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

Abstract not available

• Speaker: Prof Elizabeth Murchison, Department of Veterinary Medicine.
• Thursday 26 June 2025, 09:30-10:30
• Venue: Theo Chalmers Lecture Theatre (LT2) School of Clinical Medicine.
• Series: Cancer Research UK Cambridge Centre Lectures in Cancer Biology and Medicine; organiser: Justin Holt.

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Abstract not available

• Speaker: Dr Huiqi Yang and Dr Nicola Thompson, Cambridge University Hopitals Trust
• Thursday 19 June 2025, 09:30-10:30
• Venue: Theo Chalmers Lecture Theatre (LT2) School of Clinical Medicine.
• Series: Cancer Research UK Cambridge Centre Lectures in Cancer Biology and Medicine; organiser: Justin Holt.

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Abstract not available

• Speaker: Dr Huiqi Yang and Dr Nicola Thompson, Cambridge University Hopitals Trust
• Thursday 19 June 2025, 09:30-10:30
• Venue: Theo Chalmers Lecture Theatre (LT2) School of Clinical Medicine.
• Series: Cancer Research UK Cambridge Centre Lectures in Cancer Biology and Medicine; organiser: Justin Holt.

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Dr. Adam Cawte: Persistent association with chromatin facilitates the spreading and retention of Xist RNA on the inactive X-chromosome.

Prof. Isaia Barbierii: mRNA 5’-cap trimethylguanosine synthase TGS1 promotes oxidative phosphorylation in acute myeloid leukaemia.

• Speaker: Dr. Adam Cawte (University of Oxford, UK), Dr. Isaia Barbieri (University of Turin, IT)
• Thursday 10 April 2025, 17:00-19:00
• Venue: Online (Zoom).
• Series: Cambridge RNA Club; organiser: cambridgeRNA.

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Cardiovascular diseases remain the leading cause of death globally, with thrombosis playing a central role in their pathogenesis. Current antithrombotic therapies, while effective, often carry significant bleeding risks due to their inability to differentiate between pathological and physiological blood clotting. This presentation introduces our integrated approach that combines fundamental mechanobiology with translational engineering to address critical clinical needs in cardiovascular medicine, potentially transforming how we diagnose, monitor, and treat thrombotic disorders.

First, using our single-cell biomechanical nanotools such as Biomembrane Force Probe (BFP), we present insights into thrombosis mechanobiology, particularly focusing on the role of von Willebrand Factor (VWF) and other mechanoreceptors (GPIbα, integrin αIIbβ3 and PIEZO1 ion channels) in distinguishing between “good” and “bad” mechanical forces in thrombosis. These helped uncover new therapeutic targets for force-sensitive antithrombotic strategies. Second, we demonstrate a personalized vessel-on-chip platform that recreates patient-specific blood vessel geometries and flow conditions, enabling precise evaluation of thrombotic risk and drug responses. Finally, we introduce novel point-of-care microtechnologies for rapid blood coagulation testing, including an AI-powered platform called SmartClot, which promises to revolutionize home-based coagulation monitoring. These innovations represent a significant advancement toward more effective and safer antithrombotic treatments, with potential applications ranging from preventive care to personalized medicine.

Professor Lining Arnold Ju PhD GAICD FHEA

Snow Fellow, Australian Heart Foundation Future Leader Fellow and Australian Academy of Science John Booker Medal, The University of Sydney, School of Biomedical Engineering.

Dr. Ju received his PhD in Biomedical Engineering at Georgia Institute of Technology and Emory University, USA in 2013. From 2014 to 2019, he joined the Australian Centre for Blood Diseases, Monash University, Melbourne, then Heart Research Institute, Sydney as an Australian Heart Foundation Postdoc Fellow. In early 2020, Dr. Ju became an independent PI at the University of Sydney (USYD)’s new School of Biomedical Engineering and started up the Mechanobiology and Biomechanics Laboratory (MBL).

