http://talks.cam.ac.uk/show/rss/5408

Carolina Malco Rullan graduated with a degree in Veterinary Medicine in 2024 and worked as a general practitioner in Spain before moving to the UK to begin her PhD at the University of Cambridge in October. Her doctoral research focuses on understanding the process of intervertebral disc calcification, with particular interest in the role of Poly ADP -ribose (PAR)—a molecule previously associated with vascular calcification in humans. Carolina is investigating whether this molecule could also be involved in disc calcification in dogs, with the ultimate aim of developing a treatment that targets its precursor, PARP , to reduce or even prevent disc calcification, a condition linked to an increased risk of disc herniation

• Speaker: Carolina Malco Rullan, Departmet of Veterinary Medicine
• Friday 14 November 2025, 08:45-10:00
• Venue: LT2.
• Series: Friday Morning Seminars, Dept of Veterinary Medicine; organiser: Fiona Roby.

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This Cambridge Immunology Network Seminar will take place on Friday 1 August 2025, starting at 1:00-2:00pm

Speaker: Ben Gewurz, George and Sandra K Schussel Associate Professor of Infectious Diseases, Harvard Medical School

Title: “Systematic CRISPR -Cas9 Genetic Characterization of Epstein-Barr Virus/Host Interactions”

Host: Mike Weekes, Professor of Viral Immunology, Cambridge Institute for Medical Research

Note unusual time

• Speaker: Ben Gewurz,
• Friday 01 August 2025, 13:00-14:00
• Venue: Lecture Theatre, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus.
• Series: Cambridge Immunology Network Seminar Series; organiser: Ruth Paton.

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Abstract not available

• Speaker: Pengyi Ding, Departmet of Veterinary Medicine
• Friday 14 November 2025, 08:45-10:00
• Venue: LT2.
• Series: Friday Morning Seminars, Dept of Veterinary Medicine; organiser: Fiona Roby.

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Abstract not available

• Speaker: Weidong Jing, Departmet of Veterinary Medicine
• Friday 17 October 2025, 08:45-10:00
• Venue: LT2.
• Series: Friday Morning Seminars, Dept of Veterinary Medicine; organiser: Fiona Roby.

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Women of Afro-Caribbean descent confront more aggressive breast cancer subtypes at a younger age than their Caucasian counterparts. Yet, breast cancer research and treatment development have predominantly focused on Caucasian populations, neglecting potential biological drivers of these disparities. Our study addresses this gap by in-depth characterising the breast tumour microenvironment (TME) in an ethnically diverse cohort. We analysed treatment-naïve breast cancer samples from 45 Black British and 45 White British women, matched by age, tumour subtype, and stage by employing spatial transcriptomics (NanoString GeoMx) and hyper-plex protein profiling (Leica Microsytems Cell DIVE ). We captured whole-transcriptome data from cancer (PanCK+), immune (CD45+), and stromal (aSMA+) compartments from both tumour centre and tumour edge. The most striking differences emerged within the immune and stromal compartments, not in the cancer cells, underscoring metabolic, adhesion, and extracellular matrix rewiring in Black British tumours. Complementary spatial protein profiling further revealed changes in tissue architecture with distinct recurrent patterns of cellular organisation and cell-cell interactions, involving endothelial and B-cells. Our findings suggest that the TME plays a pivotal role in driving ethnic disparities in breast cancer, highlighting the urgent need for ethnically tailored therapies and more inclusive clinical trials to advance precision cancer care. This breakthrough offers new avenues for improving overall outcomes in breast cancer.

**Please note this seminar is on a Friday at 14:00-15:00**

• Speaker: Professor Kairbaan Hodivala-Dilke, Centre for Tumour Microenvironment, Barts Cancer Institute, Queen Mary University of London
• Friday 24 October 2025, 14:00-15:00
• Venue: CRUK CI Lecture Theatre.
• Series: Cancer Research UK Cambridge Institute (CRUK CI) Seminars in Cancer; organiser: Kate Davenport.

