Publications

This list is the same data as the bibliography table, exported from Zotero and rendered in an APA-flavoured style.

Journal articles

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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.
  9. Briscoe, E., & Fairbanks, J. (2020). Artificial scientific intelligence and its impact on national security and foreign policy. Orbis, 64(4), 544–554.
  10. Fairbanks, J. P., Bader, D. A., & Sanders, G. D. (2017). Spectral partitioning with blends of eigenvectors. Journal of Complex Networks, 5(4), 551–580.
  11. Fairbanks, J. P., Kannan, R., Park, H., & Bader, D. A. (2015). Behavioral clusters in dynamic graphs. Parallel Computing, 47, 38–50.
  12. Fairbanks, J. (2011). A Ramsey theorem for indecomposable matchings. arXiv:1110.3314.

Conference proceedings

  1. 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).
  2. 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).
  3. 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).
  4. 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
  5. 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
  6. 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
  7. 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.
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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.
  17. 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
  18. 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
  19. 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
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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

  1. Fairbanks, J. (2025). Modeling with ACT for Compositional Decision Making [Talk]. American Control Conference, Denver, CO.
  2. Fairbanks, J., & Patterson, E. (2025). Compositional Development of Compositional Mathematics [Talk]. Applied Category Theory, Gainesville, FL.
  3. Carlson, K. (2025). Multigrid Methods for Structure Preserving Discretizations [Talk]. 22ND Copper Mountain Conference on Multigrid Methods, Copper Mountain, CO.
  4. 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.
  5. Fairbanks, J. P., & Lynch, O. (2023). Computational category theory in applied mathematics [Invited]. Joint Mathematics Meetings, Boston, MA.
  6. 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.
  7. 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
  8. 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
  9. 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
  10. 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.
  11. Lynch, O., Patterson, E., & Fairbanks, J. (2021). Shaped data with acsets. JuliaCon, Virtual. https://pretalx.com/juliacon2021/talk/NWRPGY/
  12. Libkind, S., & Fairbanks, J. (2021). AlgebraicDynamics: Compositional dynamical systems. JuliaCon, Virtual. https://pretalx.com/juliacon2021/talk/ARURL8/
  13. 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
  14. 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).
  15. Herlihy, C., & Fairbanks, J. (2019). semanticmodels.jl: Not just another modeling framework. JuliaCon, Baltimore, MD. https://www.youtube.com/watch?v=WJneK7OjqMQ
  16. Herlihy, C., Cao, K., Reparti, S., Briscoe, E., & Fairbanks, J. (2019). Semantic Program Analysis for Scientific Model Augmentation. Modeling the World’s Systems, 7.
  17. Fairbanks, J. (2018). The JuliaGraphs ecosystem: Move fast and don't break things. JuliaCon, London, UK. https://youtu.be/OZuQoxTPoyM
  18. Besançon, M., & Fairbanks, J. (2018). Graph interfaces: Bespoke graphs for every occasion. JuliaCon, London, UK. https://youtu.be/OD-BSn4FZ2A
  19. Bromberger, S., & Fairbanks, J. (2017). LightGraphs: Our network, our story. JuliaCon, Berkeley, CA. https://youtu.be/MFD-qmApXl8
  20. 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.
  21. 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
  22. 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

  1. 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.
  2. Lynch, O., Fairbanks, J. P., & Patterson, E. (2021). Graphical semantic modeling with semagrams.jl. Applied Category Theory, Cambridge, UK.
  3. Fairbanks, J. P. (2019). Semantic model understanding for scientific model augmentation. Systems Biology of Human Disease,, Berlin, DE.
  4. Fairbanks, J. P. (2017). QueryGarden: growing healthy applications in well prepared SQL. OHDSI Symposium, New York, NY.
  5. 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.
  6. Fairbanks, J. P. (2015). Discovering block structure with approximate eigenvectors. SIAM Computational Science and Engineering.
  7. 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
  8. Fairbanks, J. P. (2012). Ramsey theorem for indecomposable matchings. Graph Theory at Georgia Tech (GT@GT), Atlanta, GA.

