Our people

The requisites of knowledge: a quick mind, zeal for learning, humility, foreign land, a professor’s inspiration, and a life of long span.

Juwaini of Nishapur (d.1085)

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Islem Rekik, Ph.D.

Director, BASIRA Lab
Associate Professor at Imperial College London (I-X Hub)

Email: i.rekik@imperial.ac.uk

Office: 5th floor, Imperial-X (I-HUB), White City Campus

Tel. : drop me an email.

Address: Imperial College White City Campus, Translation & Innovation Hub, 84 Wood Ln, London W12 0BZ

members (2025)

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Devvrat Joshi (MSc researcher)

Project: Scalable foundation model for automated knowledge graph generation from scientific literature

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Prajit Sengupta (MSc researcher)

Project: Reasoning-centric self-interpretable GNNS

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Shekhnaz Idrissova (MSc researcher)

Project: Sheaf-based networks for multimodal glioma grading and survival prediction

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Yitong Luo (MSc researcher)

Project: Tree-based graph generation with application to brain connectivity

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Furkan Pala (Ph.D student)

Project: GNN affodability and uniformization

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Mayssa Soussia (Ph.D student)

Project: GNNs for modeling population-driven brain hyperconnectivity.

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Arwa Rekik (Researcher & Neurologist)

Project: Brain mapping in health and neurological disease.

ALUMNI

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Pragya Singh (MSc researcher)

Project: Dual GNNs for graph superresolution, with application to connectomics.

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Gita Salsabila (MSc researcher)

Project: Reservoir-based graph convolution networks.

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Jiameng Liu (Visiting Ph.D student)

Project: Affordable GNNs via hyper-sampling.

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Hugo Frelin (MSc researcher)

Project: A GNN Framework For Adaptive Node Updates.

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Scarlet Xiao (UG researcher)

Project: Dynamic memory-enhanced generative GNNs for predicting temporal brain connectivity.

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Yijun Lin (UG researcher)

Project: Cognifying generative GNNs

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Atefe Hassani (Guest researcher)

Project: Universal federation of a xixture of highly heterogeneous medical image classification tasks.

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Kevin Mancini (MSc researcher)

Project: Solving the challenge of short and long-range message passing in GNNs.

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Ramona Ghilea (MSc researcher)

Project: Federated learning using small datasets.

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Nishant Rajadhyaksha (Researcher)

Project: Diffusion models for super-resolving brain graphs.

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Michalis Pistos (MSc researcher)​

Project: Federated multi-trajectory GNNs under data limitations for baby brain connectivity forecasting.

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Jia Ji (MSc researcher)

Project: Federated Multigraph Integration for Brain Template Learning.

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Emircan Gündoğdu (UG researcher)

Project: Template-based multi-domain federation.

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Chun Xu (MSc researcher)

Project: Federated brain connectivity evolution prediction.

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Christopher Adnel (MSc researcher)

Project: Affordable GNN models.

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Fatih Duran (Researcher)

Project: Hierarchical GNN for population-driven brain connectional template learning.

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Doga Turkseven (Researcher)

Project: Deep shape analysis for neurological disorder diagnosis.

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Mehmet Yigit Balik (Researcher)

Project: Investigating the reproducibility of GNN federated models.

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Selim Yurekli (Researcher)

Project: Predictive uncertainly of GNN models with domain shifts.

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Oben Ozgur (Researcher)

Project: One-shot federated learning.

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Yekta Can Tursun (Researcher)

Project: Federating non-OOD GNNs.

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Mert Can Kurucu (Researcher)

Project: Influencer samples in integration tasks.

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Oytun Demirbilek (Researcher)

Project: Recurrent prediction of population graph templates from a single timepoint

Furkan Pala (Researcher)

Project: A template-guided training of graph neural networks.

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Guris Ozen (Researcher)

Project: A few-shot learning using representative templates for predicting brain connectivity evolution.

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Başar Demir (Researcher)

Project: Inter-modality brain graph superresolution.

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Ahmed Nebli (Researcher)

Project: Developing integrational connectomics using geometric deep learning.

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Islem Mhiri (Ph.D, Mentor)

Project: Developing predictive intelligence in medicine by super-resolving brain data; in collaboration with LATIS Lab, ENISo University.

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Nada Chaari (Ph.D)

Project: Learning brain multigraph integration using machine and geometric deep learning.

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Zeynep Gurler (undergrad)

Project: Foreseeing brain graph evolution over time using deep adversarial network normalizer.

