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Professor of Sociology in the Department of SociologyB2, 32 Old Elvet 
DRMC Director in the Faculty of Social Sciences and Health  
Fellow in the Durham Research Methods Centre  
Fellow of the Wolfson Research Institute for Health and Wellbeing  


  • My areas of research are:
    • case-based complexity and computational modelling
    • the complexities of place and health
    • complexity and psychology, including cognition, emotions and consciousness
    • configurational complexity theory
    • complexity methods for policy evaluation
    • big data and digital sociology
    • CLICK HERE for links to all publications, grants and invites.
  • THEORY: Configurational complexity theory and method: Over the past fifteen years I have been developing a theoretical and methodological framework for studying social complexity, which is based on a case-based configurational approach. In particular, I am focused on how social science theory informs the insights of complexity science, as in the case of power relations, inequality, and human psychology. 
  • PSYCHOLOGY AND COMPLEXITY: I have been developing a theoretical framework for stitching together research on embodied cognition, emotion, and consciousness, from cells and bacteria to the dynamic unconscious and the self to nonconscious machine cognition. Currently I am applying this work to two topics -- the impact air pollution has on brain health and the role collective psychology plays in civil society.
  •  METHOD: case-based computational modelling: I have spent the past ten years developing a new case-based, data-mining approach to modeling complex social systems – called the SACS Toolkit – which my colleagues and I have used to help researchers, policy makers and service providers address and improve complex public health issues such as community health and well-being; infrastructure and grid reliability; mental health and inequality; big data and data mining; and globalization and global civil society.
  • We have also recently developed Durham COMPLEX-IT, an R-studio software app, which provides policy evaluators (and those working in health, food, environment and social service sectors) seamless access to such high-powered techniques as machine intelligence, neural nets, and agent-based modeling to make better sense of the complex world(s) in which they live and work. It is freely downloadable and soon to be developed into an online version.
  • APPLICATION: case-based, policy evaluation and air pollution and public health: Through my work with CECAN (Centre for the Evaluation of Complexity Across the Nexus), my applied work presently has two foci: helping to improve policy evaluation, particularly in terms of public health; and also geospatially and temporally modelling the complex link between air pollution in the UK and public health, in particular cognitive wellbeing.

CLICK HERE to read my blog on all things complexity.


Research interests

  • Complexities of place and health
  • Case-based complexity and computational modelling
  • Complexity and psychology, including cognition, emotions, and consciousness
  • Configurational complexity theory
  • Big data and digital sociology
  • Complexity methods for policy evaluation

Research groups

  • Health and Social Theory

Awarded Grants

  • 2020: 2020: RF200182: PI InSPIRE - Consortium Development Grant, UKPRP (MRC). 2020-05-01 - 2020-12-17, £41k
  • 2020: 2020: RF200186: Early Warning Scores: Modelling Care in Response to the COVID-19 Pandemic, MRC, £39.7k
  • 2020: RG200004: PI Exploring the Complex Policy Landscape Around Air Pollution and Public Health: A 2-Day Workshop, 2020-03-05 - 2020-03-06, £15k
  • 2019: 2019: RF200166 Co-I. CECAN - Centre for the Evaluation of Complexity Across the Nexus. PI: Prof. Nigel Gilbert. ESRC. 2019-03-01 - 2022-02-28. £3.8mil
  • 2019: RI200179: Co-I Agent-Based Modelling Covid-19, ESRC Centre for Social and Economic Research on Innovation in Genomics (INNOGEN), 2019-04-01 - 2020-03-30, £16.1k
  • 2019: RT200146: Co-I Motivation and Complexity, Leverhulme Trust, 2019-10-01 - 2022-09-30, £112.1k
  • 2018: RI200008: PI DURHAM COMPLEX-IT: A web-based computational modelling and visualisation platform and learning environment for evaluating public policy and services, ESRC Centre for Social and Economic Research on Innovation in Genomics (INNOGEN), 2018-11-2

Media Contacts

Available for media contact about:

  • Human impact:
  • Pollution:
  • Drink & drugs:
  • Public policy, health and well-being:
  • Statistics:
  • Politics & Society:
  • Psychology:
  • Sociology:


Authored book

  • Castellani, B & Rajaram, R (2021). Big Data Mining and Complexity. SAGE.
  • Castellani, Brian (2018). The Defiance of Global Commitment: A Complex Social Psychology. Abingdon, Oxon: Routledge.
  • Castellani, Brian, Rajaram, Rajeev, Buckwalter, J Galen, Ball, Michael & Hafferty, Frederic (2015). Place and health as complex systems: A case study and empirical test. Springer.
  • Castellani, Brian & Hafferty, Frederic William (2009). Sociology and complexity science: a new field of inquiry. Springer Complexity Series.
  • Castellani, Brian (2000). Pathological gambling: The making of a medical problem. Suny Press.