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Noisy intermediate-scale quantum devices provide a promising platform for exploring non-equilibrium quantum dynamics. Building on this opportunity, we theoretically explore open-system evolution implemented on digital quantum computers via repeated interactions between a quantum system and auxiliary qubits. After each interaction, the auxiliary qubits are measured, and the resulting sequence of measurement outcomes defines a quantum trajectory. By interpreting trajectories as microstates of an effective ensemble, we construct dynamical analogues of equilibrium concepts such as free energy and entropy. This framework allows us to bias quantum trajectories and tailor their properties—e.g., temporal correlations—in a controlled manner. Applying our approach to a many-body model inspired by dual-species Rydberg-atom experiments, we uncover rich heterogeneous behaviour and glassy dynamics that remain hidden in the average-state evolution. By leveraging the aforementioned thermodynamic-like functionals, we identify these features as signatures of a first-order dynamical phase transition.

• Speaker: Dr Federico Carollo (Coventry University)
• Thursday 24 July 2025, 14:00-15:15
• Venue: Seminar Room 3, RDC.
• Series: Theory of Condensed Matter; organiser: Bo Peng.

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In the past years, results based on a technique called convex integration have drawn lots of interest within the community of mathematical fluid mechanics. Among other fascinating results, this technique allows to prove existence of infinitely many solutions for the multi-dimensional compressible Euler equations. All these solutions satisfy the energy inequality which is commonly used in the literature to identify physically relevant solutions. On the other hand, intuitively at least some of the infinitely many solutions still seem to be non-physical. For this reason one has studied additional admissibility criteria regarding maximal energy dissipation—to no avail: such criteria do not select the solution which is expected to be the physical one. In this talk we give an overview on the aforementioned non-uniqueness results and we explain why maximal dissipation fails to single out the solution which is presumably the physical solution.

• Speaker: Simon Markfelder (University of Konstanz)
• Thursday 16 October 2025, 15:00-16:00
• Venue: Centre for Mathematical Sciences, MR14.
• Series: Applied and Computational Analysis; organiser: Georg Maierhofer.

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Abstract

The growing accessibility of solar photovoltaic (PV) systems offers a promising pathway for homeowners to decarbonize their buildings. However, determining the appropriate size of a PV system and battery storage remains a complex task, influenced by household energy demand, daily activity patterns, and local solar potential. This decision becomes more complex with the increasing adoption of electric vehicles (EVs), as commute patterns and charging strategies, including bidirectional charging, significantly influence electricity demand profiles. Conventional approaches to sizing PV and battery systems rely on detailed simulations that, while accurate, are computationally intensive and often take several minutes to hours to complete. This latency reduces interactivity and limits users’ ability to explore different scenarios, such as varying EV charging policies or desired levels of energy self-sufficiency. In this work, we introduce SolarFit, an application that delivers instant, high-accuracy sizing recommendations based on simple user-provided inputs. SolarFit leverages a neural network-based surrogate model, which generates results within milliseconds. By drastically reducing computation time, our approach enables users to efficiently evaluate a range of scenarios and identify system configurations that best match their needs.

Bio

Julia Gschwind is a visiting Master’s student at the University of Cambridge from ETH Zurich. She is supervised by Prof. Srinivasan Keshav and her research focuses on using neural networks to predict the optimal sizing of photovoltaic systems.

• Speaker: Julia Gschwind ETH Zurich, University of Cambridge
• Thursday 17 July 2025, 13:00-14:00
• Venue: Room GS15 at the William Gates Building and on Zoom: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon .
• Series: Energy and Environment Group, Department of CST; organiser: lyr24.

