I'm really excited to announce that our brand new MRes in Advanced Artificial Intelligence is now available on the @SussexUni website This course offers research focused training in how to be an effective and responsible AI scientist or engineer.

RT @moccia_arianna: 🚨Paper now published! 🚨. The Effects of External Cue Overlap and Internal Goals on Selective Memory Retrieval. Gratefu….

RT @anilkseth: 3/3 Their 'muPC' algorithm provides a local, biologically plausible, and highly scalable equivalent to backprop. A deserved….

We’re extending the submission deadline for the International Workshop on Biomedical Image Registration, to the 27th June at 23:59 AOE! @wbir_info @AlessaHering.

RT @GianniFranchi10: 🚀If you're coming to @eccvconf consider going to our workshop on Uncertainty Quantification at #ECCV2024 (with Andrea….

Accepted papers will be published in LNCS. Deadline for submissions is 24th June, so there's no time to waste! See our website for more details: @wbir_info @AlessaHering.

We're hosting the 11th International Workshop on Biomedical Image Registration (WBIR) in association with Learn2Reg as a MICCAI satellite workshop in Marrakesh on Sunday 6th October!.Please submit your works on developments and applications of image registration!.

You can find our code at and an explanatoru video from Aisha on the @SussexAI YouTube channel

This enables flexible task-specific registration without ad-hoc hyperparameter tuning. So far we've looked at brain MRI registration using cLapIRN and NiftyReg, but we're looking to extend to more modalities and different scenarios so get in touch if you want to collaborate.

In this work we demonstrate how to use ML for predicting the (often substantial) effect of regularisation hyperparameters when registering image pairs. Our approach allows us to efficiently infer the instance-specific optimal hyperparameter at test time without labelled data.

Proud to announce that Aisha Lawal Shuaibu (one of my PhD supervisees) has had her first paper published in @MELBAJournal! The title is HyperPredict: Estimating Hyperparameter Effects for Instance-Specific Regularization in Deformable Image Registration

@SussexUni @SussexAI @EngInfSussex.

@SussexUni Please share with prospective students! If anyone has any question do get in touch with me (as the course convenor) directly. Looking forward to meeting our first intake in September 2024!.

@SussexUni with a substantial research project and unique new modules covering advanced technical concepts, applications and implications of AI, as well as core research and scientific communication skills.

3 new studentships to join us for a #phd in #AI @SussexUni within @SussexAI. If you're interested in developing new methods for probabilistic/generative machine learning for medical imaging, computer vision or ecological monitoring, get in touch with me!.

RT @HawksFCOfficial: 🎬 FT | Whitehawk 3-1 Lewes. The South Downs are red and white. Send Tweet.

RT @kieranagibb: Next Tuesday I'll be talking at @braincoustics about our research at Sussex (in collaboration with @alicealicealice @IvorS….

RT @arnosolin: (The 2nd) Workshop on Uncertainty Quantification for Computer Vision @ICCVConference morning session running in Paris: https….

RT @kieranagibb: In our recent preprint @IvorSimpson4 @alicealicealice, @Nature_Based and I outline the need of fu….

RT @kieranagibb: Today the pre-print of a paper summarising my work over the past year is up on bioRxiv - working towards interpretable mac….