Publications

This list is the same data as the bibliography table

Journal Articles

12. 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

11. 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

10. 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

9. 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

8. 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

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

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

5. 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.

4. Briscoe, E., & Fairbanks, J. (2020). Artificial scientific intelligence and its impact on national security and foreign policy. Orbis, 64(4), 544–554.

3. Fairbanks, J. P., Bader, D. A., & Sanders, G. D. (2017). Spectral partitioning with blends of eigenvectors. Journal of Complex Networks, 5(4), 551–580.

2. Fairbanks, J. P., Kannan, R., Park, H., & Bader, D. A. (2015). Behavioral clusters in dynamic graphs. Parallel Computing, 47, 38–50.

1. Fairbanks, J. (2011). A Ramsey theorem for indecomposable matchings. arXiv Preprint arXiv:1110.3314.

Conference Proceedings

27. 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 Press. IFAC.

26. Zhao, Y., Hanks, T., Riess, H., Cohen, S., Hale, M., & Fairbanks, J. (2026, May 28). Asynchronous nonlinear sheaf diffusion for multi-agent coordination. Accepted. IEEE American Control Conference, New Orleans, LA.

25. Hanks, T., Nino, C., Barcelo, J. B., Copeland, A., Dixon, W., & Fairbanks, J. (2026, July 8). Heterogeneous Multi-agent multi-target tracking using cellular sheaves. To Appear. European Control Conference.

24. Lary, M., Samuelson, R., Wilentz, A., Zare, A., Klawonn, M., & Fairbanks, J. (2025). Learning diagrams: a graphical language for compositional training regimes. The Thirteenth International Conference on Learning Representations. International Conference on Learning Representations. https://openreview.net/forum?id=dqyuCsBvn9

23. Hanks, T., Riess, H., Cohen, S., Gross, T., Hale, M., & Fairbanks, J. (2025, April 4). Distributed Multi-agent Coordination over Cellular Sheaves. IEEE Conference on Decision and Control. IEEE Conference on Decision and Control. https://doi.org/10.48550/arXiv.2504.02049

22. 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.

21. 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. 2024 American Control Conference (ACC), 4850–4857. https://doi.org/10.23919/ACC60939.2024.10644848

20. Lynch, O., Brown, K., Fairbanks, J., & Patterson, E. (2024). GATlab: Modeling and Programming with Generalized Algebraic Theories. Electronic Notes in Theoretical Informatics and Computer Science, 4. https://oxford24.github.io/assets/mfps-papers/MFPS24-11.pdf

19. 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]. Proceedings of the AAAI Symposium Series, 2, 491–497. https://doi.org/10.1609/aaaiss.v2i1.27718

18. She, B., Hanks, T., Fairbanks, J., & Hale, M. (2023). Characterizing Compositionality of LQR from the Categorical Perspective. 2023 62nd IEEE Conference on Decision and Control (CDC), 1680–1685. https://doi.org/10.1109/CDC49753.2023.10383467

17. Brown, K., Hanks, T., & Fairbanks, J. (2022). Compositional Exploration of Combinatorial Scientific Models. Applied Category Theory. https://doi.org/10.48550/ARXIV.2206.08755

16. Brown, K., Patterson, E., Hanks, T., & Fairbanks, J. (2022). Computational Category-Theoretic Rewriting [Best Paper]. Graph Transformation: 15th International Conference, ICGT 2022, Held as Part of STAF 2022, Nantes, France, July 7–8, 2022, Proceedings, 155–172. https://doi.org/10.1007/978-3-031-09843-7_9

15. 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

14. Fairbanks, J. P., Fitch, N., Bradfield, F., & Briscoe, E. (2020). Credibility Development with Knowledge Graphs. In C. Grimme, M. Preuss, F. W. Takes, & A. Waldherr (Eds.), Lecture Notes in Computer Science (Vol. 12021, pp. 33–47). Springer International Publishing. https://doi.org/10.1007/978-3-030-39627-5_4

13. Halter, M., Herlihy, C., & Fairbanks, J. (2020). A Compositional Framework for Scientific Model Augmentation. Electronic Proceedings in Theoretical Computer Science, 323, 172–182. https://doi.org/10.4204/EPTCS.323.12

12. Cao, K., & Fairbanks, J. (2019). Unsupervised Construction of Knowledge Graphs From Text and Code. SIGKDD Conference on Knowledge Discovery and Data Mining International Workshop on Mining and Learning with Graphs, 15.

