https://gataslab.org/index.htmlThe GATAS (Generalized Algebraic Techniques Advancing Science) Lab at the University of Florida uses applied category theory to develop novel approaches to scientific computing.Hugoenhttps://gataslab.org/members/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/members/index.htmlThe members of the lab come from diverse perspectives with unique training. We are always looking for students and researchers with a desire to solve problems by leveraging abstract applications in novel science and engineering applications. Accepting applications for PhD Students in both MAE and CISE. Mathematically minded students would benefit from the MAE degree program specializing in Dynamics, Systems, and Control. For MAE applicants, the GATAS lab is particularly well suited to students interested in either Dynamics, Systems, and Control for optimization and dynamics projects or Computational Fluid Dynamics (CFD) for the Decapodes project. For CISE students, the GATAS lab is a good fit for students interested in High Performance Computing (HPC), Machine Learning, Data Science, Applied and Computational Mathematics, Computer Algebra, and Programming Language Theory. Research Projects for Undergraduates and Graduate Students in MAE, CISE, and Math Research Scientists and Postdocs in MAE, CISE, and Math Email fairbanksj [at] ufl [dot] edu for all new position inquirieshttps://gataslab.org/projects/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/projects/index.htmlHere you can find a list of our current research projects. Each project is composed of multiple publications. Decapodes A graphical tool for the composition of physical systems, built on the discrete exterior calculus. Algebraic Dynamics, Optimization, and Control Compositional frameworks for optimization, model predictive control, and dynamical systems. Compositional Algorithms with Sheaves Sheaf-theoretic methods for structured decompositions and compositional algorithms.https://gataslab.org/research/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/research/index.htmlThis page has tables of our research publications broken down by category. Journal papers YearTitleAuthorsJournalLink 2025 Porous Convection in the Discrete Exterior Calculus with Geometric Multigrid L. Morris, G. Rauta, K. Carlson, J. Fairbanks Arxiv Link 2024 Towards a Unified Theory of Time-varying Data B. Bumpus, J. Fairbanks, M. Karvonen, W. Leal, F. Simard Arxiv Link 2024 A Compositional Framework for First-Order Optimization T. Hanks, M Klawonn, M Hale, E Patterson, JP Fairbanks Arxiv Link 2024 Towards a Compositional Framework for Convex Analysis R. Samuelson, D. Stein Arxiv Link 2024 A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks R. Aduddell, J. Fairbanks, A. Kumar, P.S. Ocal, E. Patterson, B.T. Shapiro Compositionality Link 2024 The Diagrammatic Presentation of Equations in Categories K. Arlin, J. Fairbanks, T. Hosgood, E. Patterson Arxiv Link 2024 Compositional Algorithms on Compositional Data: Deciding Sheaves on Presheaves E. Althaus, B. Bumpus, J. Fairbanks, D. Rosiak Arxiv Link 2023 Decapodes: A Diagrammatic Tool for Representing, Composing, and Computing Spatialized Partial Differential Equations L. Morris, A. Baas, J. Arias, M. Gaitlin, E. Patterson, J. Fairbanks Journal of Computational Science Link 2023 Computational Category-Theoretic Rewriting K. Brown, E. Patterson, T. Hanks, J. Fairbanks J. Logical and Algebraic Methods in Programming Link 2023 The application of applied category theory to quantify mission success R. Garrett, J. Fairbanks, M. Loper, J. Moreland SIMULATION 99 (2) 201-220 Link 2023 A Compositional Framework for Convex Model Predictive Control T. Hanks, B. She, M. Hale, E. Patterson, M. Klawonn, J. Fairbanks Arxiv Link 2022 An Algebraic Framework for Structured Epidemic Modeling S. Libkind, A. Baas, M. Halter, E. Patterson, and J. P. Fairbanks Proc. of the Royal Society Phil. Trans. Link 2022 A Diagrammatic View of Differential Equations in Physics E. Patterson, A. Baas, T. Hosgood, J. P. Fairbanks Mathematics in Engineering Link 2022 Categorical Data Structures for Technical Computing E. J. Patterson, O. Lynch, J. P. Fairbanks Compositionality Link 2021 Category-theoretic formulation of the model-based systems architecting cognitive-computational Cycle Y. Mordecai, J. P. Fairbanks, E.F. Crawley MDPI Applied Sciences 11 (4), 1945 Link 2017 Spectral Partitioning with Blends of Eigenvectors J. P. Fairbanks, D. A. Bader, G. D. Sanders Journal of Complex Networks Link 2015 Behavioral Clusters in Dynamic Graphs