Book review

  • Castellani, Brian (2016). The Value of Systems and Complexity Sciences for Healthcare. Journal of Artificial Societies and Social Simulation 19(4).
  • Castellani, Brian (2013). Moreira, T. The Transformation of Contemporary Health Care: The Market, the Laboratory, and the Forum. London: Routledge. 2012.(hbk) vii+ 181 pp. ISBN 13: 978-0-415-88600-0. Sociology of Health \& Illness 35(3): 496-497.
  • Castellani, Brian (2012). Review of Social Understanding: On Hermeneutics, Geometrical Models and Artificial Intelligence (Theory and Decision Library A:).
  • Castellani, Brian (2010). Review of Mind \& Society: Special Issue on Social Simulation, Volume 8, Number 2, 2009.

Chapter in book

  • Castellani,B (2020). The Complex Global Crisis of Population and Public Health. In Complex Systems and Population Health: A Primer. Apostolopoulos, Lich & Lemke Oxford University Press.
  • Dister, Carl J., Castellani, Brian & Rajaram, Rajeev (2018). Modeling social complexity in infrastructures: a case-based approach to improving reliability and resiliency. In Handbook of Research Methods in Complexity Science: Theory and Applications. Mitleton-Kelly, Eve, Paraskevas, Alexandros & Day, Christopher Cheltenham: Edward Elgar Publishing. 267-284.
  • Castellani, Brian, Rajaram, Rajeev, Buckwalter, J Galen, Ball, Michael & Hafferty, Frederic (2015). Case-Based Modeling and the SACS Toolkit. In Place and Health as Complex Systems. Springer, Cham. 15-26.
  • Castellani, Brian, Schimpf, Corey & Hafferty, Frederic (2012). Medical Sociology and Case-Based Complexity Science: A User’s Guide. In Handbook of Systems and Complexity in Health. 521.
  • Hafferty, Frederic W & Castellani, Brian (2011). Two cultures: Two ships: The rise of a professionalism movement within modern medicine and medical sociology’s disappearance from the professionalism debate. In Handbook of the sociology of health, illness, and healing. Springer, New York, NY. 201-219.
  • Hafferty,F & Castellani,B (2009). The Hidden Curriculum: A Theory of Medical Education. In Handbook of the Sociology of Medical Education. Brosnan,C & Turner,B Routledge. 15-38.
  • Hafferty, Frederic W & Castellani, Brian (2007). Theories of Social Relations. In The behavioral sciences and health care (2nd rev. and updated). Hogrefe \& Huber. 123-129.
  • Castellani, B. & Hafferty, F.W. (2006). The complexities of medical professionalism a preliminary investigation. In Professionalism in Medicine: Critical Perspectives. Springer. 3-23.
  • Hafferty, Frederic W & Castellani, Brian (2006). Medical sociology. In Handbook of twenty-first century sociology. Sage. 331-338.
  • Castellani, John & Castellani, Brian (2005). Data-mining strategies for researching the effectiveness of assistive and instructional technologies. In Handbook of Special Education Technology Research and Practice. Knowledge by Design.
  • Castellani,J & Castellani,B (2004). Data Mining Process and Analysis Strategies for Special Education Technology Decision-Making. In Handbook of Special Education Technology. Edyburn,D, Higgins,K & Boone,R Knowledge by Design, Inc.

Conference Proceeding

  • Aitchison, Katherine J, Castellani, Brian, Chapman, Craig S, Christensen, Darren R, Crawford, Sandy, Currie, Cheryl, Downs, Carolyn, Euston, David, Forrest, David, Goodyear, Bradley G & others (2014). Controversial Topics in Gambling: Alberta Gambling Research Institute's 13th Annual Conference. Various.