11. Nadolski, M., & Fairbanks, J. (2019). Complex systems analysis of hybrid warfare. Procedia Computer Science, 17th Annual Conference on Systems Engineering Research (CSER), 153, 210–217. https://doi.org/10.1016/j.procs.2019.05.072

10. Campbell, N., Goodyear, T., Messer, W., Stuart, E., & Fairbanks, J. (2018). Digital Witness: Remote Method for Volunteering Digital Evidence on Mobile Devices. 2018 IEEE International Symposium on Technologies for Homeland Security (HST), 1–5. https://doi.org/10.1109/THS.2018.8574119

9. Fairbanks, J. P., Fitch, N., Knauf, N., & Briscoe, E. (2018). Credibility Assessment in the News: Do We Need to Read? WSDM/MIS2, 2, 8. https://doi.org/10.1145/3159652.3160597

8. Nathan, E., Fairbanks, J., & Bader, D. (2018). Ranking in Dynamic Graphs Using Exponential Centrality. In C. Cherifi, H. Cherifi, M. Karsai, & M. Musolesi (Eds.), Complex Networks & Their Applications VI (Vol. 689, pp. 378–389). Springer International Publishing. https://doi.org/10.1007/978-3-319-72150-7_31

7. Thankachan, R. V., Swenson, B. P., & Fairbanks, J. P. (2018). Performance Effects of Dynamic Graph Data Structures in Community Detection Algorithms. 2018 IEEE High Performance Extreme Computing Conference (HPEC), 1–7. https://doi.org/10.1109/HPEC.2018.8547528

6. Ediger, D., & Fairbanks, J. P. (2017). Deriving Streaming Graph Algorithms from Static Definitions. 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Graph Algorithms Building Blocks, 637–642. https://doi.org/10.1109/IPDPSW.2017.146

5. 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, International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland, 108, 68–78. https://doi.org/10.1016/j.procs.2017.05.021

4. Thankachan, R. V., Hein, E. R., Swenson, B. P., & Fairbanks, J. P. (2017). Integrating productivity-oriented programming languages with high-performance data structures. 2017 IEEE High Performance Extreme Computing Conference (HPEC), 1–8. https://doi.org/10.1109/HPEC.2017.8091068

3. Fairbanks, J. P., Zakrzewska, A., & Bader, D. A. (2016). New stopping criteria for spectral partitioning. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 25–32. https://doi.org/10.1109/ASONAM.2016.7752209

2. Zakrzewska, A., Nathan, E., Fairbanks, J., & Bader, D. A. (2016). A local measure of community change in dynamic graphs. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 349–353. https://doi.org/10.1109/ASONAM.2016.7752257

1. Fairbanks, J., Ediger, D., McColl, R., Bader, D. A., & Gilbert, E. (2013). A statistical framework for streaming graph analysis. 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013), 341–347. https://doi.org/10.1145/2492517.2492620

Talks and Conference Talks

22. Carlson, K. (2025, April 16). Multigrid Methods for Structure Preserving Discretizations [Talk]. 22ND Copper Mountain Conference on Multigrid Methods, Copper Mountain, CO.

21. Fairbanks, J. (2025, July). Modeling with ACT for Compositional Decision Making [Talk]. American Control Conference, Denver, CO.

20. Fairbanks, J., & Patterson, E. (2025, July). Compositional Development of Compositional Mathematics [Talk]. Applied Category Theory, Gainesville, FL.