J. P. Fairbanks, R. Kannan, H. Park, D. A. Bader Parallel Computing Special Issue of Scientific Graph Analysis Link 2011 A Ramsey Theorem for Indecomposable Matchings J. P. Fairbanks Electronic Journal of Combinatorics, Vol 18(1) Linkhttps://gataslab.org/publications/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/publications/index.htmlDetail pages for a few of our papers. The complete lists live on the Research and Publications pages. Decapodes: A diagrammatic tool for representing, composing, and computing spatialized partial differential equations Journal of Computational Science, 2024. A diagrammatic view of differential equations in physics Mathematics in Engineering, 2022. A Diagrammatic Presentation of Equations in Categories arXiv preprint, 2022.https://gataslab.org/bibliography/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/bibliography/index.htmlThis list is the same data as the bibliography table, exported from Zotero and rendered in an APA-flavoured style. Journal articles Morris, L., Baas, A., Arias, J., Gatlin, M., Patterson, E., & Fairbanks, J. P. (2024). Decapodes: A diagrammatic tool for representing, composing, and computing spatialized partial differential equations. Journal of Computational Science, 81, 102345. https://doi.org/10.1016/j.jocs.2024.102345 Aduddell, R., Fairbanks, J., Kumar, A., Ocal, P. S., Patterson, E., & Shapiro, B. T. (2024). A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks. Compositionality, 6, 2. https://doi.org/10.32408/compositionality-6-2 Brown, K., Patterson, E., Hanks, T., & Fairbanks, J. (2023). Computational category-theoretic rewriting. Journal of Logical and Algebraic Methods in Programming, 134, 100888. https://doi.org/10.1016/j.jlamp.2023.100888 Garrett, R. K., Fairbanks, J. P., Loper, M. L., & Moreland, J. D. (2023). The application of applied category theory to quantify mission success. Simulation, 99(2), 201–220. https://doi.org/10.1177/00375497221114861 Patterson, E., Baas, A., Hosgood, T., & Fairbanks, J. (2023). A diagrammatic view of differential equations in physics. Mathematics in Engineering, 5(2), 1–59. https://doi.org/10.3934/mine.2023036 Patterson, E., Lynch, O., & Fairbanks, J. (2022). Categorical Data Structures for Technical Computing. Compositionality, Volume 4 (2022). https://doi.org/10.32408/compositionality-4-5 Libkind, S., Baas, A., Halter, M., Patterson, E., & Fairbanks, J. P. (2022). An algebraic framework for structured epidemic modelling. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 380(2233), 20210309. https://doi.org/10.1098/rsta.2021.0309 Mordecai, Y., Fairbanks, J. P., & Crawley, E. F. (2021). Category-theoretic formulation of the model-based systems architecting cognitive-computational cycle. Applied Sciences, 11(4), 1945. Briscoe, E., & Fairbanks, J. (2020). Artificial scientific intelligence and its impact on national security and foreign policy. Orbis, 64(4), 544–554. Fairbanks, J. P., Bader, D. A., & Sanders, G. D. (2017). Spectral partitioning with blends of eigenvectors. Journal of Complex Networks, 5(4), 551–580. Fairbanks, J. P., Kannan, R., Park, H., & Bader, D. A. (2015). Behavioral clusters in dynamic graphs. Parallel Computing, 47, 38–50. Fairbanks, J. (2011). A Ramsey theorem for indecomposable matchings. arXiv:1110.3314. Conference proceedings Hanks, T., Nino, C., Barcelo, J. B., Copeland, A., Dixon, W., & Fairbanks, J. (2026). Heterogeneous Multi-agent multi-target tracking using cellular sheaves. In European Control Conference. IEEE. (to appear). Zhao, Y., Hanks, T., Riess, H., Cohen, S., Hale, M., & Fairbanks, J. (2026). Asynchronous nonlinear sheaf diffusion for multi-agent coordination. In IEEE American Control Conference. IEEE. (accepted). Currier, K., Leal, W., Rauta, G., Copeland, A., Dixon, W., & Fairbanks, J. (2026). Whitney Control Barrier Functions: A Mesh-based Geometric approach via Discrete Exterior Calculus. In IFAC. (in press). Hanks, T., Riess, H., Cohen, S., Gross, T., Hale, M., & Fairbanks, J. (2025). Distributed Multi-agent Coordination over Cellular Sheaves. In IEEE Conference on Decision and Control. IEEE. https://doi.org/10.48550/arXiv.2504.02049 Lary, M., Samuelson, R., Wilentz, A., Zare, A., Klawonn, M., & Fairbanks, J. (2025). Learning diagrams: a graphical language for compositional training regimes. In The thirteenth international conference on learning representations. https://openreview.net/forum?id=dqyuCsBvn9 Hanks, T., She, B., Hale, M., Patterson, E., Klawonn, M., & Fairbanks, J. (2024). Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems. In 2024 American Control Conference (ACC) (pp. 4850-4857). IEEE. https://doi.org/10.23919/ACC60939.2024.10644848 Bumpus, B. M., Fairbanks, J., Genovese, F., Puca, C., & Rosiak, D. (2024). How nice is this functor? Two squares and some homology go a long way. Proceedings of Applied Category Theory, 2024. Lynch, O., Brown, K., Fairbanks, J., & Patterson, E. (2024). GATlab: Modeling and Programming with Generalized Algebraic Theories. In Electronic Notes in Theoretical Informatics and Computer Science. Episciences. org. https://oxford24.github.io/assets/mfps-papers/MFPS24-11.pdf She, B., Hanks, T., Fairbanks, J., & Hale, M. (2023). Characterizing Compositionality of LQR from the Categorical Perspective. In 2023 62nd IEEE Conference on Decision and Control (CDC) (pp. 1680-1685). https://doi.org/10.1109/CDC49753.2023.10383467 Aguinaldo, A., Patterson, E., Fairbanks, J., Regli, W., & Ruiz, J. (2023). A Categorical Representation Language and Computational System for Knowledge-Based Robotic Task Planning [Best Paper Award]. In Proceedings of the AAAI Symposium Series (pp. 491-497). https://doi.org/10.1609/aaaiss.v2i1.27718 Libkind, S., Baas, A., Patterson, E., & Fairbanks, J. (2022). Operadic Modeling of Dynamical Systems: Mathematics and Computation. Electronic Proceedings in Theoretical Computer Science, 372, 192-206. https://doi.org/10.4204/EPTCS.372.14 Brown, K., Patterson, E., Hanks, T., & Fairbanks, J. (2022). Computational Category-Theoretic Rewriting [Best Paper]. In Graph Transformation: 15th International Conference, ICGT 2022, Held as Part of STAF 2022, Nantes, France, July 7–8, 2022, Proceedings (pp. 155–172). Springer-Verlag. https://doi.org/10.1007/978-3-031-09843-7_9 Brown, K., Hanks, T., & Fairbanks, J. (2022). Compositional Exploration of Combinatorial Scientific Models. In Applied Category Theory. https://doi.org/10.48550/ARXIV.2206.08755 Halter, M., Herlihy, C., & Fairbanks, J. (2020). A Compositional Framework for Scientific Model Augmentation. In Electronic Proceedings in Theoretical Computer Science (pp. 172-182). Opn Publishing Association. https://doi.org/10.4204/EPTCS.323.12 Fairbanks, J. P., Fitch, N., Bradfield, F., & Briscoe, E. (2020). Credibility Development with Knowledge Graphs. In Lecture Notes in Computer Science (pp. 33-47). Springer International Publishing. https://doi.org/10.1007/978-3-030-39627-5_4 Cao, K., & Fairbanks, J. (2019). Unsupervised Construction of Knowledge Graphs From Text and Code. In SIGKDD Conference on Knowledge Discovery and Data Mining International Workshop on Mining and Learning with Graphs. ACM. Nadolski, M., & Fairbanks, J. (2019). Complex systems analysis of hybrid warfare. Procedia Computer Science, 153, 210-217. https://doi.org/10.1016/j.procs.2019.05.072 Campbell, N., Goodyear, T., Messer, W., Stuart, E., & Fairbanks, J. (2018). Digital Witness: Remote Method for Volunteering Digital Evidence on Mobile Devices. In 2018 IEEE International Symposium on Technologies for Homeland Security (HST) (pp. 1-5). IEEE. https://doi.org/10.1109/THS.2018.8574119 Thankachan, R. V., Swenson, B. P., & Fairbanks, J. P. (2018). Performance Effects of Dynamic Graph Data Structures in Community Detection Algorithms. In 2018 IEEE High Performance extreme Computing Conference (HPEC) (pp. 1-7). IEEE. https://doi.org/10.1109/HPEC.2018.8547528 Fairbanks, J. P., Fitch, N., Knauf, N., & Briscoe, E. (2018). Credibility Assessment in the News: Do We Need to Read? In WSDM/MIS2 (pp. 8). ACM. https://doi.org/10.1145/3159652.3160597 Nathan, E., Fairbanks, J., & Bader, D. (2018). Ranking in Dynamic Graphs Using Exponential Centrality. In Complex Networks & Their Applications VI (pp. 378-389). Springer International Publishing. https://doi.org/10.1007/978-3-319-72150-7_31 Thankachan, R. V., Hein, E. R., Swenson, B. P., & Fairbanks, J. P. (2017). Integrating productivity-oriented programming languages with high-performance data structures. In 2017 IEEE High Performance Extreme Computing Conference (HPEC) (pp. 1-8). IEEE. https://doi.org/10.1109/HPEC.2017.8091068 Ediger, D., & Fairbanks, J. P. (2017). Deriving Streaming Graph Algorithms from Static Definitions. In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 637-642). IEEE. https://doi.org/10.1109/IPDPSW.2017.146 Nathan, E., Sanders, G., Fairbanks, J., Henson, V. E., & Bader, D. A. (2017). Graph Ranking Guarantees for Numerical Approximations to Katz Centrality. Procedia Computer Science, 108, 68-78. https://doi.org/10.1016/j.procs.2017.05.021 Fairbanks, J. P., Zakrzewska, A., & Bader, D. A. (2016). New stopping criteria for spectral partitioning. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 25-32). IEEE. https://doi.org/10.1109/ASONAM.2016.7752209 Zakrzewska, A., Nathan, E., Fairbanks, J., & Bader, D. A. (2016). A local measure of community change in dynamic graphs. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 349-353). IEEE. https://doi.org/10.1109/ASONAM.2016.7752257 Fairbanks, J., Ediger, D., McColl, R., Bader, D. A., & Gilbert, E. (2013). A statistical framework for streaming graph analysis. In 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013) (pp. 341-347). https://doi.org/10.1145/2492517.2492620 Talks and conference talks Fairbanks, J. (2025). Modeling with ACT for Compositional Decision Making [Talk]. American Control Conference, Denver, CO. Fairbanks, J., & Patterson, E. (2025). Compositional Development of Compositional Mathematics [Talk]. Applied Category Theory, Gainesville, FL. Carlson, K. (2025). Multigrid Methods for Structure Preserving Discretizations [Talk]. 22ND Copper Mountain Conference on Multigrid Methods, Copper Mountain, CO. Fairbanks, J. P., Aduddell, R., Kumar, A., Ocal, P. S., Patterson, E., & Shapiro, B. T. (2024). A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks. AMS Southeastern Sectional Meeting, Tallahassee, FL. Fairbanks, J. P., & Lynch, O. (2023). Computational category theory in applied mathematics [Invited]. Joint Mathematics Meetings, Boston, MA. Aduddell, R., Ocal, P. S., Fairbanks, J. P., Patterson, E., Shapiro, B., & Kumar, A. (2023). A categorical framework for (gene) regulatory networks. Joint Mathematics Meeting, Boston, MA. Patterson, E., Hosgood, T., Baas, A., & Fairbanks, J. (2022). Diagrammatic differential equations: Formal categorical framework and applications to multiphysics simulation. Applied Category Theory, Glasgow, UK. https://doi.org/10.3934/mine.2023036 Libkind, S., Baas, A., Halter, M., Patterson, E., & Fairbanks, J. (2022). Typed and stratified models with slice categories. In Applied Category Theory (pp. 1-3). https://msp.cis.strath.ac.uk/act2022/papers/ACT2022_paper_3530.pdf Wu, S. L., Libkind, S., Brown, K., Patterson, E., & Fairbanks, J. (2022). Individual. jl: Rewriting individual-based models for epidemiology using graph rewriting [Extended abstract]. Applied Category Theory, Glasgow, UK. https://msp.cis.strath.ac.uk/act2022/papers/ACT2022_paper_3642.pdf Jackson, M., Halter, M., Goodyear, T., O’Donnell, B., & Fairbanks, J. (2021). Accelerating automatic target recognition performance evaluation with a relational database. Tri-Service Radar Symposium. Lynch, O., Patterson, E., & Fairbanks, J. (2021). Shaped data with acsets. JuliaCon, Virtual. https://pretalx.com/juliacon2021/talk/NWRPGY/ Libkind, S., & Fairbanks, J. (2021). AlgebraicDynamics: Compositional dynamical systems. JuliaCon, Virtual. https://pretalx.com/juliacon2021/talk/ARURL8/ Halter, M., Patterson, E., Baas, A., & Fairbanks, J. (2020). Compositional Scientific Computing with Catlab and SemanticModels. In Applied Category Theory. http://arxiv.org/abs/2005.04831 Halter, M., Raparti, S., Cao, K., Herlihy, C., & Fairbanks, J. (2020). SemanticModels. jl: a julia package for scientific model augmentation. In Proceedings of the JuliaCon conferences (pp. 57). Herlihy, C., & Fairbanks, J. (2019). semanticmodels.jl: Not just another modeling framework. JuliaCon, Baltimore, MD. https://www.youtube.com/watch?v=WJneK7OjqMQ Herlihy, C., Cao, K., Reparti, S., Briscoe, E., & Fairbanks, J. (2019). Semantic Program Analysis for Scientific Model Augmentation. Modeling the World’s Systems, 7. Fairbanks, J. (2018). The JuliaGraphs ecosystem: Move fast and don't break things. JuliaCon, London, UK. https://youtu.be/OZuQoxTPoyM Besançon, M., & Fairbanks, J. (2018). Graph interfaces: Bespoke graphs for every occasion. JuliaCon, London, UK. https://youtu.be/OD-BSn4FZ2A Bromberger, S., & Fairbanks, J. (2017). LightGraphs: Our network, our story. JuliaCon, Berkeley, CA. https://youtu.be/MFD-qmApXl8 Frederick, T., Herlihy, C., & Fairbanks, J. (2017). Using big data to predict and analyze cooperation and conflict. The Conflict Conference, University of Texas, Austin, TX. Fairbanks, J., Knauf, N., Fitch, N., Herlihy, C., & Briscoe, E. (2017). Assessing credibility in the global news media. http://resources.basistech.com.s3.amazonaws.com/hltcon-presentations/2017/Fairbanks_Georgia_Tech_HLTCon.pdf Bader, D., Michalewicz, A., Green, O., Birkett-Rees, J., Riedy, J., Fairbanks, J., & Zakrzewska, A. (2016). Semantic database applications at the samtavro cemetery, georgia. In The 44th Computer Applications