Preprints

  1. 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
  2. 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
  3. Arlin, K., Fairbanks, J., Hosgood, T., & Patterson, E. (2024). The diagrammatic presentation of equations in categories. arXiv:2401.09751.
  4. 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.
  5. 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

  1. Fairbanks, J. P. (2026). Compositional Modeling: Structures, Dynamics, Optimization. American Control Conference, New Orleans, LA.
  2. Fairbanks, J. P. (2026). Panel on Applied Category Theory for Compositional Decision Making. American Control Conference, New Orleans, LA.
  3. 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.
  4. Cohen, S., & Fairbanks, J. P. (2026). Federated Learning with Cellular Sheaves. UF Undergraduate Research Symposium, Gainesville, FL.
  5. 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.
  6. Gross, T., & Fairbanks, J. P. (2026). Quadrotor Coordination Using Cellular Sheaves and Linearized LQR. Center for Undergraduate Research Spring Symposium, Gainesville, FL, USA.
  7. Bou Barcelo, J., & Fairbanks, J. P. (2026). Heterogeneous Multi-Agent Multi-Target Tracking. INFORMS Optimization Society Conference, Atlanta, GA.
  8. 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.
  9. Hanks, T., & Fairbanks, J. P. (2026). Coordination Sheaves. Core Lab Georgia Tech, Atlanta.
  10. Fairbanks, J. P., & Zare, A. (2025). Domain Transfer for Continuity of Performance Across SAS Systems ​. ONR Code 32 Program Review, Online.
  11. Fairbanks, J. P., & Leal, W. (2025). Sheaves in Time Varying Data and Dynamical Systems. NCR Lab UF MAE Department, Gainesville, FL.
  12. Leal, W., & Fairbanks, J. P. (2025). Sheaves in Dynamical Systems: Enumerating Fixed Points of CTLNs. Kallies Research Group, Toledo, OH.
  13. 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.
  14. Fairbanks, J. P., & Leal, W. (2025). Computing Fixed Points of CTLNs with Separated Presheaves, Sheaves and Dynamic Programming. Category Theory Octoberfest 2025, Online.
  15. Wall, A., & Fairbanks, J. P. (2025). A Category-Theoretic Approach to Resource Optimization. University Mathematics Society, Gainesville, FL.
  16. Fairbanks, J. P., & Leal, W. (2025). Sheaf Cohomology on Simplicial Complexes. CODAC COE, Gainesville, FL.
  17. Leal, W. (2025). Temporal Analysis of Data Using Category Theory and the Hidden Connection Between Persistence and Accumulation. Seminario de Matemáticas Aplicadas, Quantil, Colombia.
  18. Fairbanks, J. P. (2025). Going beyond graphs: simplicial, hyper, and relational structure. JuliaCon, Pittsburgh.
  19. Fairbanks, J. P. (2025). New Approaches in Computational Physics: Multiphysics and Multiscale with Discrete Exterior Calculus. Army Research Lab, Adelphi, MD.
  20. Fairbanks, J. P. (2025). Introduction to Applied Category Theory for Compositional Decision Making. ACC Conference Workshop, Denver, CO.
  21. Fairbanks, J. P. (2025). Compositional Modeling in Applied Category Theory for Compositional Decision Making. ACC Conference Workshop, Denver, CO.
  22. 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.
  23. Hanks, T., & Fairbanks, J. P. (2025). Category Theory for Distributed Optimization. Applied Category Theory [keynote], Gainesville, FL.
  24. Zelko, J., Cuffaro, M., Wu, S., & Fairbanks, J. P. (2025). A Case Study in Public Health Research. Applied Category Theory, Gainesville, FL.
  25. Fairbanks, J. P., & Patterson, E. (2025). AlgebraicJulia Compositional Development of Compositional Mathematics. Applied Category Theory, Gainesville, FL.
  26. Hanks, T., & Fairbanks, J. P. (2025). Multiagent Autonomy with Cellular Sheaves. GTRI ACAI, Atlanta, GA.
  27. Wall, A., & Fairbanks, J. P. (2025). Structured Decompositions. Undergraduate Mathematics Research Symposium, Gainesville, FL.
  28. 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.
  29. Fairbanks, J. P. (2024). A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks. AMS Southeastern Sectional Meeting, Tallahassee, FL.
  30. 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.
  31. Morris, L., & Nathan, E. (2023). Discourse Sheaves for Opinion Dynamics over Social Media Data. Lawrence Livermore National Laboratory Summer SLAM, Livermore, CA.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. Fairbanks, J. P., Morris, L. L., & Rauta, G. (2023). Computational Multiphysics in a Categorical Framework. Applied Category Theory, College Park, MD.
  37. 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.
  38. Fairbanks, J. P. (2023). Decapodes. jl: A Framework for Multiphysics Simulation. MAE Department AFOSR Visit, Gainesville, FL.