19. Fairbanks, J. P., Aduddell, R., Kumar, A., Ocal, P. S., Patterson, E., & Shapiro, B. T. (2024, February). A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks. AMS Southeastern Sectional Meeting, Tallahassee, FL.

18. 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.

17. Fairbanks, J. P., & Lynch, O. (2023). Computational category theory in applied mathematics [Invited]. Joint Mathematics Meetings, Boston, MA.

16. Libkind, S., Baas, A., Halter, M., Patterson, E., & Fairbanks, J. (2022). Typed and stratified models with slice categories. Applied Category Theory, 1–3. https://msp.cis.strath.ac.uk/act2022/papers/ACT2022_paper_3530.pdf

15. 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

14. Patterson, E., Hosgood, T., Baas, A., & Fairbanks, J. (2022, July). Diagrammatic differential equations: Formal categorical framework and applications to multiphysics simulation. Applied Category Theory, Glasgow, UK. https://doi.org/10.3934/mine.2023036

13. Libkind, S., & Fairbanks, J. (2021, July). AlgebraicDynamics: Compositional dynamical systems. JuliaCon, Virtual. https://pretalx.com/juliacon2021/talk/ARURL8/

12. Lynch, O., Patterson, E., & Fairbanks, J. (2021, July). Shaped data with acsets. JuliaCon, Virtual. https://pretalx.com/juliacon2021/talk/NWRPGY/

11. Jackson, M., Halter, M., Goodyear, T., O’Donnell, B., & Fairbanks, J. (2021, September). Accelerating automatic target recognition performance evaluation with a relational database. Tri-Service Radar Symposium.

10. Halter, M., Raparti, S., Cao, K., Herlihy, C., & Fairbanks, J. (2020). SemanticModels. jl: a julia package for scientific model augmentation. Proceedings of the JuliaCon Conferences, 1, Article 1.

9. Halter, M., Patterson, E., Baas, A., & Fairbanks, J. (2020, June 29). Compositional Scientific Computing with Catlab and SemanticModels. Applied Category Theory. http://arxiv.org/abs/2005.04831

8. Herlihy, C., Cao, K., Reparti, S., Briscoe, E., & Fairbanks, J. (2019). Semantic Program Analysis for Scientific Model Augmentation. Modeling the World’s Systems, 7.

7. Herlihy, C., & Fairbanks, J. (2019, July). semanticmodels.jl: Not just another modeling framework. JuliaCon, Baltimore, MD. https://www.youtube.com/watch?v=WJneK7OjqMQ

6. Besançon, M., & Fairbanks, J. (2018). Graph interfaces: Bespoke graphs for every occasion. JuliaCon, London, UK. https://youtu.be/OD-BSn4FZ2A

5. Fairbanks, J. (2018). The JuliaGraphs ecosystem: Move fast and don’t break things. JuliaCon, London, UK. https://youtu.be/OZuQoxTPoyM

4. Bromberger, S., & Fairbanks, J. (2017). LightGraphs: Our network, our story. JuliaCon, Berkeley, CA. https://youtu.be/MFD-qmApXl8

3. 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

2. 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.

1. Bader, D., Michalewicz, A., Green, O., Birkett-Rees, J., Riedy, J., Fairbanks, J., & Zakrzewska, A. (2016, April 2). Semantic database applications at the samtavro cemetery, georgia. The 44th Computer Applications and Quantitative Methods in Archaeology Conference (CAA). The 44th Computer Applications and Quantitative Methods in Archaeology Conference (CAA). https://2016.caaconference.org/session-11-supporting-researchers-in-the-use-and-re-use-of-archaeological-data-continuing-the-ariadne-thread/

Posters

8. Lynch, O., Fairbanks, J. P., & Patterson, E. (2021, June). Graphical semantic modeling with semagrams.jl. Applied Category Theory, Cambridge, UK.

7. Perez, J., Baas, A., Ferrall-Fairbanks, M. C., Platt, M. O., & Fairbanks, J. P. (2021, October). Parameter estimation by minimizing the loss with respect to a finite difference approximation on the vector field. Biomedical Engineering Society Annual Meeting, Orlando, FL.

