Brennan Klein, PhD

My research program is shaped by two drives: First, to develop tools, theory, and models that capture and explore the rich complexity in our natural and mathematical world. Second, to use tools and insights from Complex Systems and Network Science to document—and fight against—emergent or systemic disparities across society, especially as they relate to public health and public safety.

Complex systems are able to represent, predict, and intervene on their surroundings at a number of different scales—all in ways that appear to maintain the statistical boundary between them and their environment. These dynamics fascinate me, and they inform my research across a variety of domains, from decision making, to experimental design, to causation and emergence in networks.

I received a BA in Cognitive Science and Psychology from Swarthmore College in 2014, studying the relationship between perception, action, and cognition. I received my PhD in Network Science from Northeastern University in 2020. I make art under the pseudonym JK Rofling.

Affiliations

Northeastern University

Associate Research Scientist. Sep. 2023 — present. Boston, MA.

• at the Network Science Institute, with a joint appointment at the Institute for Experiential AI.

• director of the Complexity & Society Lab (the “And Lab”).

Harvard University

Data for Justice Fellow. Jul. 2022 — present. Cambridge, MA.

• at the Institute on Policing, Incarceration & Public Safety, in The Hutchins Center for African & African American Research.

Preprints/working papers

1. Sabhahit, N.G., Laber, M., Hartle, H., van der Kolk, J. Scarpino, S.V., Klein, B., & Krioukov, D. (in prep). Deterministic construction of typical graphs in network models.

Published works

2024

1. Klein, B., Hartle, H., Shrestha, M., Zenteno, A.C., Barros Sierra Cordera, D., Nicolás-Carlock, J.R., Bento, A.I., Althouse, B., Gutierrez, B., Escalera-Zamudio, M., Reyes-Sandoval, A., Pybus, O., Vespignani, A., Díaz-Quiñonez, J.A., Scarpino, S.V., & Kraemer, M.U.G. (2024). Spatial scales of COVID-19 transmission in Mexico. PNAS Nexus, pgae306. doi: 10.1093/pnasnexus/pgae306.

2. Demekas, D., Heins, C., & Klein, B. (2024). An analytical model of active inference in the Iterated Prisoner’s Dilemma. In: Buckley, C.L., et al. Active Inference. IWAI 2023; Ghent, Belgium. Communications in Computer and Information Science, vol 1915. Springer, Cham. doi: 10.1007/978-3-031-47958-8_10.

3. Klein, B., LaRock, T., McCabe, S., Torres, L., Friedland, L., Privitera, F., Lake, B., Kraemer, M.U.G., Brownstein, J.S., Gonzalez, R., Lazer, D., Eliassi-Rad, T., Scarpino, S.V., Vespignani, A., & Chinazzi, M. (2024). Characterizing the collective physical distancing of the United States during the first nine months of the COVID-19 pandemic. PLOS Digital Health 3(2): e0000430. doi: 10.1371/journal.pdig.0000430.

   • Version 1 of report here. Version 2 of report here. Mobility and contact patterns in the United States dashboard here.

4. Friston, K.J., Ramstead, M.J., Kiefer, A.B., Tschantz, A., Buckley, C.L., Albarracin, M., Pitliya, R.J., Heins, C., Klein, B., Millidge, B., Sakthivadivel, D.A., St Clere Smithe, T., Koudahl, M., Tremblay, S.E., Petersen, C., Fung, K., Fox, J.G., Swanson, S., Mapes, D., & René, G. (2024). Designing ecosystems of intelligence from first principles. Collective Intelligence, 3(1). doi: 10.1177/26339137231222481.

2023

1. Klein, B. (2023). A consolidated framework for quantifying interaction dynamics. News & Views commentary, Nature Computational Science. 2662-8457. doi: 10.1038/s43588-023-00520-4.

2. Klein, B., Ogbunugafor, C.B., Schafer, B.J., Bhadricha, Z., Kori, P., Sheldon, J., Kaza, N., Sharma, A., Wang, E.A., Eliassi-Rad, T., Scarpino, S.V. & Hinton, E. (2023). COVID-19 amplified racial disparities in the U.S. criminal legal system. Nature. 616(7957). doi: 10.1038/s41586-023-05980-2.