  39. 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.
  40. 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.
  41. 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.
  42. 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.
  43. 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.
  44. Fairbanks, J. P. (2022). Scientific and Engineering Modeling with Applied Category Theory. DARPA Young Faculty Colloquium, Arlington, VA.
  45. Fairbanks, J. P., & Patterson, E. (2022). Enkix Task Reasoning. DARPA Site Visit, Gainesville, FL.
  46. Fairbanks, J. P. (2022). Computational Physics Modeling with Categories. Institute of Theoretical Physics, Friedric-Alexander-Universitaet, Erlangen-Nuernberg, Germany.
  47. Libkind, S., & Fairbanks, J. P. (2022). Compositional Modeling of Disease Dynamics. UW-IHME Compositional Epidemiology Modeling Working Group, Online.
  48. Fairbanks, J. P. (2022). Using Category Theory to Design Computational Mathematics Software. Numerical Analysis Seminar at UF Mathematics Department, Gainesville, FL.
  49. Fairbanks, J. P. (2022). Scientific and Engineering Modeling with Applied Category Theory. MAE Department Control Theory Working Group, Gainesville, FL.
  50. Fairbanks, J. P. (2022). Applied Category Theory for the Mathematics of Disease. Canadian Network for Modeling Infectious Disease, Vancouver, Canada.
  51. Fairbanks, J. P., & Patterson, E. (2022). Enkix Task Reasoning. DARPA Site Visit, Gainesville, FL.
  52. Hanks, T. (2022). Compositional Convex Optimization. Air Force Research Laboratory, Rome, NY.
  53. Fairbanks, J. P. (2022). Diagrammatic Equations in Physics: Directly Computable Models. Lawrence Livermore National Laboratory Center for Applied Scientific Computing, Livermore, CA.
  54. Fairbanks, J. P. (2022). Model Aware Scientific Computing with Categories. Air Force Research Laboratory, Rome, NY.
  55. Fairbanks, J. P. (2022). Diagrammatic Equations for Complex Machine Learning Formulations. ONR Code 32 Site Visit, Gainesville, FL.
  56. Fairbanks, J. P. (2022). Introduction to Category Theory. The Simula Corporation, Oslo, NO.
  57. Fairbanks, J. P. (2022). Diagrammatic Equations In Physics, Directly Computable Models. The Simula Corporation, Oslo, NO.
  58. Fairbanks, J. P. (2022). Computational Modeling with Category Theory. Systems Medicine Laboratory Seminar UF College of Medicine, Gainesville, FL.
  59. Fairbanks, J. P. (2022). Scientific Modeling with AlgebraicJulia. Rel.AI Research Seminar, Online.
  60. Fairbanks, J. P., & Lynch, O. (2022). Computational Category Theory in Applied Mathematics. Joint Mathematics Meetings, Boston, MA.
  61. 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.
  62. Bumpus, B. M., & Fairbanks, J. P. (2022). Structured Decompositions: Recursive Data and Recursive Algorithms. Joint Math Meeting, Boston, MA.
  63. Brown, K., & Fairbanks, J. P. (2022). Automated Model Space Exploration. UW-IHME Compositional Epidemiology Modeling Working Group, Online.
  64. 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.
  65. Lynch, O., Patterson, E., & Fairbanks, J. P. (2021). Shaped Data with ACSets. JuliaCon, Online.
  66. Libkind, S., Patterson, E., & Fairbanks, J. P. (2021). Shaped Data with ACSets. JuliaCon, Online.
  67. Fairbanks, J. P., & Patterson, E. (2021). Compositional Modeling with AlgebraicJulia. NIH Interagency Modeling and Analysis Group, Online.
  68. Fairbanks, J. P. (2021). The AlgebraicJulia Ecosystem: a Categorical Approach to Technical Computing. Topos Institute Berkeley Seminar, Berkeley, CA.
  69. Fairbanks, J. P. (2021). Computational Categorical Algebra with Catlab. Graph Transformation Theory and Applications, Paris, FR.
  70. Fairbanks, J. P. (2021). Progress towards the GroMet specification for semantic model exchange. DARPA Automating Scientific Knowledge Extraction Principal Investigator Meeting, Arlington, VA.
  71. Fairbanks, J. P. (2021). Generalized Algebraic Theories for Enhancing Multiphysics: An Introductory Deep Dive. DARPA Directly Computable Models Program Review, Arlington, VA.
  72. Fairbanks, J. P. (2021). Categorical Scientific Knowledge Representation. DARPA Automating Scientific Knowledge Extraction Stakeholder Workshop, Arlington, VA.
  73. Fairbanks, J. P. (2021). Model Aware Computing with Scientific Categories. DARPA Young Investigator Award Principal Investigator Meeting, Arlington, VA.
  74. Fairbanks, J. P. (2021). Introduction to the AlgebraicJulia Software Ecosystem. UF CISE - LLNL Advisory Board Annual Meeting, Gainesville, FL.
  75. Fairbanks, J. P. (2020). Rethinking Set Theory and Computational Mathematics. Undergraduate Math Society, Gainesville, FL.