Category / Computer Science

Insights from the Alan Turing Institute Data Study Group

Stepping into the world of data science at the Alan Turing Institute (ATI) Data Study Group from September 9-13, 2024 was an exhilarating experience. As the national institute for data science, the ATI’s strong connections to academia and industry set the stage for a week of intensive collaboration and problem-solving.

Joining the Transport for London (TfL) project within the hackathon-style event, I found myself amidst an eclectic team of 11 individuals, each bringing a unique set of skills and backgrounds to the table. The project’s challenge of identifying physical assets on the London Underground from point cloud data presented a thrilling opportunity to apply our collective expertise to a real-world problem.

The task at hand was no small feat – analysing point cloud data to pinpoint key track features along the London Underground network. With collected image data, our goal was to automate the detection and classification of critical track components such as sleepers, rails, signalling equipment, and more. Our team’s approach was multifaceted, involving rigorous preprocessing, segmentation model training, and advanced data analysis techniques. By leveraging tools like U-Net and SAM 2 for image segmentation and employing post-processing methods to extract valuable insights from the predicted masks, we made strides towards achieving our objectives.

As an individual who recently completed a PhD thesis on “Complex Urban Road Networks: Static Structures and Dynamic Processes,” this opportunity to apply my research expertise in a practical setting was both challenging and rewarding. The seamless blend of academic knowledge and hands-on problem-solving during the ATI Data Study Group not only expanded my technical skills but also reinforced the importance of interdisciplinary collaboration in tackling complex data challenges.

Thanks to The Alan Turing Institute,  especially TuringDSG organisers for an incredible opportunity. I would like to extend my gratitude to my PhD supervisor Dr. Wei Koong Chai for supporting my professional and personal development.

Assemgul Kozhabek (Computing Department, SciTech  )

Third INRC Symposium: Interdisciplinary Computational and Clinical Approaches at the Edge of Brain Research

Last month, we celebrated the third symposium of the Interdisciplinary Neuroscience Research Centre at the Inspire Lecture Theatre, entitled “Interdisciplinary Computational and Clinical Approaches at the Edge of Brain Research”.

This year, our symposium revolved around two linking themes: applied machine learning for understanding neuroscientific data and translational neuroscience. We choose to contrast these two themes because they show the breadth of areas of the centre and steer the debate on potential synergies.

The event started with an exciting talk by Prof. Miguel Maravall (director of the Sussex Neuroscience Centre of Excellence, Sussex University).  Dr Maravall presented new experiments testing the idea that the function of the somatosensory cortex -beyond processing input information about an object’s features- represents the decision to act and even the outcomes of such actions. The recording of this lecture is available here.

Next, the first session concentrated on computational approaches. In this focused session, we enjoyed three talks. The opening talk by Michak Gnacek (Emteq Labs Emteq Labs, Brighton and Centre for Digital Entertainment, BU) showcased his appealing results on affect recognition in Virtual Reality leveraging multimodal physiological recordings and continual machine learning. The second speaker was Dr Géza Gergely Ambrus (Department of Psychology, BU). Dr Ambrus presented gripping new findings that extend the application of multivariate pattern analysis beyond face perception to other facial characteristics to explore underlying neural mechanisms. Finally, Dr Matteo Toscani (Department of Psychology, BU) discussed a series of intriguing studies over the recent years on unsupervised learning approaches -such as avant-grade deep autoencoders- for inferring haptic material properties.

After this first session, Prof. Jonathan Cole (University Hospital Dorset, NHS) opened the second session centred on clinical neuroscience. In his inspiring talk, Dr Cole discussed his research on patients with congenital and acquired complete absence of touch and movement/position, showing how the absence of these senses leads to different alterations in proprioception. Next, Prof. Caroline Edmonds (Department of Psychological Sciences, University of East London) presented a fascinating study on real-life implications of co-occurring memory impairments in children with neonatal hypoxic-ischaemic encephalopathy. The study evaluated memory function in school-aged children with this condition who received hypothermia treatment and survived without extensive neuromotor impairment.