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Difficulties in social interaction have been recognized as a core feature of autism, with traditional theories locating the root cause within the autistic “mind”. The ‘Double Empathy Problem’ theory (Milton et al., 2022) reframes these challenges as bidirectional communication breakdowns in mixed-neurotype interactions. This presentation examines this bidirectional challenge through a systematic review of qualitative studies (107 studies; 1,798 participants) and two experimental research projects using the Empathic Accuracy paradigm. Specifically, we investigated invisible aspects of mixed-neurotype interactions versus the effect of disclosing autism on empathy. The review revealed “invisible” challenges that profoundly impact autistic students in educational settings, such as loneliness (reported even when students appeared included), and a twofold negative impact of camouflaging: poor mental health outcomes from masking autistic traits during social interactions, and hiding these struggles. The review also identified positive features, particularly meaningful mixed-neurotype friendships and the positive effect of autism disclosure to peers. In a series of experiments (N=235; N=271) we also investigated more closely how non-autistic people empathize with autistic people, and how autism disclosure affects non-autistic individuals’ empathy and social interest towards an autistic social target. We found that disclosure improved self-reported empathy and empathic accuracy – non-autistic participants better understood autistic individuals’ emotions when aware of their diagnosis. However, the impact on social interest varied across populations, revealing complex dynamics between disclosure, understanding, and social connection (see our recently published paper for more details: https://link.springer.com/article/10.1007/s10803-025-06802-2).

• Speaker: Dr Yonat Rum, The Hebrew University of Jerusalem
• Wednesday 30 July 2025, 16:00-17:00
• Venue: Douglas House and online https://us02web.zoom.us/j/81866331311?pwd=ZoVl1HOEsSNbwRvedQOLKhkcR8hGy3.1.
• Series: ARClub Talks; organiser: Simon Braschi.

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Abstract not available

• Speaker: Dr Federico Carollo (Coventry University)
• Thursday 24 July 2025, 14:00-15:15
• Venue: Seminar Room 3, RDC.
• Series: Theory of Condensed Matter; organiser: Bo Peng.

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The increasing availability of human trajectory and social data, fueled by GPS and social networks, presents a unique opportunity for scientific discovery. However, existing data analysis methods struggle to provide robust, efficient, and generalizable graph representations, hindering their applicability in urban and social sciences. This research addresses this challenge by developing novel machine learning algorithms specifically tailored for graph-structured data in these domains. This research tackles three key challenges: (1) Sparse Data and Data Distribution Heterogeneity: Current methods often struggle with sparse data and varying data distributions, limiting their ability to capture diverse patterns and hindering scalability. This research proposes novel approaches for flexible, adaptive, and generalizable representations in urban planning and social sciences. (2) Non-General Representation and Difficulty Adapting to New Data: Existing methods often lack the ability to generalize across different datasets and struggle to adapt to new data, hindering their effectiveness in real-world applications. This research aims to develop methods that can learn robust and efficient representations that generalize across different datasets and adapt to new data. (3) Trade-off Between Efficiency and Effectiveness: Balancing processing speed, accuracy, and reliability is crucial in urban and social science data analysis. This research addresses this challenge by developing innovative algorithms that optimize for both efficiency and effectiveness. This research leverages contrastive learning and information bottleneck techniques to develop robust and efficient graph representation learning methods for spatial-temporal data and recommender systems. The developed methods have demonstrated significant improvements in downstream tasks such as traffic prediction, crime prediction, and anomaly detection. This research lays a strong foundation for future work in graph-structured data analysis across various domains, including urban science, social science, and scientific discovery. Future research will focus on extending these methods to multi-modal datasets, enabling zero-shot learning, and developing novel approaches for understanding complex biological systems.

• Speaker: qrzhang@hku.hk
• Monday 21 July 2025, 15:50-17:20
• Venue: Computer Laboratory, William Gates Building, Lecture Theatre 1.
• Series: Foundation AI; organiser: Pietro Lio.

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Thermodynamics was originally developed for large numbers of particles in macroscopic systems. Things can be very different on the nanoscale, and new questions arise:

1. How is small different from big? As nanoscale size is approached, so the effect of individual disturbances becomes significant and measurable.

2. How is few different from many? As the number of particles is reduced, it may become possible to forgo ignorance of individual positions and momenta.