6. Fairbanks, J. P. (2019, May). Semantic model understanding for scientific model augmentation. Systems Biology of Human Disease, Berlin, DE.

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.

4. Fairbanks, J. P. (2017). QueryGarden: growing healthy applications in well prepared SQL. OHDSI Symposium, New York, NY.

3. 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

2. Fairbanks, J. P. (2015, March). Discovering block structure with approximate eigenvectors. SIAM Computational Science and Engineering.

1. Fairbanks, J. P. (2012). Ramsey theorem for indecomposable matchings. Graph Theory at Georgia Tech (GT@GT), Atlanta, GA.

Preprints

5. Arlin, K., Fairbanks, J., Hosgood, T., & Patterson, E. (2024). The diagrammatic presentation of equations in categories. arXiv Preprint 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 Preprint arXiv:2407.03488.

3. Bumpus, B. M., Fairbanks, J., & Turner, W. J. (2024). Pushing Tree Decompositions Forward Along Graph Homomorphisms (arXiv:2408.15184). 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:2403.05711). arXiv. https://doi.org/10.48550/arXiv.2403.05711

1. Althaus, E., Bumpus, B. M., Fairbanks, J., & Rosiak, D. (2023). Compositional Algorithms on Compositional Data: Deciding Sheaves on Presheaves (arXiv:2302.05575). arXiv. https://doi.org/10.48550/arXiv.2302.05575

Talks Extremely Comprehensive List

75. Hanks, T., & Fairbanks, J. P. (2026, January 1). Coordination Sheaves. Core Lab Georgia Tech, Atlanta.

74. Hanks, T., Klawonn, M., Patterson, E., Hale, M., & Fairbanks, J. P. (2026, January 1). Categorical Foundations of Distributed Optimization and Learning. AMS Special Session on Mathematical Foundation of Machine Learning, Joint Mathematics Meeting, Washington DC.

73. Bou Barcelo, J., & Fairbanks, J. P. (2026, March 20). Heterogeneous Multi-Agent Multi-Target Tracking. INFORMS Optimization Society Conference, Atlanta, GA.

72. Gross, T., & Fairbanks, J. P. (2026, April 1). Quadrotor Coordination Using Cellular Sheaves and Linearized LQR. Center for Undergraduate Research Spring Symposium, Gainesville, FL, USA.

71. Hanks, T., Reiss, H., Cohen, S., Gross, T., Hale, M., & Fairbanks, J. P. (2026, April 1). Distributed Multi-Agent Coordination over Cellular Sheaves. AMS Special Session on Applied Category Theory Joint Mathematics Meeting, Washington DC.

70. Cohen, S., & Fairbanks, J. P. (2026, April 6). Federated Learning with Cellular Sheaves. UF Undergraduate Research Symposium, Gainesville, FL.

69. Rauta, G., Fairbanks, J. P., & Kuzendorf, W. (2026, April 15). Low-Mach Compressible Navier-Stokes Using Discrete Exterior Calculus on Rectilinear Grids. WCCM-ECCOMAS [accepted], Munich, Germany.

68. Fairbanks, J. P. (2026, May 27). Compositional Modeling: Structures, Dynamics, Optimization. American Control Conference, New Orleans, LA.

67. Fairbanks, J. P. (2026, May 27). Panel on Applied Category Theory for Compositional Decision Making. American Control Conference, New Orleans, LA.

66. Fairbanks, J. P., & Kim, N. (2025, February 13). T6: Validation, Uncertainty Quantification, Uncertainty Budget, Workflow and Data Management. CM3C: Center for Multiscale Modeling of Multiphase Combustion, Gainesville, FL.

65. Wall, A., & Fairbanks, J. P. (2025, May 1). Structured Decompositions. Undergraduate Mathematics Research Symposium, Gainesville, FL.