Dr. Ju works at the biomedical engineering and mechanobiology. His team has pioneered multiple biomechanical nanotools, including multi-parametric thrombus profiling microfluidics (Nature Materials 2019; Nature Communications 2024), patient-specific vessel-on-a-chip platform (Advanced Materials 2025; Science Advances 2025), single-cell biomembrane force probes (Nature Communications 2018), 4D hemodynamic modeling (Nature 2021; Blood 2025) and fluorescent micropipette aspiration assays (Nature Communications 2024). His novel understanding of the mechanics behind blood clot formation has profound implications for diagnosing and preventing thrombosis in heart attacks and strokes. His vision is to build novel platforms that integrate advanced biomanufacturing, high-throughput biomechanical phenotyping, and generative AI towards rapid and intelligent biosensing technologies for aging, diabetes, obesity, hypertension, vaccine and autoimmune related thrombotic risks.

• Speaker: Professor Arnold Lining Ju, University of Sydney
• Friday 06 June 2025, 14:00-15:00
• Venue: Oatley 1 Meeting Room, Department of Engineering.
• Series: Engineering - Mechanics and Materials Seminar Series; organiser: div-c.

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MS Teams

Data Acquisition (DAQ) workloads form an important class of scientific network traffic that by its nature (1) flows across different research infrastructure, including remote instruments and supercomputer clusters, (2) has ever-increasing throughput demands, and (3) has ever-increasing integration demands—for example, observations at one instrument could trigger a reconfiguration of another instrument.

This talk describes ongoing work on developing specialized transport protocols for DAQ workloads. It introduces a new transport feature for this kind of elephant flow: multi-modality involves the network actively configuring the transport protocol to change how DAQ flows are processed across different underlying networks that connect scientific research infrastructure. This idea takes advantage of programmable network hardware that is increasingly being deployed in scientific research infrastructure. The talk describes an initial evaluation through a pilot study on a hardware testbed and using data from a particle detector.

Bio: Nik Sultana is an assistant professor of Computer Science at Illinois Institute of Technology. He develops networking techniques to improve cybersecurity and research infrastructure. Before joining Illinois Tech, he was a post-doc at UPenn after completing his PhD at Cambridge University. In 2024 and 2023 he received VSP awards from the Universities Research Association, and in 2022 he received a Google Research Award.

• Speaker: Nik Sultana, Illinois Institute of Technology
• Friday 04 April 2025, 15:00-16:00
• Venue: Online (Teams link below).
• Series: Computer Laboratory Systems Research Group Seminar; organiser: Richard Mortier.

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Abstract not available

• Speaker: Professor Arnold Lining Ju, University of Sydney
• Friday 06 June 2025, 14:00-15:00
• Venue: Oatley 1 Meeting Room, Department of Engineering.
• Series: Engineering - Mechanics and Materials Seminar Series; organiser: div-c.

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Abstract not available

• Speaker: Jelena Ninic, University of Birmingham
• Friday 17 October 2025, 15:00-16:00
• Venue: CivEng Seminar Room (1-33) (Civil Engineering Building).
• Series: Engineering Department Structures Research Seminars; organiser: Shehara Perera.

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Abstract not available

• Speaker: Ali Abbas, University of East London
• Friday 09 May 2025, 15:00-16:00
• Venue: CivEng Seminar Room (1-33) (Civil Engineering Building).
• Series: Engineering Department Structures Research Seminars; organiser: Shehara Perera.

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Abstract not available

• Speaker: Iman Mohagheghian, University of Surrey
• Friday 02 May 2025, 15:00-16:00
• Venue: CivEng Seminar Room (1-33) (Civil Engineering Building).
• Series: Engineering Department Structures Research Seminars; organiser: Shehara Perera.

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Key recovery is the process of regaining access to end-to-end encrypted data after the user has lost their device, but still has their password. Existing E2EE key recovery methods, such as those deployed by Signal and WhatsApp, centralize trust by relying on servers administered by a single provider.

In this talk, we share our recent work on Kintsugi, a decentralized recovery protocol that distributes trust over multiple recovery nodes. This talk will cover how we developed Kintsugi and its unique security properties, as well as compare it to prior E2EE key recovery work.