3. How is cold different from hot? Many, or perhaps most, nanoscale thermodynamics experiments are carried out at low temperatures.

4. How is quantum different from classical? Quantum heat engines can be used to cool and initialise quantum devices.

The talk will focus on experiments which address questions such as these in new ways.

• Speaker: Andrew Briggs, Department of Materials, The University of Oxford
• Thursday 13 November 2025, 15:00-16:00
• Venue: The Cluster Room, A0.022, Ray Dolby Centre, Cavendish Laboratory.
• Series: Physics and Chemistry of Solids Group; organiser: Stephen Walley.

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Thermodynamics was originally developed for large numbers of particles in macroscopic systems. Things can be very different on the nanoscale, and new questions arise:

1. How is small different from big? As nanoscale size is approached, so the effect of individual disturbances becomes significant and measurable.

2. How is few different from many? As the number of particles is reduced, it may become possible to forgo ignorance of individual positions and momenta.

3. How is cold different from hot? Many, or perhaps most, nanoscale thermodynamics experiments are carried out at low temperatures.

4. How is quantum different from classical? Quantum heat engines can be used to cool and initialise quantum devices.

The talk will focus on experiments which address questions such as these, including the entropic cost of information erasure in a single-electron nanoscale device.

• Speaker: Andrew Briggs, Department of Materials, The University of Oxford
• Thursday 13 November 2025, 15:00-16:00
• Venue: The Cluster Room, A0.022, Ray Dolby Centre, Cavendish Laboratory.
• Series: Physics and Chemistry of Solids Group; organiser: Stephen Walley.

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We define the notion of a classical commitment scheme to quantum states, which allows a quantum prover to compute a classical commitment to a quantum state, and later open each qubit of the state in either the standard or the Hadamard basis. Our notion is a strengthening of the measurement protocol from Mahadev (STOC 2018). We construct such a commitment scheme from the post-quantum Learning With Errors (LWE) assumption, and more generally from any noisy trapdoor claw-free function family that has the distributional strong adaptive hardcore bit property (a property that we define in this work). Our scheme is succinct in the sense that the running time of the verifier in the commitment phase depends only on the security parameter (independent of the size of the committed state), and its running time in the opening phase grows only with the number of qubits that are being opened (and the security parameter). As a corollary we obtain a classical succinct argument system for QMA under the post-quantum LWE assumption. Previously, this was only known assuming post-quantum secure indistinguishability obfuscation. As an additional corollary we obtain a generic way of converting any X/Z quantum PCP into a succinct argument system under the quantum hardness of LWE .

• Speaker: Agi Vilanyi (MIT)
• Monday 28 July 2025, 10:00-11:00
• Venue: Computer Laboratory, William Gates Building, Room SS03.
• Series: Quantum Computing Seminar; organiser: Tom Gur.

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Protein representation learning (PRL) is crucial for understanding structure-function relationships, yet current sequence- and graph-based methods fail to capture the hierarchical organization inherent in protein structures. We introduce Topotein, a comprehensive framework that applies topological deep learning to PRL through the novel Protein Combinatorial Complex (PCC) and Topology-Complete Perceptron Network (TCPNet). Our PCC represents proteins at multiple hierarchical levels—-from residues to secondary structures to complete proteins—-while preserving geometric information at each level. TCP Net employs SE(3)-equivariant message passing across these hierarchical structures, enabling more effective capture of multi-scale structural patterns. Through extensive experiments on four PRL tasks, TCP Net consistently outperforms state-of-the-art geometric graph neural networks. Our approach demonstrates particular strength in tasks such as fold classification which require understanding of secondary structure arrangements, validating the importance of hierarchical topological features for protein analysis.

• Speaker: Zhiyu Wang
• Monday 28 July 2025, 16:00-17:00
• Venue: Computer Laboratory, William Gates Building, Lecture Theatre 1.
• Series: Foundation AI; organiser: Pietro Lio.