64. Hanks, T., & Fairbanks, J. P. (2025, May 20). Multiagent Autonomy with Cellular Sheaves. GTRI ACAI, Atlanta, GA.

63. Fairbanks, J. P., & Patterson, E. (2025, June 2). AlgebraicJulia Compositional Development of Compositional Mathematics. Applied Category Theory, Gainesville, FL.

62. Zelko, J., Cuffaro, M., Wu, S., & Fairbanks, J. P. (2025, June 2). A Case Study in Public Health Research. Applied Category Theory, Gainesville, FL.

61. Hanks, T., & Fairbanks, J. P. (2025, June 3). Category Theory for Distributed Optimization. Applied Category Theory [keynote], Gainesville, FL.

60. Rauta, G., & Fairbanks, J. P. (2025, July 1). Modeling of Coupled Weakly Compressible Navier-Stokes and Thermal Equation in the Discrete Exterior Calculus. Army Research Lab Poster Session, Adelphi, MD.

59. Fairbanks, J. P. (2025, July 2). Compositional Modeling in Applied Category Theory for Compositional Decision Making. ACC Conference Workshop, Denver, CO.

58. Fairbanks, J. P. (2025, July 6). Introduction to Applied Category Theory for Compositional Decision Making. ACC Conference Workshop, Denver, CO.

57. Fairbanks, J. P. (2025, July 22). New Approaches in Computational Physics: Multiphysics and Multiscale with Discrete Exterior Calculus. Army Research Lab, Adelphi, MD.

56. Fairbanks, J. P. (2025, July 24). Going beyond graphs: simplicial, hyper, and relational structure. JuliaCon, Pittsburgh.

55. Leal, W. (2025, August 1). Temporal Analysis of Data Using Category Theory and the Hidden Connection Between Persistence and Accumulation. Seminario de Matemáticas Aplicadas, Quantil, Colombia.

54. Fairbanks, J. P., & Leal, W. (2025, August 15). Sheaf Cohomology on Simplicial Complexes. CODAC COE, Gainesville, FL.

53. Wall, A., & Fairbanks, J. P. (2025, September 1). A Category-Theoretic Approach to Resource Optimization. University Mathematics Society, Gainesville, FL.

52. Fairbanks, J. P. (2025, October 1). Building Modeling and Simulation Tools on Discrete Exterior Calculus Foundations. IMSI workshop on Discrete Exterior Calculus Differential Geometry and Applications, Chicago, Ill.

51. Fairbanks, J. P., & Leal, W. (2025, October 1). Computing Fixed Points of CTLNs with Separated Presheaves, Sheaves and Dynamic Programming. Category Theory Octoberfest 2025, Online.

50. Fairbanks, J. P., & Leal, W. (2025, November 1). Sheaves in Time Varying Data and Dynamical Systems. NCR Lab UF MAE Department, Gainesville, FL.

49. Leal, W., & Fairbanks, J. P. (2025, November 1). Sheaves in Dynamical Systems: Enumerating Fixed Points of CTLNs. Kallies Research Group, Toledo, OH.

48. Fairbanks, J. P., & Zare, A. (2025, December 10). Domain Transfer for Continuity of Performance Across SAS Systems ​. ONR Code 32 Program Review, Online.

47. Fairbanks, J. P. (2024, March 23). A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks. AMS Southeastern Sectional Meeting, Tallahassee, FL.

46. Bumpus, B. M. (2023, January 1). 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.

45. Bumpus, B. M., & Fairbanks, J. P. (2023, January 1). Chopping things up to decide stuff fast. 54th Southeastern International Conference on Combinatorics Graph Theory and Computing, Boca Raton, FL.

44. Morris, L. L., Baas, A., Fairbanks, J. P., Arias, J., & Gaitlin, M. (2023, January 1). Abstraction and Composition in Modeling and Simulation. Graduate Mathematics Association, Gainesville, FL.

43. Fairbanks, J. P., Morris, L. L., & Rauta, G. (2023, January 20). Categorical Composition of Discrete Exterior Calculus Climate Models. Programming for the Planet (PROPL) at POPL, London, UK.