To conclude the symposium, Prof. Birgit Gurr (Community Brain Injury and Adult Neuropsychology Services Dorset at Dorset HealthCare University, NHS) and Dr Ellen Seiss (Department of Psychology, BU) introduced a compelling evaluation of the dynamic information processing programme, encompassing mental exercises fostering the recovery of patients from a stroke.

After the symposium, we visited the Multimodal Immersive Neuro-sensing lab for natural neuro-behavioural measurement (MINE), led by Dr Xun He.

All in the INRC would like to wholeheartedly thank the speaker and the attendees for the fascinating talks and exciting debates we had. If you are interested in getting in touch, contributing or joining the Interdisciplinary Neuroscience Research Centre, please do not hesitate to contact Ellen Seiss (eseiss@bourenmouth.ac.uk) or Emili Balaguer-Ballester (eb-ballester@bournemouth.ac.uk).

Thank you again for your interest, and we are looking forward to seeing you in our upcoming activities.

Kind regards,

Ellen and Emili, on behalf of all of us at the INRC

 

ACM SIGCOMM Test of Time Award

 

Happy to share that our paper entitled “Probabilistic in-network caching for information-centric networks” published in ACM ICN 2012 has been identified as one of the top 1% most cited/downloaded papers in the ACM Digital Library from those published between 2012-2014 and was considered for the 2024 ACM SIGCOMM Test of Time Award. The research was part of the work conducted under the EU ICT COMET project.

The paper was co-authored by Wei Chai,  Yiannis Psaras (protocol.ai) and George Pavlou (University College London).

🌟Exciting News in Complex Networks Research🌟

I am thrilled to share that I have been honoured to receive the Scholarship for Events on Complex Systems (SECS) from the Young Researchers of the Complex Systems Society (yrCSS). This prestigious award will allow me to attend the upcoming Complex Networks 2024 conference in Istanbul, Turkey from December 10-12, 2024.

          

My PhD research focuses on “Complex Urban Road Networks: Static Structures and Dynamic Processes”, exploring the intricate dynamics of urban transportation systems. This field has always sparked my curiosity, and I am eager to delve deeper into this complex interplay of structures and dynamics.

In addition to this incredible opportunity, I am also a finalist in the multi-modal category of the TRA Vision Young Researchers 2024 Competition with my research project “Transport Capacity Planning for Mega-events”. It is truly humbling to be recognised for my work in this competitive arena.

I am grateful for the guidance and support of my PhD supervisor, Dr. Wei Koong Chai, whose expertise and mentorship have been invaluable throughout my research journey. I am excited about the upcoming conference, where I hope to further contribute to the field of complex networks research. Thank you for joining me on this incredible academic adventure!

Best wishes,

Assemgul Kozhabek

🌐🔬 #ComplexSystems #ComplexNetworks

See yrCSS: https://yrcss.cssociety.org/

Complex Networks 2024 conference: https://complexnetworks.org/

Interdisciplinary Computational and Clinical Approaches at the Edge of Brain Research

We cordially invite you to the 3rd Symposium of the BU Interdisciplinary Neuroscience Research Centre on Wednesday, the 12th of June 2024, from 9:30-13:00 at the Inspire Lecture Theatre, Fusion Building (1st floor).

The symposium is entitled: “Interdisciplinary Computational and Clinical Approaches at the Edge of Brain Research”.

This third symposium revolves around contrasting computational and translational methodologies from a cross-disciplinary standpoint, leveraging synergies between BU and our collaborators in other universities and at the NHS. It is an opportunity for informal discussions on grant proposals and to explore shared interests with our external guests. The general schedule is as follows:

9:15. Welcome and coffee.

9:30. Keynote talk: Prof. Miguel Maravall, Sussex University.

10.20-10:40. Coffee and grants discussion.

10:40-11:40. Session I. Integrating Cognitive and Computational Neuroscience.

11.40 -12.00. Coffee and grants discussion.