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Abstract not available

• Speaker: qrzhang@hku.hk
• Wednesday 16 July 2025, 15:50-17:20
• Venue: Computer Laboratory, William Gates Building, Lecture Theatre 1.
• Series: Foundation AI; organiser: Pietro Lio.

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Abstract not available

• Speaker: qrzhang@hku.hk
• Wednesday 16 July 2025, 15:50-17:20
• Venue: Computer Laboratory, William Gates Building, Lecture Theatre 1.
• Series: Foundation AI; organiser: Pietro Lio.

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Humans are a critical link to the security of any complex system, and blockchains are no exception. Sometimes, even basic assumptions are not met in practice; we observed that some service providers or users do not properly check transactions, whether purposefully (for latency benefits) or inadvertently (due to operational mistakes). These unexpected behaviors pose new challenges to blockchain security. The first part of this talk will examine a network layer vulnerability – a “blockchain amplification attack.” Some Ethereum nodes appear to sidestep transaction validations to achieve lower latency, making them vulnerable to a flood of invalid transactions. We quantify its attack damage through mathematical modeling, network monitoring, and local simulation, and compare it with the potential economic gains of latency reduction. The second part focuses on a wallet-level attack – “blockchain address poisoning.” Attackers generate addresses resembling the victim’s recipient’s address to fool the victim into sending their assets to the attacker by mistake. We develop a detection algorithm to scan two years of Ethereum and Binance Smart Chain (BSC), characterize attack patterns, extrapolate large attack groups, and bound the attacker’s computational capability through measurement and simulation. We will also discuss our initiatives to make our research accessible to end users.

Zoom link: https://us02web.zoom.us/j/85980496815?pwd=z3tmHabXUSHbPgCe6VrSDq3WoIOi0R.1

• Speaker: Taro Tsuchiya, Carnegie Mellon University
• Tuesday 15 July 2025, 14:00-15:00
• Venue: Webinar & LT2, Computer Laboratory, William Gates Building..
• Series: Computer Laboratory Security Seminar; organiser: Alexandre Pauwels.

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Abstract Stay Tuned.

Bio

E-Ping is a third-year postdoc, working with Keshav and Professor David Coomes (Plant Sciences) on using satellite data to quantify the benefit of emissions reduction and its permanence in tropical forest conservation projects in the Reducing Emissions from Deforestation and Forest Degradation (REDD+) framework, with the aim of improving credibility of conservation finance mechanisms through carbon markets.

• Speaker: E-Ping Rau, University of Cambridge
• Friday 10 October 2025, 13:00-14:00
• Venue: Room GS15 at the William Gates Building and on Zoom: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon .
• Series: Energy and Environment Group, Department of CST; organiser: lyr24.

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Humans are a critical link to the security of any complex system, and blockchains are no exception. Sometimes, even basic assumptions are not met in practice; we observed that some service providers or users do not properly check transactions, whether purposefully (for latency benefits) or inadvertently (due to operational mistakes). These unexpected behaviors pose new challenges to blockchain security. The first part of this talk will examine a network layer vulnerability – a “blockchain amplification attack.” Some Ethereum nodes appear to sidestep transaction validations to achieve lower latency, making them vulnerable to a flood of invalid transactions. We quantify its attack damage through mathematical modeling, network monitoring, and local simulation, and compare it with the potential economic gains of latency reduction. The second part focuses on a wallet-level attack – “blockchain address poisoning.” Attackers generate addresses resembling the victim’s recipient’s address to fool the victim into sending their assets to the attacker by mistake. We develop a detection algorithm to scan two years of Ethereum and Binance Smart Chain (BSC), characterize attack patterns, extrapolate large attack groups, and bound the attacker’s computational capability through measurement and simulation. We will also discuss our initiatives to make our research accessible to end users.

• Speaker: Taro Tsuchiya, Carnegie Mellon University
• Tuesday 15 July 2025, 14:00-15:00
• Venue: Webinar & LT2, Computer Laboratory, William Gates Building..
• Series: Computer Laboratory Security Seminar; organiser: Alexandre Pauwels.

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