Journal Article

  • Badham, Jennifer, Barbrook-Johnson, Pete, Caiado, Camila & Castellani, Brian (2021). Justified Stories with Agent-Based Modelling for Local COVID-19 Planning. Journal of Artificial Societies and Social Simulation 24(1): 8.
  • Schimpf, Corey, Barbrook-Johnson, Pete & Castellani, Brian (2021). Cased-based modelling and scenario simulation for ex-post evaluation. Evaluation 27(1): 116-137.
  • Barbrook-Johnson, Pete, Castellani, Brian, Hills, Dione, Penn, Alexandra & Gilbert, Nigel (2021). Policy evaluation for a complex world: Practical methods and reflections from the UK Centre for the Evaluation of Complexity across the Nexus. Evaluation 27(1): 4.
  • Schimpf, Corey & Castellani, Brian (2020). COMPLEX-IT: A Case-Based Modelling and Scenario Simulation Platform for Social Inquiry. Journal of Open Research Software 8: 25.
  • Rajaram, R & Castellani, B (2020). Diversity in complex systems: measuring parts of the distribution to the whole. Journal of Physics Communications 4(4): 045008.
  • Lieff, Susan J., Baker, Lindsay, Poost-Foroosh, Laya, Castellani, Brian, Hafferty, Fred W. & Ng, Stella L. (2020). Exploring the Networking of Academic Health Science Leaders. Academic Medicine 1.
  • Giabbanelli, Philippe J., Voinov, Alexey A., Castellani, Brian & Tornberg, Petter (2019). Ideal, Best, and Emerging Practices in Creating Artificial Societies. 13-24.
  • Castellani, Brian, Barbrook-Johnson, Peter & Schimpf, Corey (2019). Case-based methods and agent-based modelling: bridging the divide to leverage their combined strengths. International Journal of Social Research Methodology 22(4): 403-416.
  • Barbrook-Johnson, Pete, Schimpf, Corey & Castellani, Brian (2019). Reflections On the Use of Complexity-Appropriate Computational Modeling for Public Policy Evaluation in the UK. Journal on Policy and Complex Systems 5(1).
  • Castellani, Brian, Griffiths, Frances, Rajaram, Rajeev & Gunn, Jane (2018). Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach. Journal of Evaluation in Clinical Practice 24(6): 1293-1309.
  • Kingsbury, Diana M, Bhatta, Madhav P, Castellani, Brian, Khanal, Aruna, Jefferis, Eric & Hallam, Jeffrey S (2018). Factors Associated with the Presence of Strong Social Supports in Bhutanese Refugee Women During Pregnancy. Journal of immigrant and minority health 1-7.
  • Kingsbury, Diana, Bhatta, Madhav, Castellani, Brian, Khanal, Aruna, Jefferis, Eric & Hallam, Jeffery (2018). The Personal Social Networks of Resettled Bhutanese Refugees During Pregnancy in the United States: A Social Network Analysis. Journal of community health 43(6): 1028-1036.
  • Rajaram, Rajeev, Castellani, Brian & Wilson, AN (2017). Advancing shannon entropy for measuring diversity in systems. Complexity 2017: 8715605.
  • Castellani, Brian & Rajaram, Rajeev (2016). Past the power law: Complex systems and the limiting law of restricted diversity. Complexity 21(S2): 99-112.
  • Rajaram, Rajeev & Castellani, Brian (2016). An entropy based measure for comparing distributions of complexity. Physica A: Statistical Mechanics and its Applications 453: 35-43.
  • Galen Buckwalter, J, Castellani, Brian, Mcewen, Bruce, Karlamangla, Arun S, Rizzo, Albert A, John, Bruce, O'donnell, Kyle & Seeman, Teresa (2016). Allostatic load as a complex clinical construct: a case-based computational modeling approach. Complexity 21(S1): 291-306.
  • Castellani, Brian, Rajaram, Rajeev, Gunn, Jane & Griffiths, Frances (2016). Cases, clusters, densities: Modeling the nonlinear dynamics of complex health trajectories. Complexity 21(S1): 160-180.
  • Rajaram, Rajeev & Castellani, Brian (2015). The utility of nonequilibrium statistical mechanics, specifically transport theory, for modeling cohort data. Complexity 20(4): 45-57.