and Quantitative Methods in Archaeology Conference (CAA). Archaeopress. https://2016.caaconference.org/session-11-supporting-researchers-in-the-use-and-re-use-of-archaeological-data-continuing-the-ariadne-thread/ Posters Perez, J., Baas, A., Ferrall-Fairbanks, M. C., Platt, M. O., & Fairbanks, J. P. (2021). Parameter estimation by minimizing the loss with respect to a finite difference approximation on the vector field. Biomedical Engineering Society Annual Meeting, Orlando, FL. Lynch, O., Fairbanks, J. P., & Patterson, E. (2021). Graphical semantic modeling with semagrams.jl. Applied Category Theory, Cambridge, UK. Fairbanks, J. P. (2019). Semantic model understanding for scientific model augmentation. Systems Biology of Human Disease,, Berlin, DE. Fairbanks, J. P. (2017). QueryGarden: growing healthy applications in well prepared SQL. OHDSI Symposium, New York, NY. Brown, C. S., Duke, J., Fairbanks, J. P., Herlihy, C., Mukadam, K., Poovey, J., & Rost, M. (2017). Implementing real-time patient level predictions using PLP models. OHDSI Symposium. Fairbanks, J. P. (2015). Discovering block structure with approximate eigenvectors. SIAM Computational Science and Engineering. Fairbanks, J., & Sanders, G. (2015). Discovering block structure in graphs with approximate eigenvectors [Poster]. SIAM Computational Science and Engineering, Salt Lake City, UT. https://jpfairbanks.com/doc/siam-cse-2015.pdf Fairbanks, J. P. (2012). Ramsey theorem for indecomposable matchings. Graph Theory at Georgia Tech (GT@GT), Atlanta, GA. Preprints Bumpus, B. M., Fairbanks, J., & Turner, W. J. (2024). Pushing Tree Decompositions Forward Along Graph Homomorphisms. arXiv. https://doi.org/10.48550/arXiv.2408.15184 Hanks, T., Klawonn, M., Patterson, E., Hale, M., & Fairbanks, J. (2024). A Compositional Framework for First-Order Optimization. arXiv. https://doi.org/10.48550/arXiv.2403.05711 Arlin, K., Fairbanks, J., Hosgood, T., & Patterson, E. (2024). The diagrammatic presentation of equations in categories. arXiv:2401.09751. Bumpus, B. M., Capucci, M., Fairbanks, J., & Rosiak, D. (2024). Failures of compositionality: a short note on cohomology, sheafification and lavish presheaves. arXiv:2407.03488. Althaus, E., Bumpus, B. M., Fairbanks, J., & Rosiak, D. (2023). Compositional Algorithms on Compositional Data: Deciding Sheaves on Presheaves. arXiv. https://doi.org/10.48550/arXiv.2302.05575 Talks, extremely comprehensive list Fairbanks, J. P. (2026). Compositional Modeling: Structures, Dynamics, Optimization. American Control Conference, New Orleans, LA. Fairbanks, J. P. (2026). Panel on Applied Category Theory for Compositional Decision Making. American Control Conference, New Orleans, LA. Rauta, G., Fairbanks, J. P., & Kuzendorf, W. (2026). Low-Mach Compressible Navier-Stokes Using Discrete Exterior Calculus on Rectilinear Grids. WCCM-ECCOMAS [accepted], Munich, Germany. Cohen, S., & Fairbanks, J. P. (2026). Federated Learning with Cellular Sheaves. UF Undergraduate Research Symposium, Gainesville, FL. Hanks, T., Reiss, H., Cohen, S., Gross, T., Hale, M., & Fairbanks, J. P. (2026). Distributed Multi-Agent Coordination over Cellular Sheaves. AMS Special Session on Applied Category Theory Joint Mathematics Meeting, Washington DC. Gross, T., & Fairbanks, J. P. (2026). Quadrotor Coordination Using Cellular Sheaves and Linearized LQR. Center for Undergraduate Research Spring Symposium, Gainesville, FL, USA. Bou Barcelo, J., & Fairbanks, J. P. (2026). Heterogeneous Multi-Agent Multi-Target Tracking. INFORMS Optimization Society Conference, Atlanta, GA. Hanks, T., Klawonn, M., Patterson, E., Hale, M., & Fairbanks, J. P. (2026). Categorical Foundations of Distributed Optimization and Learning. AMS Special Session on Mathematical Foundation of Machine Learning, Joint Mathematics Meeting, Washington DC. Hanks, T., & Fairbanks, J. P. (2026). Coordination Sheaves. Core Lab Georgia Tech, Atlanta. Fairbanks, J. P., & Zare, A. (2025). Domain Transfer for Continuity of Performance Across SAS Systems ​. ONR Code 32 Program Review, Online. Fairbanks, J. P., & Leal, W. (2025). Sheaves in Time Varying Data and Dynamical Systems. NCR Lab UF MAE Department, Gainesville, FL. Leal, W., & Fairbanks, J. P. (2025). Sheaves in Dynamical Systems: Enumerating Fixed Points of CTLNs. Kallies Research Group, Toledo, OH. Fairbanks, J. P. (2025). Building Modeling and Simulation Tools on Discrete Exterior Calculus Foundations. IMSI workshop on Discrete Exterior Calculus Differential Geometry and Applications, Chicago, Ill. Fairbanks, J. P., & Leal, W. (2025). Computing