3. Ramstead, M.J.D., Sakthivadivel, D.A.R., Heins, C., Koudahl, M.T., Millidge, B., Da Costa, L., Klein, B., & Friston, K. (2023). On Bayesian mechanics: A physics of and by beliefs. Royal Society Interface Focus issue on Making and Breaking Symmetries in Mind and Life. 13(3): 20220029. doi: 10.1098/rsfs.2022.0029.

4. Heins, C., Klein, B., Demekas, D., Aguilera, M., & Buckley, C.L. (2023). Spin glass systems as collective active inference. 3rd International Workshop on Active Inference (IWAI). Grenoble, France, with ECML/PKDD. Springer Cham. ISSN: 1865-0929. Recipient: Best paper award. doi: 10.1007/978-3-031-28719-0_6.

5. Klein, B., Zenteno, A.C., Joseph, D., Zahedi, M., Hu, M., Copenhaver, M., Kraemer, M.U.G., Chinazzi, M., Klompas, M., Vespignani, A., Scarpino, S.V., & Salmasian, H. (2023). Forecasting hospital-level COVID-19 admissions using real-time mobility data. Communications Medicine. 3(25). doi: 10.1038/s43856-023-00253-5.

2022

1. Rissaki, A., Scarone, B., Liu, D., Pandey, A., Klein, B., Eliassi-Rad, T., & Borkin, M. (2022). BiaScope: Visual Unfairness Diagnosis for Graph Embeddings. 2022 IEEE Visualization in Data Science (VDS), Oklahoma City, OK, USA, 2022 pp. 27-36. doi: 10.1109/VDS57266.2022.00008.

2. Klein, B., Generous, N., Chinazzi, M., Bhadricha, Z., Gunashekar, R., Kori, P., Li, B., McCabe, S., Green, J., Lazer, D., Marsicano, C., Scarpino, S.V., & Vespignani, A. (2022). Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy. PLOS Digital Health. 1(6): e0000065. doi: 10.1371/journal.pdig.0000065.

3. Heins, R., Millidge, B., Demekas, D., Klein, B., Friston, K., Couzin, I., & Tschantz, A. (2022) pymdp: A Python library for active inference in discrete state spaces. Journal of Open Source Software. 7 (73), 4098. doi: 10.21105/joss.04098. Open review: joss-reviews/issues/4098. Extended tutorial on arXiv: 2201.03904.

4. Klein, B. & Harris, D.A. (2022). Letter to the Editor: Examining the robustness of 3ft versus 6ft of physical distancing in schools: A reanalysis of van den Berg et al. (2021). Clinical Infectious Diseases. 1058-4838. doi: 10.1093/cid/ciac187.

5. Klein, B., Swain, A., Byrum, T., Scarpino, S.V., & Fagan, W. (2022). Exploring noise, degeneracy and determinism in biological networks with the einet package. Methods in Ecology and Evolution. doi: 10.1111/2041-210X.13805.

2021

1. Klein, B., Hoel, E., Swain, A., Griebenow, R., & Levin, M. (2021). Evolution and emergence: Higher order information structure in protein interactomes across the tree of life. Integrative Biology. zyab020. doi: 10.1093/intbio/zyab020.

2. Klein, B., Holmér, L., Smith, K., Johnson, M., Swain, A., Stolp, L., Teufel, A., & Kleppe, A. (2021). A computational exploration of resilience and evolvability of protein-protein interaction networks. Nature Communications Biology. 4, 1352. doi: 10.1038/s42003-021-02867-8.

3. Balietti, S., Klein, B., & Riedl, C. (2021). Optimal design of experiments to identify latent behavioral types. Experimental Economics. 24, 772--799. doi: 10.1007/s10683-020-09680-w.

4. Kraemer, M.U.G., Hill, V., Ruis, C., Dellicour S., Bajaj, S., McCrone, J., Baele G., Parag, K.V., Lindstrom Battle, A., Gutierrez, B., Jackson, B., Colquhoun, R., O’Toole, Á., Klein, B., Vespignani, A., The COVID-19 Genomics UK (CoG-UK) consortium, Volz, E., Faria, N.R., Aanensen, D., Loman, N.J., du Plessis, L., Cauchemez, S., Rambaut A., Scarpino, S.V., & Pybus, O.G. (2021). Spatio-temporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence. Science. 368 (6490), 493--497. doi: 10.1126/science.abj0113.