42. Morris, L. L., Baas, A., Fairbanks, J. P., Arias, J., & Gaitlin, M. (2023, February 26). Abstraction and Composition in Modeling and Simulation. SIAM Conference on Computational Science and Engineering, Amsterdam, NL.

41. Fairbanks, J. P. (2023, March 1). Decapodes. Jl: A Framework for Multiphysics Simulation. MAE Department AFOSR Visit, Gainesville, FL.

40. Fairbanks, J. P., Hanks, T., She, B., Hale, M., Patterson, E., & Klawonn, M. (2023, April 1). A Compositional Framework for Model Predictive Control. AFOSR Center of Excellence Program Review, Gainesville, FL.

39. Fairbanks, J. P., Morris, L. L., & Rauta, G. (2023, July 21). Computational Multiphysics in a Categorical Framework. Applied Category Theory, College Park, MD.

38. Bumpus, B. M., Fairbanks, J. P., Rosiak, D., & Althaus, E. (2023, July 31). Compositional Algorithms on Compositional Data: Deciding Sheaves on Presheaves. Applied Category Theory, College Park, MD.

37. Fairbanks, J. P., Hanks, T. E., She, B., Patterson, E., Hale, M., & Klawonn, M. (2023, July 31). A Compositional Framework for Convex Model Predictive Control. Applied Category Theory, College Park, MD.

36. Libkind, S., Bumpus, B. M., Garcia, J. L., Sorkatti, L. H., & Tenka, S. (2023, July 31). Additive Invariants of Open Petri Nets. Applied Category Theory, College Park, MD.

35. Lynch, O., Brown, K., Fairbanks, J. P., & Patterson, E. (2023, July 31). Gatlab. Jl: Symbolic computing with categories using generalized algebraic theories. Applied Category Theory, College Park, MD.

34. Morris, L., & Nathan, E. (2023, August 1). Discourse Sheaves for Opinion Dynamics over Social Media Data. Lawrence Livermore National Laboratory Summer SLAM, Livermore, CA.

33. Morris, L. L., Baas, A., Fairbanks, J. P., Arias, J., & Gaitlin, M. (2023, September 1). Abstraction and Composition in Modeling and Simulation. Mechanical and Aerospace Engineering Seminar, Gainesville, FL.

32. Brown, K., & Fairbanks, J. P. (2022, January 1). Automated Model Space Exploration. UW-IHME Compositional Epidemiology Modeling Working Group, Online.

31. Bumpus, B. M., & Fairbanks, J. P. (2022, January 4). Structured Decompositions: Recursive Data and Recursive Algorithms. Joint Math Meeting, Boston, MA.

30. Fairbanks, J. P., Aduddell, R., Ocal, P. S., Patterson, E., Shapiro, B., & Kumar, A. (2022, January 4). A Categorical Framework for (Gene) Regulatory Networks. Joint Mathematics Meeting, Boston, MA.

29. Fairbanks, J. P., & Lynch, O. (2022, January 4). Computational Category Theory in Applied Mathematics. Joint Mathematics Meetings, Boston, MA.

28. Fairbanks, J. P. (2022, March 1). Scientific Modeling with AlgebraicJulia. Rel.AI Research Seminar, Online.

27. Fairbanks, J. P. (2022, May 1). Computational Modeling with Category Theory. Systems Medicine Laboratory Seminar UF College of Medicine, Gainesville, FL.

26. Fairbanks, J. P. (2022, May 1). Diagrammatic Equations In Physics, Directly Computable Models. The Simula Corporation, Oslo, NO.

25. Fairbanks, J. P. (2022, May 1). Introduction to Category Theory. The Simula Corporation, Oslo, NO.

24. Fairbanks, J. P. (2022, June 1). Diagrammatic Equations for Complex Machine Learning Formulations. ONR Code 32 Site Visit, Gainesville, FL.

23. Fairbanks, J. P. (2022, June 1). Diagrammatic Equations in Physics: Directly Computable Models. Lawrence Livermore National Laboratory Center for Applied Scientific Computing, Livermore, CA.