Fixed Points of CTLNs with Separated Presheaves, Sheaves and Dynamic Programming. Category Theory Octoberfest 2025, Online. Wall, A., & Fairbanks, J. P. (2025). A Category-Theoretic Approach to Resource Optimization. University Mathematics Society, Gainesville, FL. Fairbanks, J. P., & Leal, W. (2025). Sheaf Cohomology on Simplicial Complexes. CODAC COE, Gainesville, FL. Leal, W. (2025). Temporal Analysis of Data Using Category Theory and the Hidden Connection Between Persistence and Accumulation. Seminario de Matemáticas Aplicadas, Quantil, Colombia. Fairbanks, J. P. (2025). Going beyond graphs: simplicial, hyper, and relational structure. JuliaCon, Pittsburgh. Fairbanks, J. P. (2025). New Approaches in Computational Physics: Multiphysics and Multiscale with Discrete Exterior Calculus. Army Research Lab, Adelphi, MD. Fairbanks, J. P. (2025). Introduction to Applied Category Theory for Compositional Decision Making. ACC Conference Workshop, Denver, CO. Fairbanks, J. P. (2025). Compositional Modeling in Applied Category Theory for Compositional Decision Making. ACC Conference Workshop, Denver, CO. Rauta, G., & Fairbanks, J. P. (2025). Modeling of Coupled Weakly Compressible Navier-Stokes and Thermal Equation in the Discrete Exterior Calculus. Army Research Lab Poster Session, Adelphi, MD. Hanks, T., & Fairbanks, J. P. (2025). Category Theory for Distributed Optimization. Applied Category Theory [keynote], Gainesville, FL. Zelko, J., Cuffaro, M., Wu, S., & Fairbanks, J. P. (2025). A Case Study in Public Health Research. Applied Category Theory, Gainesville, FL. Fairbanks, J. P., & Patterson, E. (2025). AlgebraicJulia Compositional Development of Compositional Mathematics. Applied Category Theory, Gainesville, FL. Hanks, T., & Fairbanks, J. P. (2025). Multiagent Autonomy with Cellular Sheaves. GTRI ACAI, Atlanta, GA. Wall, A., & Fairbanks, J. P. (2025). Structured Decompositions. Undergraduate Mathematics Research Symposium, Gainesville, FL. Fairbanks, J. P., & Kim, N. (2025). T6: Validation, Uncertainty Quantification, Uncertainty Budget, Workflow and Data Management. CM3C: Center for Multiscale Modeling of Multiphase Combustion, Gainesville, FL. Fairbanks, J. P. (2024). A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks. AMS Southeastern Sectional Meeting, Tallahassee, FL. Morris, L. L., Baas, A., Fairbanks, J. P., Arias, J., & Gaitlin, M. (2023). Abstraction and Composition in Modeling and Simulation. Mechanical and Aerospace Engineering Seminar, Gainesville, FL. Morris, L., & Nathan, E. (2023). Discourse Sheaves for Opinion Dynamics over Social Media Data. Lawrence Livermore National Laboratory Summer SLAM, Livermore, CA. Libkind, S., Bumpus, B. M., Garcia, J. L., Sorkatti, L. H., & Tenka, S. (2023). Additive Invariants of Open Petri Nets. Applied Category Theory, College Park, MD. Lynch, O., Brown, K., Fairbanks, J. P., & Patterson, E. (2023). Gatlab. jl: Symbolic computing with categories using generalized algebraic theories. Applied Category Theory, College Park, MD. Bumpus, B. M., Fairbanks, J. P., Rosiak, D., & Althaus, E. (2023). Compositional Algorithms on Compositional Data: Deciding Sheaves on Presheaves. Applied Category Theory, College Park, MD. Fairbanks, J. P., Hanks, T. E., She, B., Patterson, E., Hale, M., & Klawonn, M. (2023). A Compositional Framework for Convex Model Predictive Control. Applied Category Theory, College Park, MD. Fairbanks, J. P., Morris, L. L., & Rauta, G. (2023). Computational Multiphysics in a Categorical Framework. Applied Category Theory, College Park, MD. Fairbanks, J. P., Hanks, T., She, B., Hale, M., Patterson, E., & Klawonn, M. (2023). A Compositional Framework for Model Predictive Control. AFOSR Center of Excellence Program Review, Gainesville, FL. Fairbanks, J. P. (2023). Decapodes. jl: A Framework for Multiphysics Simulation. MAE Department AFOSR Visit, Gainesville, FL. Morris, L. L., Baas, A., Fairbanks, J. P., Arias, J., & Gaitlin, M. (2023). Abstraction and Composition in Modeling and Simulation. SIAM Conference on Computational Science and Engineering, Amsterdam, NL. Fairbanks, J. P., Morris, L. L., & Rauta, G. (2023). Categorical Composition of Discrete Exterior Calculus Climate Models. Programming for the Planet (PROPL) at POPL, London, UK. Bumpus, B. M. (2023). Chopping things up to decide stuff fast. International seminar series on applications of category theory to finite model theory and computer science, Nottingham, United Kingdom. Bumpus, B. M., & Fairbanks, J. P. (2023). Chopping things up to decide stuff fast. 54th Southeastern