  • Hafferty, Frederic W, Castellani, Brian, Hafferty, Philip K & Pawlina, Wojciech (2013). Anatomy and histology as socially networked learning environments: Some preliminary findings. Academic Medicine 88(9): 1315-1323.
  • Rajaram, Rajeev & Castellani, Brian (2012). Modeling complex systems macroscopically: Case/agent-based modeling, synergetics, and the continuity equation. Complexity 18(2): 8-17.
  • Castellani, Brian & Rajaram, Rajeev (2012). Case-based modeling and the SACS Toolkit: a mathematical outline. Computational and Mathematical Organization Theory 18(2): 153-174.
  • Hafferty, Frederic W & Castellani, Brian (2010). The increasing complexities of professionalism. Academic Medicine 85(2): 288-301.
  • Castellani, Brian, Hafferty, Frederic & Ball, Michael (2009). E-Social Science from a Systems Perspective: Applying the SACS Toolkit. Journal of Sociocybernetics 7(2): 89-106.
  • Hafferty, F.W. & Castellani, B. (2009). A sociological framing of medicine's modern-day professionalism movement. Medical Education 43(9): 826-828.
  • Castellani, Brian, Castellani, John & Spray, S Lee (2003). Grounded neural networking: Modeling complex quantitative data. Symbolic Interaction 26(4): 577-589.
  • Castellani, Brian & Castellani, John (2003). Data mining: qualitative analysis with health informatics data. Qualitative Health Research 13(7): 1005-1018.
  • Wear, Delese & Castellani, Brian (2002). Motherhood and medicine: The experience of double consciousness. Annals of Behavioral Science and Medical Education 8(2): 92.
  • Castellani, Brian & Wear, Delese (2000). Physician views on practicing professionalism in the corporate age. Qualitative Health Research 10(4): 490-506.
  • Wear, Delese & Castellani, Brian (2000). The development of professionalism: curriculum matters. Academic Medicine 75(6): 602-611.
  • Wear, Delese & Castellani, Brian (2000). (Re) considering Context in Patient-Doctor Relationships. Annals of Behavioral Science and Medical Education 7(1): 13.
  • Wear, D. & Castellani, B. (1999). Conflicting plots and narrative d ysfunction in health care. Perspectives in Biology and Medicine 42(4): 544-558.
  • Castellani, Brian (1999). Michel Foucault and Symbolic Interactionism: The Making of a New Theory of Interaction. Studies in Symbolic Interaction 22: 247-272.
  • Castellani, Brian, Wedgeworth, Raymond, Wootton, Enoch & Rugle, Loreen (1997). A bi-directional theory of addiction: examining coping and the factors related to substance relapse. Addictive Behaviors 22(1): 139-144.
  • Castellani, B., Wootton, E., Rugle, L., Wedgeworth, R., Prabucki, K. & Olson, R. (1996). Homelessness, negative affect, and coping among veterans with gambling problems who misused substances. Psychiatric Services 47(3): 298-299.
  • Castellani, Brian & Rugle, Loreen (1995). A comparison of pathological gamblers to alcoholics and cocaine misusers on impulsivity, sensation seeking, and craving. International journal of the addictions 30(3): 275-289.

Newspaper/Magazine Article

  • Castellani,B (2014). Brian Castellani on the Complexity Sciences. October 9th 2014.
  • Castellani, Brian (2014). FOCUS: Complexity and the failure of quantitative social science. Discover Society 12: 12.
  • HAFFERTY, FREDERIC & CASTELLANI, BRIAN (2010). La complejidad creciente del profesionalismo. LA SALUD 85(2): 39.
  • Castellani, Brian (2001). Is pathological gambling really a problem?-You bet! Psychiatric Times 18(2).

Other (Digital/Visual Media)

  • Castellani,B (Published). Map of the complexity sciences.


  • Lieff, Susan, Poost-foroosh, Laya, Baker, Lindsay, Castellani, Brian, Hafferty, Fred & Ng, Stella L (2016), It takes a village: Academic leaders' conceptions of their social networks: oc2-5, 50: Medical Education, 59.

Supervision students