• Speaker: Emilie Ma
• Tuesday 06 May 2025, 14:00-15:00
• Venue: Webinar (via Zoom online).
• Series: Computer Laboratory Security Seminar; organiser: Anna Talas.

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Large Language Model (LLM) pretraining relies on complex strategies for large-scale optimization, with the learning rate schedule being particularly important yet often following conventional rules. In this talk, I will discuss our recent NeurIPS Spotlight that investigates a simple but effective strategy: a constant learning rate followed by strategic cooldowns. Our analysis demonstrates that this approach does not only perform reliably, but it offers practical advantages as it does not require predetermined training lengths and easily allows continual training. Importantly, these findings enable more efficient scaling law experiments, as they allow for reuse of training runs and thereby substantially reduce compute and GPU hours. In a followup work, we investigate theoretical explanations of the unique behavior of such learning rate schedules, leveraging last-iterate convergence bounds which closely match real experiments. At the end of the talk, I will conclude by introducing the Swiss AI initiative (https://www.swiss-ai.org/) which deploys the world’s first national research infrastructure with 10,000 NVIDIA Grace Hopper GPUs. This initiative leverages our research innovations, such as the above, to develop state-of-the-art open and multilingual LLMs, with the goal of advancing fully transparent scientific research on foundation models.

Bio: Alex Hägele is a PhD Student at EPFL in the Machine Learning and Optimization group (MLO) supervised by Martin Jaggi. Currently, he is part of the inaugural Anthropic Fellowship for AI Safety research, based in London. Previously, he completed his BSc+MSc in Computer Science at ETH Z ürich and was a visiting Student Researcher at Apple MLR in Paris. His research explores scaling behavior and training of language models, spanning optimization, data, and architectures.

• Speaker: Alex Hägele, EPFL
• Tuesday 08 April 2025, 14:00-15:00
• Venue: Computer Lab, FW26.
• Series: Cambridge ML Systems Seminar Series; organiser: Sally Matthews.

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The Canadian Arctic Archipelago (CAA) is home to over 300 marine-terminating glaciers facing retreat with ongoing Arctic change, increasing glacial meltwater delivery to the ocean. Subglacial discharge can produce meltwater plumes that promote upwelling and enhance mixing near glacier termini, impacting water column structure, turbidity, and other biogeochemical properties in the proximate ocean. Despite their abundance, knowledge is lacking on glacier-ocean systems across the CAA , specifically how glacial meltwater is influencing and modifying the marine environment in the coastal ocean. This talk explores the 4 years of late summer in-situ observations of marine-terminating glacier-ocean systems and non-glacierized systems in Jones Sound, a glacier rich region of the CAA . Specifically, we examine the systematic influence of marine-terminating glacier presence on the chemical and physical marine environment and contrast marine-terminating glacier systems with riverine systems in the same region. We find marine-terminating glaciers host late-summer nutrient enhancement above the region’s characteristic nutricline year over year. This contrasts riverine systems that show rare nutrient enhancement above the characteristic nutricline. Ongoing retreat may shift these systems towards riverine-like systems, reducing this above-nutricline nutrient enhancement that may impact phytoplankton community composition, which may have subsequent impacts on carbon sequestration and food web function. This work also informs the Inuit community of Ausuittuq (Grise Fiord, NU), who live in Jones Sound and use the neighbouring ocean for traditional hunting, culture, and economic benefit, about the ongoing change in their local environment.

• Speaker: Claire Parrott, University of British Columbia
• Wednesday 09 April 2025, 15:00-16:00
• Venue: BAS Seminar Room 2.
• Series: British Antarctic Survey - Polar Oceans seminar series; organiser: Dr Birgit Rogalla.

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Abstract

Jurisdictional REDD plus policies undertaken at the state or national level are rapidly replacing fragmented local projects at the forefront of conservation efforts. However, their effectiveness remains uncertain, as does the reliability of the mechanisms proposed to measure their impact. To address this, we employ the synthetic control method, which only has one prior application in this domain, to estimate the additional impacts of national REDD plus implementations in Guyana, Gabon, and Honduras. We further assess the assumptions underlying this approach and explore statistical frameworks to enhance confidence in our results.

