Please note that the list below only shows forthcoming events, which may not include regular events that have not yet been entered for the forthcoming term. Please see the past events page for a list of all seminar series that the department has on offer.

 

Past events in this series


Tue, 04 Nov 2025
14:00
C4

Exploring partition diversity in complex networks

Lena Mangold
(IT:U Interdisciplinary Transformation University Austria)
Abstract
Partition diversity refers to the concept that for some networks there may be multiple, similarly plausible ways to group the nodes, rather than one single best partition. In this talk, I will present two projects that address this idea from different but complementary angles. The first introduces the benchmark stochastic cross-block model (SCBM), a generative model designed to create synthetic networks with two distinct 'ground-truth' partitions. This allows us to study the extent to which existing methods for partition detection are able to reveal the coexistence of multiple underlying structures. The second project builds on this benchmark and paves the way for a Bayesian inference framework to directly detect coexisting partitions in empirical networks. By formulating this model as a microcanonical variant of the SCBM, we can evaluate how well it fits a given network compared to existing models. We find that our method more reliably detects partition diversity in synthetic networks with planted coexisting partitions, compared to methods designed to detect a single optimal partition. Together, the two projects contribute to a broader understanding of partition diversity by offering tools to explore the ambiguity of network structure.
Tue, 11 Nov 2025
14:00
C4

Towards Precision in the Diagnostic Profiling of Patients: Leveraging Symptom Dynamics in the Assessment and Treatment of Mental Disorders

Omid Ebrahimi
(Department of Experimental Psychology, University of Oxford)
Abstract

Major depressive disorder (MDD) is a heterogeneous mental disorder. International guidelines present overall symptom severity as the key dimension for clinical characterisation. However, additional layers of heterogeneity may reside within severity levels related to how symptoms interact with one-another in a patient, called symptom dynamics. We investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same diagnosis and overall symptom severity. We show that examining symptom dynamics provides information about the person-specific psychopathological expression of patients beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may serve as a promising new dimension for clinical characterisation. Areas of opportunity are outlined for the field of precision psychiatry in uncovering disorder evolution patterns (e.g., spontaneous recovery; critical worsening) and the identification of granular treatment effects by moving toward investigations that leverage symptom dynamics as their foundation. Future work aimed at investigating the cascading dynamics underlying depression onset and maintenance using the large-scale (N > 5.5 million) CIPA Study are outlined. 

Tue, 02 Dec 2025
14:00
C4

TBA

Fabio Caccioli
(University College London)
Abstract

TBA