12.00-13:00. Session II. Interdisciplinary Clinical Approaches & Concluding Remarks.

If you have any queries, please do not hesitate to contact Ellen Seiss, eseiss@bournemouth.ac.uk or Emili Balaguer-Ballester, eb-ballester@bournemouth.ac.uk.

Thank you very much, and we are looking forward to seeing you there.

Kind regards,

Ellen and Emili, on behalf of all of us.

 

 

 

 

Cross-university Multidisciplinary Research

In December, I had the pleasure of participating in an expert panel addressing AI testing at the International Conference on Artificial Intelligence at Peterhouse College, at the University of Cambridge. You might be wondering what brought a cybersecurity researcher to an AI-centric event. I had the same scepticism when my multi-university research group decided we conduct AI-related research; what would my contribution be?

Our work has focused on defining meta-data for AI provenance, contributing to advancements in various facets of AI, including testing and auditability. Specifically, my focus lies on evaluating the dimensions of risk and trust within this context. Given the widespread impact of AI across diverse domains, there is a compelling opportunity for multidisciplinary research, consecutively, our group, has diverse expertise ranging from machine learning to psychology.

An initial publication on our work can be found here.

Author Dr Andrew M’manga

Discovering Causal Relations and Equations from Data

Discovering equations, laws, or invariant principles underpins scientific and technical advancement. Robust model discovery has typically emerged from observing the world and, when possible, performing interventions to falsify models.

Recently, data-driven approaches like classic and deep machine learning are evolving traditional equation discovery methods. These new tools can provide unprecedented advances in computer science, neuroscience, physics, philosophy, and many applied areas.

We have just published a new study discussing concepts and methods on causal and equation discovery, outlining current challenges and promising future lines of research. The work also showcases comprehensive case studies in diverse scientific areas ranging from earth and environmental science to neuroscience.

Our tenet is that discovering fundamental laws and causal relations by observing natural phenomena is revolutionised with the coalescence of observational data and simulations, modern machine learning algorithms and domain knowledge. Exciting times are ahead with many challenges and opportunities to improve our understanding of complex systems.

This study is a collaborative work between eight universities in Europe and the United States (Valencia, Berlin, Tübingen, Jena, Stockholm, New York, and Bournemouth Universities).

Camps-Valls, G., Gerhardus, A., Ninad, U., Varando, G., Martius, G., Balaguer-Ballester, E., Vinuesa, R., Diaz, E., Zanna, L. and Runge, J., 2023. Discovering causal relations and equations from data. Physics Reports, 1044, 1-68 (Impact Factor=30).

 

CuttingGardens2023 conference in Bournemouth

The MINE Research Cluster and EEG Lab are hosting a four-day CuttingGardens 2023 conference in Bournemouth during 16-19 October 2023. CuttingGardens is a distributed conference on cutting-edge methods for EEG/MEG data analysis, with 20+ “gardens” happening simultaneously at several locations across the world. The common global programme, broadcasted to all locations, includes cognitive neuroscience advances, real-time EEG analysis, reproducible research, and deep neural network. Our Bournemouth Garden’s local programme has hands-on #EEGLab and #MNE-Python tutorials, EEG-VR and EEG-eye tracking workshops, exciting talks and tour of state-of-the-art labs!

Key dates:
Abstract submission deadline: 15 September 2023
Registration deadline: 27 September 2023
Conference: 16-19 October 2023

More information can be found at https://cuttinggardens2023.org/gardens/bournemouth/. Please check the webpage if you are interested. This is an ideal event for anyone who is keen to elevate their EEG/MEG research skills. We welcome research students, postdocs, academics and professionals alike.

Bournemouth Garden Organising Committee:
Xun He, Ellen Seiss, Marina Kilintari, Federica Degno, Ruijie Wang, Andrew Hanson, and Biao Zeng (University of South Wales, BU’s Visiting Fellow)

 

INRC seminar by Dr Jie Sui, Friday the 8th of September at 14.00 h, Share Lecture Theatre (Fusion).