Bio

Onkar is a 2nd year PhD student at the Department of Computer Science & Technology, supervised by Prof. Anil Madhavapeddy and Dr. Sadiq Jaffer. His research interests involve utilising advances in machine learning and causal inference to better understand the impacts of interventions undertaken by governments globally, particularly in the context of evaluating and forecasting progress towards the Sustainable Development Goals. His interests more broadly include spatial statistics, macroeconomics, private markets, and linguistics. He previously received his bachelor’s degree from the University of Tokyo in 2021 and a master’s degree from the University of Cambridge in 2023. Onkar has worked across various firms in the investment and technology industries prior to and during his PhD.

• Speaker: Onkar Gulati, University of Cambridge
• Friday 04 April 2025, 13:00-14:00
• Venue: SS03, William Gates Building. Zoom link: 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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Abstract

Jurisdictional REDD policies undertaken at the state or national level are rapidly replacing fragmented local projects at the forefront of conservation efforts. However, their effectiveness remains uncertain, as does the reliability of the mechanisms proposed to measure their impact. To address this, we employ the synthetic control method, which only has one prior application in this domain, to estimate the additional impacts of national REDD implementations in Guyana, Gabon, and Honduras. We further assess the assumptions underlying this approach and explore statistical frameworks to enhance confidence in our results.

Bio

Onkar is a 2nd year PhD student at the Department of Computer Science & Technology, supervised by Prof. Anil Madhavapeddy and Dr. Sadiq Jaffer. His research interests involve utilising advances in machine learning and causal inference to better understand the impacts of interventions undertaken by governments globally, particularly in the context of evaluating and forecasting progress towards the Sustainable Development Goals. His interests more broadly include spatial statistics, macroeconomics, private markets, and linguistics. He previously received his bachelor’s degree from the University of Tokyo in 2021 and a master’s degree from the University of Cambridge in 2023. Onkar has worked across various firms in the investment and technology industries prior to and during his PhD.

• Speaker: Onkar Gulati, University of Cambridge
• Friday 04 April 2025, 13:00-14:00
• Venue: SS03, William Gates Building. Zoom link: 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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Recent aspects of molecular chaperone function in health and disease F. Ulrich Hartl Department of Cellular Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany While protein folding was originally assumed to occur spontaneously, we now appreciate that in the crowded environment of cells, newly-synthesized polypeptides depend on molecular chaperones to reach their folded states efficiently and at a biologically relevant time scale. Assistance of protein folding is provided by members of different chaperone classes acting to facilitate the interconversion of folding intermediates, preventing misfolding and off-pathway aggregation, often in an ATP -dependent mechanism. A well-studied example are the cylindrical chaperonins (GroEL/ES in bacteria, Hsp60 in mitochondria, TRiC in the eukaryotic cytosol), which form nano-cages for single protein molecules to fold unimpaired by aggregation. As an added benefit, encapsulation results in entropic confinement of dynamic folding intermediates, thereby markedly accelerating folding for some proteins over the spontaneous folding rate.

Once folded, many proteins continue to require chaperone surveillance to retain their functional states, especially under conditions of cell stress. Failure of the chaperone machinery to maintain proteostasis, i.e. the conformational integrity and balance of the cellular proteome, facilitates the manifestation of diseases in which proteins misfold and form toxic aggregates. These disorders include, among others, Alzheimer’s, Parkinson’s, and Huntington’s disease.

I will provide an overview of chaperone mechanisms and then discuss recent work providing new insights into the role of chaperones in protein folding and proteostasis maintenance, with a focus on observations in intact cells.

• Speaker: Prof. Ulrich Hartl - Max-Planck-Institute of Biochemistry
• Tuesday 08 April 2025, 15:00-16:00
• Venue: Department of Chemistry, Cambridge, Pfizer LT.
• Series: Biological Chemistry Research Interest Group; organiser: Echo Wu Williamson.