International Conference on Combinatorics Graph Theory and Computing, Boca Raton, FL. Morris, L. L., Baas, A., Fairbanks, J. P., Arias, J., & Gaitlin, M. (2023). Abstraction and Composition in Modeling and Simulation. Graduate Mathematics Association, Gainesville, FL. Fairbanks, J. P. (2022). Scientific and Engineering Modeling with Applied Category Theory. DARPA Young Faculty Colloquium, Arlington, VA. Fairbanks, J. P., & Patterson, E. (2022). Enkix Task Reasoning. DARPA Site Visit, Gainesville, FL. Fairbanks, J. P. (2022). Computational Physics Modeling with Categories. Institute of Theoretical Physics, Friedric-Alexander-Universitaet, Erlangen-Nuernberg, Germany. Libkind, S., & Fairbanks, J. P. (2022). Compositional Modeling of Disease Dynamics. UW-IHME Compositional Epidemiology Modeling Working Group, Online. Fairbanks, J. P. (2022). Using Category Theory to Design Computational Mathematics Software. Numerical Analysis Seminar at UF Mathematics Department, Gainesville, FL. Fairbanks, J. P. (2022). Scientific and Engineering Modeling with Applied Category Theory. MAE Department Control Theory Working Group, Gainesville, FL. Fairbanks, J. P. (2022). Applied Category Theory for the Mathematics of Disease. Canadian Network for Modeling Infectious Disease, Vancouver, Canada. Fairbanks, J. P., & Patterson, E. (2022). Enkix Task Reasoning. DARPA Site Visit, Gainesville, FL. Hanks, T. (2022). Compositional Convex Optimization. Air Force Research Laboratory, Rome, NY. Fairbanks, J. P. (2022). Diagrammatic Equations in Physics: Directly Computable Models. Lawrence Livermore National Laboratory Center for Applied Scientific Computing, Livermore, CA. Fairbanks, J. P. (2022). Model Aware Scientific Computing with Categories. Air Force Research Laboratory, Rome, NY. Fairbanks, J. P. (2022). Diagrammatic Equations for Complex Machine Learning Formulations. ONR Code 32 Site Visit, Gainesville, FL. Fairbanks, J. P. (2022). Introduction to Category Theory. The Simula Corporation, Oslo, NO. Fairbanks, J. P. (2022). Diagrammatic Equations In Physics, Directly Computable Models. The Simula Corporation, Oslo, NO. Fairbanks, J. P. (2022). Computational Modeling with Category Theory. Systems Medicine Laboratory Seminar UF College of Medicine, Gainesville, FL. Fairbanks, J. P. (2022). Scientific Modeling with AlgebraicJulia. Rel.AI Research Seminar, Online. Fairbanks, J. P., & Lynch, O. (2022). Computational Category Theory in Applied Mathematics. Joint Mathematics Meetings, Boston, MA. Fairbanks, J. P., Aduddell, R., Ocal, P. S., Patterson, E., Shapiro, B., & Kumar, A. (2022). A Categorical Framework for (Gene) Regulatory Networks. Joint Mathematics Meeting, Boston, MA. Bumpus, B. M., & Fairbanks, J. P. (2022). Structured Decompositions: Recursive Data and Recursive Algorithms. Joint Math Meeting, Boston, MA. Brown, K., & Fairbanks, J. P. (2022). Automated Model Space Exploration. UW-IHME Compositional Epidemiology Modeling Working Group, Online. Fairbanks, J. P., Perez, J., Baas, A., Ferrall-Fairbanks, M., & Platt, M. O. (2021). Parameter Estimation by Minimizing the Loss with Respect to a Finite Difference Approximation on the Vector Field. Biomedical Engineering Society Annual Meeting, Orlando, FL. Lynch, O., Patterson, E., & Fairbanks, J. P. (2021). Shaped Data with ACSets. JuliaCon, Online. Libkind, S., Patterson, E., & Fairbanks, J. P. (2021). Shaped Data with ACSets. JuliaCon, Online. Fairbanks, J. P., & Patterson, E. (2021). Compositional Modeling with AlgebraicJulia. NIH Interagency Modeling and Analysis Group, Online. Fairbanks, J. P. (2021). The AlgebraicJulia Ecosystem: a Categorical Approach to Technical Computing. Topos Institute Berkeley Seminar, Berkeley, CA. Fairbanks, J. P. (2021). Computational Categorical Algebra with Catlab. Graph Transformation Theory and Applications, Paris, FR. Fairbanks, J. P. (2021). Progress towards the GroMet specification for semantic model exchange. DARPA Automating Scientific Knowledge Extraction Principal Investigator Meeting, Arlington, VA. Fairbanks, J. P. (2021). Generalized Algebraic Theories for Enhancing Multiphysics: An Introductory Deep Dive. DARPA Directly Computable Models Program Review, Arlington, VA. Fairbanks, J. P. (2021). Categorical Scientific Knowledge Representation. DARPA Automating Scientific Knowledge Extraction Stakeholder Workshop, Arlington, VA. Fairbanks, J. P. (2021). Model Aware Computing with Scientific Categories. DARPA Young Investigator Award Principal Investigator Meeting, Arlington, VA. Fairbanks, J. P. (2021). Introduction to the AlgebraicJulia