the Rust language is expected to ensure the safety of these tools. This project aims to demonstrate the suitability of Rust to the development of a simulator for SBML models.</p>
This project aims to make PyTorch and OpenVINO interchangeable. By using the Python API of OpenVINO, we will create an adapter for PyTorch, the first of its kind. The goal of this project is to showcase (POC) the potential performance benefits of using OV. The change on the user side should look like: import torch --> import torch_adapter as torch. This library will cover all preprocessing steps of an image, up to loading a model for inference on the processed image. Benchmarks will be conducted on these to demonstrate the benefits of using my adapter, and tests will be performed to confirm consistency with PyTorch. Finally, the package will be released to be installable via pip in any environment (pip install torch_adapter).
<p>Cytoscape.js is a graph theory and networks library focused on providing built-in, rich and performant graph models for analysis and data visualization. This project aims at expanding Cytoscape.js’s data analysis functionalities by offering several of the most commonly used clustering algorithms, including the k-means, hierarchical, affinity propagation, Markov cluster algorithms and more, via extensions that can be easily incorporated into the default library. Such extensions, written in a user friendly and accessible manner, will help expand the usage of Cytoscape.js, as clustering algorithms are applicable in a wide variety of fields, from bioinformatics to machine learning, data science, etc.</p>
The aim of the project is to read industrial meter with Deep Learning frameworks and OpenVINO .The project is divided into two parts. In the first part of the project, we created a deep learning-based solution to read industrial meters. We achieved this by first detecting meters in the frame with the EfficientDet-d0 model, then doing semantic segmentation of meters with UNET (with a Resnet50 backbone) to obtain a segmentation map with which we calculated readings, and for inference we use the OpenVINO runtime. In part two of the project, we further optimize the solution pipeline to support multiple camera inputs with OpenVINO-toolkit functions like AsyncInferQueue and other performance hints, along with a web-based GUI with HTML,CSS, JS, and Flask web framework.
This project proposes a complete rewrite of BRL-CAD's existing OGV, which currently uses Meteor.js, an older framework no longer actively maintained. I suggest converting it to a more stable and maintainable framework. I plan to use Next.js, a modern React-based framework, for the frontend. SCSS/SASS will be used for styling, Nest.js will be used as the backend framework for better efficiency and type-safety, and Three.js will be used for modelling 3-D graphics on the web. Additionally, the frontend will be redesigned following industry-standard UI/UX best practices.. Also, it will be made sure to use libraries that have LTS support and are correctly maintained.
<p>Integrated Build Software Optimisation Tools (BOOST) with SBOLDesigner. SBOLDesigner is a CAD tool for creating and manipulating the sequences of genetic constructs using the Synthetic Biology Open Language (SBOL) 2.0 data model and BOOST is a repertoire of CAD/CAM tools for minimizing the cost and time for synthesizing DNA sequences with the maximal success rate of synthesis.</p> <p>Integration of them enabled automated synthetic biology design-build workflows by providing different functionalities like the DNA Sequence verification against constraints, modification of complex region according to the genetic code, fragmentation of large sequences depending on max. length of synthesis and desired assembly protocol.</p>
Java Pathfinder (JPF) is a Java virtual machine that can run compiled Java programs as well as model checking it. It is also an extensible software analysis framework for Java bytecode. As it has been created for about two decades, supporting new Java language features is of vital importance for its wide adoption. JPF community has taken steps to add Java 11 support, but there are still some unsolved issues. In this project, I plan to add better Java 11 support for JPF. This includes more comprehensive Java bytecode support, especially for invokedynamic, more JDK API support, and some bug fixes. It will fix all 13 failing tests JPF faces now on Java 11 and enable more programs to run on JPF.
The proposal outlines the development of an enhanced web application, IfcTester, for managing Building Information Modeling (BIM) project exchange requirements using IfcOpenShell. The current application lacks functionality and user experience improvements, which this project aims to address. It proposes a series of updates, including loading .ids files, implementing CRUD functionality for specifications and facets, upgrading the user interface, validating Ifc files, and potentially adding an XML editor. The proposal emphasizes on completing the half-built web app which allows viewing and minor editing of IDS files here: https://blenderbim.org/ifctester/ It focuses on finishing this web app, building features for more editing, drag and drop from a library of specifications, and adding and removing requirements.