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Recent aspects of molecular chaperone function in health and disease F. Ulrich Hartl Department of Cellular Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany While protein folding was originally assumed to occur spontaneously, we now appreciate that in the crowded environment of cells, newly-synthesized polypeptides depend on molecular chaperones to reach their folded states efficiently and at a biologically relevant time scale. Assistance of protein folding is provided by members of different chaperone classes acting to facilitate the interconversion of folding intermediates, preventing misfolding and off-pathway aggregation, often in an ATP -dependent mechanism. A well-studied example are the cylindrical chaperonins (GroEL/ES in bacteria, Hsp60 in mitochondria, TRiC in the eukaryotic cytosol), which form nano-cages for single protein molecules to fold unimpaired by aggregation. As an added benefit, encapsulation results in entropic confinement of dynamic folding intermediates, thereby markedly accelerating folding for some proteins over the spontaneous folding rate.

Once folded, many proteins continue to require chaperone surveillance to retain their functional states, especially under conditions of cell stress. Failure of the chaperone machinery to maintain proteostasis, i.e. the conformational integrity and balance of the cellular proteome, facilitates the manifestation of diseases in which proteins misfold and form toxic aggregates. These disorders include, among others, Alzheimer’s, Parkinson’s, and Huntington’s disease.

I will provide an overview of chaperone mechanisms and then discuss recent work providing new insights into the role of chaperones in protein folding and proteostasis maintenance, with a focus on observations in intact cells.

• Speaker: Prof. Ulrich Hartl - Max-Planck-Institute of Biochemistry
• Tuesday 08 April 2025, 14:30-15:30
• Venue: Department of Chemistry, Cambridge, Pfizer LT.
• Series: Biological Chemistry Research Interest Group; organiser: Echo Wu Williamson.

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Data is often available in matrix form, in which columns are samples, and processing of such data often entails finding an approximate factorization of the matrix into two factors. The first factor (the “dictionary”) yields recurring patterns characteristic of the data. The second factor (“the activation matrix”) describes in which proportions each data sample is made of these patterns. Nonnegative matrix factorization (NMF) is a popular unsupervised learning technique for analysing data with nonnegative values, with applications in many areas such as in text information retrieval, recommender systems, audio signal processing, and hyperspectral imaging. In a first part, I will give a short tutorial presentation about NMF for data processing, with a focus on majorization-minimization algorithms for NMF with the beta-divergence, a continuous family of loss functions that takes the quadratic loss, KL divergence and Itakura-Saito divergence as special cases. Then, I will present applications for hyperspectral unmixing in remote sensing and factor analysis in dynamic positron emission tomography, introducing robust variants of NMF that account for outliers, nonlinear phenomena or specific binding.

References C. Févotte, J. Idier. Algorithms for nonnegative matrix factorization with the beta-divergence. Neural computation, 2011. C. Févotte, N. Dobigeon. Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization. IEEE Transactions on Image Processing, 2015. Y. C. Cavalcanti, T. Oberlin, N. Dobigeon, C. Févotte, S. Stute, M. J. Ribeiro, C. Tauber. Factor analysis of dynamic PET images: beyond Gaussian noise. IEEE Transactions on Medical Imaging, 2019. A. Marmin, H. Goulart, C. Févotte. Joint majorization-minimization for nonnegative matrix factorization with the beta-divergence. IEEE Transactions on Signal Processing, 2023.

Bio:

Cédric Févotte is a CNRS research director with Institut de Recherche en Informatique de Toulouse (IRIT). Previously, he was a CNRS researcher at Laboratoire Lagrange (Nice, 2013-2016) & Télécom ParisTech (2007-2013), a research engineer at Mist-Technologies (the startup that became Audionamix, 2006-2007) and a postdoc at University of Cambridge (2003-2006). He holds MEng and PhD degrees in EECS from École Centrale de Nantes. His research interests concern statistical signal processing and machine learning, with particular interests in matrix factorization, inverse problems, source separation and recommender systems. Selected distinctions: IEEE Fellow (2022), ERC Consolidator Grant (2016-2022), IEEE Signal Processing Society Sustained Impact Paper Award (2023), IEEE Signal Processing Society Best Paper Award (2014).