Software Ecosystem. UF CISE - LLNL Advisory Board Annual Meeting, Gainesville, FL. Fairbanks, J. P. (2020). Rethinking Set Theory and Computational Mathematics. Undergraduate Math Society, Gainesville, FL.https://gataslab.org/presentations/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/presentations/index.htmlEach week the GATAS Lab holds a lab meeting where one or two lab members gives a 30-60 minute presentation. We use these presentations for practice talks or educating each other on open problems. Here you can find a collection of previous talks. DateTitlePresenterSlides Nov 12, 2024 Fall 2024 progress: Structured Decompositions Andersen Wall Slides Nov 12, 2024 Implementing Cellular Sheaf Optimization Using PartitionedArrays Sam Cohen Slides Nov 5, 2024 Parallel Computing with MPI George Rauta Slides Oct 29, 2024 DEC Tips and Tricks 4 Luke Morris Slides Oct 3, 2024 The Decapodes Pipeline George Rauta Slides Oct 1, 2024 Sharing Vector Variables via Typed UWDs in AlgebraicOptimization.jl Sam Cohen Slides Oct 1, 2024 Newton's Method Tyler Hanks Slides Sep 10, 2024 Categorical Chemistry: The Architecture of a Chemical Computer Wilmer Leal Slides Aug 28, 2024 DEC Tips and Tricks 3 Luke Morris Slides Aug 21, 2024 Towards a Unified Theory of Time-Varying Data Wilmer Leal Slides Mar 25, 2024 CUDA.jl George Rauta Slides Mar 25, 2024 GATAS Lab Retreat Spring '24 Matt Cuffaro Slides Mar 3, 2024 Categorical Chemistry: The architecture of a chemical computer Wilmer Leal Slides Feb 5, 2024 BuildKite: In My Daemon Node? Matt Cuffaro Slides Feb 5, 2024 Net Flow Tyler Hanks Slides Nov 17, 2023 Discrete Exterior Calculus Tips & Tricks; Part 2 Luke Morris Slides Nov 9, 2023 Dialectica Petri nets: A linear logic model of reaction systems Wilmer Leal Slides Nov 9, 2023 Flow Talk Tyler Hanks Slides Sep 19, 2023 Chemical Reactions and the reasoning system in Chemistry Wilmer Leal Slides Sep 14, 2023 Decorate Corels Talk Tyler Hanks Slides Sep 11, 2023 Discrete Exterior Calculus Tips & Tricks; Part 1 Luke Morris Slides Jan 16, 2015 Tree Decompositions in Julia Richard Samuelson Slideshttps://gataslab.org/sponsors/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/sponsors/index.htmlOur lab is supported by several sponsors, specifically the following US Federal Agencies. Defense Advanced Research Projects Agency DARPA Office of Naval Research ONR Air Force Research Laboratory AFRL National Science Foundation NSF Grants and contracts Our sponsors have supported the GATAS Lab and the AlgebraicJulia Ecosystem through the following projects. All sponsorsARODARPAGTRI SINIJONR SponsorTitleAmountStart YearEnd YearPrimary Institution ONR Domain Transfer for Continuity of Performance Across Synthetic Aperture Sonar 500K 2023 2026 UFL ARO Machine Learning-based Sensor Fusion for Electro-optical and Infrared Target Detection 175K 2022 2023 Huntington-Ingalls DARPA ASKEM: Generalized Algebraic Techniques Advancing Scientific Discovery 5.8M 2022 2025 UFL DARPA Director's Fellowship: Model Aware Scientific Computing 250K 2022 2023 UFL DARPA Perceptual Task Guidance: ENKIx 4.8M 2022 2024 UFL DARPA Young Faculty Award: Model Aware Scientific Computing 500K 2020 2022 GTRI DARPA AIE: Automating Scientific Knowledge Extraction Extended 700K 2020 2021 GTRI DARPA Directly Computable Models: Generalized Algebraic Theories Enhancing Multiphysics 1M 2019 2021 GTRI DARPA Artificial Social Intelligence for Successful Teams (ASIST) 400K 2019 2023 Gallup ONR Extracting, Explaining, and Estimating Information in Sonar Data (E3ISD) 695K 2019 2022 GTRI ONR Mine Counter-measures Situational Awareness 375K 2019 2021 GTRI DARPA Artificial Intelligence Exporation: Automating Scientific Knowledge Extraction 1M 2018 2020 GTRI NIJ Developing Novel Means of Evidence Collection 400K 2016 2018 GTRI ONR Performance Estimation of Underwater Mine Counter-measures Operations 990K 2016 2019 GTRI GTRI SI Multi-source Anticipatory Intelligence 900K 2016 2019 GTRIhttps://gataslab.org/act2025/index.htmlMon, 01 Jan 0001 00:00:00 +0000https://gataslab.org/act2025/index.htmlAbout The 8th International Conference on Applied Category Theory (ACT) took place together at the University of Florida on June 2-6, 2025. The conferences were preceded by the Adjoint School on May 26-30, 2025. For more information on the ACT series, see here. This conference has taken place ACT 2025 was held at the University of Florida on June 2-6, 2025. This page is kept as a record of the event; the call for participation and the schedule are preserved below. Registration is closed.