5. McCabe, S., Torres, L., LaRock, T., Haque, S.A., Yang, C-H., Hartle, H., & Klein, B. (2021). netrd: A library for network reconstruction and graph distances. Journal of Open Source Software. 6(62), 2990. doi: 10.21105/joss.02990. Open review: joss-reviews/issues/2990.

6. Nande, A., Sheen, J., Walters, E.L., Klein, B., Chinazzi, M., Gheorghe, A., Adlam, B., Shinnick, J., Tejeda, M.F., Scarpino, S.V., Vespignani, A., Greenlee, A.J., Schneider, D., Levy, M.Z., & Hill, A.L. (2021). The effect of eviction moratoria on the transmission of SARS-CoV-2. Nature Communications. 12 (2274) 1--13. doi: 10.1038/s41467-021-22521-5.

2020

1. Hartle, H., Klein, B., McCabe, S., Daniels, A., St-Onge, G., Murphy, C., & Hébert-Dufresne, L. (2020). Network comparison and the within-ensemble graph distance. Proceedings of the Royal Society A, 476, 20190644. Included in special feature: A Generation of Network Science doi: 10.1098/rspa.2019.0744.

2. T Byrum, T., Swain, A., Klein, B., & Fagan, W. (2020). einet: Effective information and causal emergence. R package version 0.1.0. https://CRAN.R-project.org/package=einet.

3. Klein, B. & Hoel, E. (2020). The emergence of informative higher scales in complex networks. Complexity. 8932526, 12 pages. doi: doi.org/10.1155/2020/8932526.

4. Kraemer, M.U.G., Yang, C-H., Gutierrez, B., Wu, C-H., Klein, B., Pigott, D.M., du Plessis, L., Faria, N.R., Li, R., Hanage, W.P., Brownstein, J.S., Layan, M., Vespignani, A., Tian, H., Dye, C., Pybus, O.G., & Scarpino, S.V. (2020). The effect of human mobility and control measures on the COVID-19 epidemic in China. Science. 368 (6490), 493--497. doi: doi.org/10.1126/science.abb4218.

2017

1. Pilny, A., Poole, M. S., Reichelmann, A., & Klein, B. (2017). A structurational group decision-making perspective on the commons dilemma: results from an online public goods game. Journal of Applied Communication Research, 45(4), 413–428. doi: 10.1080/00909882.2017.1355559.

2016

1. Klein, B., Li, Z. & Durgin, F.H. (2016). Large perceptual distortions of locomotor action space occur in ground-based coordinates: Angular expansion and the large-scale horizontal-vertical illusion. Journal of Experimental Psychology: Human Perception and Performance, 42(4), 581. doi: 10.1037/xhp0000173.

2013

1. Durgin, F. H., Klein, B., Spiegel, A., Strawser, C. J., & Williams, M. (2013). The social psychology of perception experiments: Hills, backpacks, glucose and the problem of generalizability. Journal of Experimental Psychology: Human Perception and Performance, 39(2), 477. doi: 10.1037/a0027805.

2012

1. Li, Z., Sun, E., Strawser, C. J., Spiegel, A., Klein, B., & Durgin, F. H. (2012). On the anisotropy of perceived ground extents and the interpretation of walked distance as a measure of perception. Journal of Experimental Psychology: Human Perception and Performance, 38(6), 1582. doi: 10.1037/a0029405.

• PHYS 7332 - Network Science Data II - Fall 2024

• PHYS 5116 - Complex Networks and Applications - Fall 2024 (previous editions: Fall 2022, Fall 2023)

• NETS 7976 - Causal Inference with Network Interference - Fall 2024

• NETS 8941 - Network Science Literature Review (previous editions: Spring 2022, Spring 2023, Spring 2024)

• NETS 7976 - Network Reconstruction and Inference from Dynamics (previous editions: Spring 2024)

• NETS 7976 - Reasoning Under Uncertainty with Probabilistic Machine Learning (previous editions: Fall 2023)

• NETS 7976 - Information Theory & Bayesian Inference for Complex Systems (previous editions: Fall 2022)

Fellowship opportunities

• Pymdp Fellowship: A new fellowship opportunity for early career researchers in the Active Inference community. The goal of the fellowship is to expand the use and development of the pymdp software package, by awarding researchers $3,200 USD for short-term research or development sprints that advance functionality and applications of pymdp.

  • Stay tuned for information about applying to be a part of the second cohort of fellows!

Complexity & Society Lab

(website in progress)