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Martin Hanik (Mentor)

Project: Regression graph neural networks for brain cognitive score prediction.
Affiliation: Zuse Institute Berlin

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Mehmet Arif Demirtas (undergrad)

Project: Regression graph neural networks for brain cognitive score prediction.

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Alaa Bessadok (Ph.D, Mentor)

Project: Predicting missing multimodal neuroimaging driven data for boosting neurological disorder diagnosis; in collaboration with ISSAT University.

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Furkan Tornaci (Researcher)

Project: Reproducibility of GNN models.

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Sinem Elif Haseki(Researcher)

Project: Brain multigraph integration.

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Ece Çınar (Researcher)

Project: Project: Brain multigraph integration.

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Umut Guvercin (Researcher)

Project: A few-shot learning for diagnostic tasks.

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Mohammed Amine Gharsallaoui (Researcher, Mentor)

Project: Brain network integration using deep meta-paths.

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Alpay Tekin (Researcher)

Project: Graph neural networks for brain connectivity synthesis.

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Megi Isallari (undergrad)

Project: Super-resolving brain graphs using geometric deep learning.

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Mustafa Burak Gurbuz (undergrad)

Project: Estimating connectional brain templates using geometric deep learning.

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Ahmet Serkan Goktas (undergrad)

Project: Residual embedding similarity-based network selection for predicting brain network evolution trajectory from a single observation.

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Ugur Demir (undergrad)

Project: Brain network integration using deep meta-paths.

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Ugur Ali Kaplan (undergrad)

Project: Can we predict the future of the brain connectivity using a single timepoint?

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Montassar Ben Dhifallah (undergrad)

Project: Can we predict the future of the brain?

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Göktuğ Güvercin (undergrad)

Project: Developing a Python machine learning toolbox for brain network classification. http://github.com/basiralab/BrainNet-ML-ToolBox

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Inis Buzi (undergrad)

Project: Geometric embedding of brain hyperconnectomes in predictive learning.

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Alin Banka (undergrad)

Project: Geometric embedding of brain hyperconnectomes in predictive learning.

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Abdullah Yalcin (undergrad)

Project: Classification of multi-sized multi-view connectomic datasets for developing unified precision medicine .

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Mustafa Saglam (undergrad)

Project: Profiling neurological disorders using diffused brain multigraphs for disentangling connectivity changes across disorders.

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Kübra Cengiz (Ph.D)

Project: Designing machine-learning based models for predicting high-resolution medical data from low-resolution data.

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Olfa Ghribi (Postdoc)

Project: Baby cortical network evolution prediction; in collaboration with IDEA Lab, University of North Carolina (UNC).

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Oumaima Ben Khelifa (MSc)

Project: Graph morphology learning for brain connectivity mapping and analysis.

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Baha Eddine Ezzine (Research intern)

Project: Predicting the spatiotemporal evolution of healthy and disordered brain trajectories

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Olfa Graa (Research intern)

Project: Multi-View LEArning-based data Proliferator (MV-LEAP) for boosting classification using highly imbalanced classes

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Nesrine Bnouni (Ph.D)

Project: Developing machine learning methods for automatic cervical cancer labeling and stratification; in collaboration with LATIS Lab, ENISo University.

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Nicolas Georges (MSc)

Project: How to identify the most reproducible features disentangling brain states for a dataset of interest?

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Minghui Zhu (MSc)

Project: Predicting target multiple brain networks from a source network.

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Can Gafuroğlu (undergrad)

Project: Predictive intelligence for early diagnosis of neurological disorders.

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Josh Corps (undergrad)

Project: Predicting the morphological age of the brain in healthy and disordered populations.

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Rory Raeper (undergrad)

Project: Ensemble learning classifier for early dementia diagnosis.

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Elizabeth Dryburgh (MRC DTP student)

Project: Investigating the functional wiring of human brain intelligence in neurotypical and autistic subjects.

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Mayssa Soussia (MSc)

Project: Network analysis for brain disorder diagnosis.

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Salma Dhifallah (MSc)

Project: Estimation of network atlases from large-scale connectomic datasets.

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Ines Mahjoub (MSc)

Project: Developing advanced network analysis tools for Alzheimer’s disease diagnosis. In collaboration with ENISo, LATIS lab Tunisia.

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Carrie Morris (MSc)

Project: Computer-aided diagnosis of Autism Syndrome Disorder. University of Dundee

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Anna Lisowska (MSc)

Project: Developing advanced healthcare methods for early dementia diagnosis. University of Dundee

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Samya Amiri (Ph.D)

Project: Developing machine learning techniques for brain tumor segmentation. In collaboration with ENISo, LATIS lab Tunisia.