• Speaker: Cédric Févotte, Institut de Recherche en Informatique de Toulouse (IRIT)
• Tuesday 22 April 2025, 11:00-12:00
• Venue: LT6, Baker Building, CUED.
• Series: Signal Processing and Communications Lab Seminars; organiser: Kimberly Cole.

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Data is often available in matrix form, in which columns are samples, and processing of such data often entails finding an approximate factorization of the matrix into two factors. The first factor (the “dictionary”) yields recurring patterns characteristic of the data. The second factor (“the activation matrix”) describes in which proportions each data sample is made of these patterns. Nonnegative matrix factorization (NMF) is a popular unsupervised learning technique for analysing data with nonnegative values, with applications in many areas such as in text information retrieval, recommender systems, audio signal processing, and hyperspectral imaging. In a first part, I will give a short tutorial presentation about NMF for data processing, with a focus on majorization-minimization algorithms for NMF with the beta-divergence, a continuous family of loss functions that takes the quadratic loss, KL divergence and Itakura-Saito divergence as special cases. Then, I will present applications for hyperspectral unmixing in remote sensing and factor analysis in dynamic positron emission tomography, introducing robust variants of NMF that account for outliers, nonlinear phenomena or specific binding.

References C. Févotte, J. Idier. Algorithms for nonnegative matrix factorization with the beta-divergence. Neural computation, 2011. C. Févotte, N. Dobigeon. Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization. IEEE Transactions on Image Processing, 2015. Y. C. Cavalcanti, T. Oberlin, N. Dobigeon, C. Févotte, S. Stute, M. J. Ribeiro, C. Tauber. Factor analysis of dynamic PET images: beyond Gaussian noise. IEEE Transactions on Medical Imaging, 2019. A. Marmin, H. Goulart, C. Févotte. Joint majorization-minimization for nonnegative matrix factorization with the beta-divergence. IEEE Transactions on Signal Processing, 2023.

Bio:

Cédric Févotte is a CNRS research director with Institut de Recherche en Informatique de Toulouse (IRIT). Previously, he was a CNRS researcher at Laboratoire Lagrange (Nice, 2013-2016) & Télécom ParisTech (2007-2013), a research engineer at Mist-Technologies (the startup that became Audionamix, 2006-2007) and a postdoc at University of Cambridge (2003-2006). He holds MEng and PhD degrees in EECS from École Centrale de Nantes. His research interests concern statistical signal processing and machine learning, with particular interests in matrix factorization, inverse problems, source separation and recommender systems. Selected distinctions: IEEE Fellow (2022), ERC Consolidator Grant (2016-2022), IEEE Signal Processing Society Sustained Impact Paper Award (2023), IEEE Signal Processing Society Best Paper Award (2014).

• Speaker: Cédric Févotte, Institut de Recherche en Informatique de Toulouse (IRIT)
• Tuesday 22 April 2025, 11:00-12:00
• Venue: LT6, Baker Building, CUED.
• Series: Signal Processing and Communications Lab Seminars; organiser: Kimberly Cole.

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Abby graduated from Cambridge Veterinary School in 2001 and during five years in a busy small animal practice, developed an interest in radiology and ultrasound, and gained the RCVS Certificate in Veterinary Diagnostic Imaging. Abby returned to Cambridge in 2006 to undertake a Residency program in Diagnostic Imaging, and gained the European Diploma in Veterinary Diagnostic Imaging in 2009. Abby is a European Specialist in Veterinary Diagnostic Imaging and an RCVS fellow. She has published many scientific publications and book chapters in the field, and is a former executive board member of ECVDI and former chair of the EAVDI BID . She is current Chair of the ECVDI examination committee. She is interested in all aspects of imaging, and is currently researching advance imaging of the feline biliary tract as part of the Vet MD programme at Cambridge Vet school.

Chaired by Olivier Restif

• Speaker: Abigail Caine, Department of Veterinary Medicine
• Friday 06 June 2025, 08:45-10:00
• Venue: LT2.
• Series: Friday Morning Seminars, Dept of Veterinary Medicine; organiser: Fiona Roby.

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