22. Fairbanks, J. P. (2022, June 1). Model Aware Scientific Computing with Categories. Air Force Research Laboratory, Rome, NY.

21. Fairbanks, J. P. (2022, August 1). Applied Category Theory for the Mathematics of Disease. Canadian Network for Modeling Infectious Disease, Vancouver, Canada.

20. Fairbanks, J. P., & Patterson, E. (2022, August 1). Enkix Task Reasoning. DARPA Site Visit, Gainesville, FL.

19. Hanks, T. (2022, August 1). Compositional Convex Optimization. Air Force Research Laboratory, Rome, NY.

18. Fairbanks, J. P. (2022, August 21). Scientific and Engineering Modeling with Applied Category Theory. MAE Department Control Theory Working Group, Gainesville, FL.

17. Fairbanks, J. P. (2022, September 1). Using Category Theory to Design Computational Mathematics Software. Numerical Analysis Seminar at UF Mathematics Department, Gainesville, FL.

16. Libkind, S., & Fairbanks, J. P. (2022, September 1). Compositional Modeling of Disease Dynamics. UW-IHME Compositional Epidemiology Modeling Working Group, Online.

15. Fairbanks, J. P. (2022, October 1). Computational Physics Modeling with Categories. Institute of Theoretical Physics, Friedric-Alexander-Universitaet, Erlangen-Nuernberg, Germany.

14. Fairbanks, J. P. (2022, November 1). Scientific and Engineering Modeling with Applied Category Theory. DARPA Young Faculty Colloquium, Arlington, VA.

13. Fairbanks, J. P., & Patterson, E. (2022, November 1). Enkix Task Reasoning. DARPA Site Visit, Gainesville, FL.

12. Fairbanks, J. P. (2021, February 1). Introduction to the AlgebraicJulia Software Ecosystem. UF CISE - LLNL Advisory Board Annual Meeting, Gainesville, FL.

11. Fairbanks, J. P. (2021, February 4). Model Aware Computing with Scientific Categories. DARPA Young Investigator Award Principal Investigator Meeting, Arlington, VA.

10. Fairbanks, J. P. (2021, February 12). Categorical Scientific Knowledge Representation. DARPA Automating Scientific Knowledge Extraction Stakeholder Workshop, Arlington, VA.

9. Fairbanks, J. P. (2021, March 1). Generalized Algebraic Theories for Enhancing Multiphysics: An Introductory Deep Dive. DARPA Directly Computable Models Program Review, Arlington, VA.

8. Fairbanks, J. P. (2021, March 25). Progress towards the GroMet specification for semantic model exchange. DARPA Automating Scientific Knowledge Extraction Principal Investigator Meeting, Arlington, VA.

7. Fairbanks, J. P. (2021, May 1). Computational Categorical Algebra with Catlab. Graph Transformation Theory and Applications, Paris, FR.

6. Fairbanks, J. P. (2021, June 1). The AlgebraicJulia Ecosystem: a Categorical Approach to Technical Computing. Topos Institute Berkeley Seminar, Berkeley, CA.

5. Fairbanks, J. P., & Patterson, E. (2021, July 8). Compositional Modeling with AlgebraicJulia. NIH Interagency Modeling and Analysis Group, Online.

4. Libkind, S., Patterson, E., & Fairbanks, J. P. (2021, July 28). Shaped Data with ACSets. JuliaCon, Online.

3. Lynch, O., Patterson, E., & Fairbanks, J. P. (2021, July 28). Shaped Data with ACSets. JuliaCon, Online.

2. Fairbanks, J. P., Perez, J., Baas, A., Ferrall-Fairbanks, M., & Platt, M. O. (2021, October 6). Parameter Estimation by Minimizing the Loss with Respect to a Finite Difference Approximation on the Vector Field. Biomedical Engineering Society Annual Meeting, Orlando, FL.

1. Fairbanks, J. P. (2020, March 10). Rethinking Set Theory and Computational Mathematics. Undergraduate Math Society, Gainesville, FL.