We want to draw your attention to a seminar organized by the Interdisciplinary Neuroscience Research Centre on this Friday, the 8th of September, from 14:00 h to 15:00 h at the Share Lecture Theatre (Fusion Building). There will be a networking event after the talk with coffee and biscuits.

Our guest speaker is Dr. Jie Sui (University of Aberdeen), invited by Dr. Ellen Seiss. Prof Dr Sui is renowned for her studies investigating the unique self, self-representation, and social interactions in VR. Her research combines multiple neural recording modalities, such as EEG and fMRI, with computational modelling.

The title of this exciting talk is: “Understanding the Self: Prospects for Translation”. Please find the abstract below.

We warmly invite you to attend this seminar.

Kind regards,

Ellen and Emili, on behalf of all of us.

Abstract:

“An understanding of the self helps explain not only human thoughts, feelings, and attitudes but also many aspects of everyday behaviours. This talk focuses on a particular perspective on self-processes. This perspective highlights the dynamics of the self that best connects with the development of the self over time and its realist orientation. We are using psychological experiments and data mining to comprehend the stability and flexibility of the self in different populations.

In this talk, I integrate experimental psychology, associative learning theory, computational neuroscience, and machine learning approaches to demonstrate why and how self-association affects cognition and how it is modulated by various social experiences and situational factors.”

INRC seminar by Dr Jie Sui, Friday the 8th of September at 14.00 h, Share Lecture Theatre (Fusion).

We want to draw your attention to a seminar organized by the Interdisciplinary Neuroscience Research Centre on Friday, the 8th of September, from 14:00 h to 15:00 h at the Share Lecture Theatre (Fusion Building). There will be a networking event after the talk with coffee and biscuits.

Our guest speaker is Dr. Jie Sui (University of Aberdeen), invited by Dr. Ellen Seiss. Prof Dr Sui is renowned for her studies investigating the unique self, self-representation, and social interactions in VR. Her research combines multiple neural recording modalities, such as EEG and fMRI, with computational modelling.

The title of this exciting talk is: “Understanding the Self: Prospects for Translation”. Please find the abstract below.

We warmly invite you to attend this seminar.

Kind regards,

Ellen and Emili, on behalf of all of us.

Abstract:

“An understanding of the self helps explain not only human thoughts, feelings, and attitudes but also many aspects of everyday behaviours. This talk focuses on a particular perspective on self-processes. This perspective highlights the dynamics of the self that best connects with the development of the self over time and its realist orientation. We are using psychological experiments and data mining to comprehend the stability and flexibility of the self in different populations.

In this talk, I integrate experimental psychology, associative learning theory, computational neuroscience, and machine learning approaches to demonstrate why and how self-association affects cognition and how it is modulated by various social experiences and situational factors.”

Broadening horizons: Network Science at Utrecht Summer School

We are thrilled to announce that Assemgul Kozhabek, one of our  PhD candidates, recently had the opportunity to participate in the Utrecht Summer School on “Data Science: Network Science” from July 10-14, 2023. Assemgul’s research, under the guidance of Dr. Wei Koong Chai, is centered around understanding and optimizing urban road networks. By attending this course, she was able to gain a deeper understanding of network science and its relevance to her research goals. The course covered various topics, including network modeling, analysis techniques, and practical application of network science in real-world scenarios.
The Utrecht Summer School provided Assemgul with a unique learning experience. Through interactive lectures, hands-on workshops, and networking opportunities with experts in the field, she was able to broaden her knowledge and enhance her skills in analyzing urban road networks. She expresses her gratitude to Dr. Wei Koong Chai for his support and guidance throughout this journey. Assemgul also immensely grateful for the OpenBright Award that made this opportunity possible.
Assemgul’s participation in the Utrecht Summer School on “Data Science: Network Science” has undoubtedly equipped her with valuable insights and tools that will contribute to her ongoing research. Stay tuned for exciting updates on her research journey!