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Members

and their Research

Collage School Topic of the
project
Lead researcher Lead researcher
email
Lead researcher
esteem
Collab
Internal
Collab
External
Outputs Fundings Plan for next 2
years
PhD supervision
of relevant projects
Public
engagement
How has your
research informed/will inform teaching
DCDI CSE Ai
Use in Cyber Security for data analysis and tracking
Dr
Ayman El Hajjar
a.elhajjar@westmimnster.ac.uk - - Adrian
Kingwell,
Mezzo Labs
KTP
UK innovate- Algorithm that tracks anomalies in the usage of private
data
[External] Adrian Kingwell, Mezzo
Labs
[Internal] Ayman El
Hajjar, Dimitris Parapadakis university of Westminster
[Submitted, received and completed.
KTP]
- PhD
Director of studies for three PhD students in the field of Cyber
security.
- Many
of our MSc Cyber Security and Forensics conduct their MSc projects on this
topic. This is because we emphasise on this topic in several lectures, and we
discuss how AI will enhance cyber security posture and how it can also
disrupt their work as malicious actors will also use it.
DCDI CSE The
use of AI to filter traffic in home environments
Dr
Ayman El Hajjar
a.elhajjar@westmimnster.ac.uk - - - Design
of software and the AI algorithm to monitor traffic in real-time
[Internal]
Ayman El Hajjar, Tamas Kiss, Dimitris Parapadakis
[Submitted, received and completed. UK Innovate CYBER ASAP]
- PhD
Director of studies for three PhD students in the field of Cyber
security.
- Many
of our MSc Cyber Security and Forensics conduct their MSc projects on this
topic. This is because we emphasise on this topic in several lectures, and we
discuss how AI will enhance cyber security posture and how it can also
disrupt their work as malicious actors will also use it.
DCDI CSE Enhancing
Data Mining Systems via Ontological Semantic Methods
Natalia
Yerashenia
Lecturer
in Data Science and Analytics, MSc projects Supervisor for Business
Intelligence & Analytics students, British Computer Society academic
member, IEEE Conference of Business Informatics conference speaker (2022)
Alexander
Bolotov,
David Chan You Fee
- Our
team is developing an AI-driven data mining system that utilizes ontological
semantic methods to automate analytical conclusions. This system, designed
with a particular use-case of financial data prediction such as stock prices,
leverages machine learning techniques to manage substantial heterogeneous
data, effectively integrating AI with ontology and graph-based methods. The
output of this research will be a groundbreaking data preprocessing and
feature selection strategy for AI models, improving the efficiency of data
mining in the financial sector.
- Over
the next two years, our primary focus will be integrating semantic components
into our data mining system, enabling AI to contextually interpret data. We
aim to formalize theoretical concepts using RDF or OWL Ontology to establish
a unified framework for data analysis, specifically targeting financial data
prediction. We also intend to create a comprehensive library of concepts for
users and developers, facilitating better collaboration in AI and data
analysis projects within the finance sector.
- Presenting current outcomes on IEEE Conference of Business Informatics conference speaker
(June, 2022)
This research
provides practical insights into the merging of AI and ontological semantic
methods, thereby deepening our understanding of data mining systems. We aim
to leverage these insights to teach students the practical applications of
advanced AI and data pre-processing methodologies in real-world contexts,
thereby strengthening their proficiency in AI-driven data analysis.
DCDI CSE CODEMATICS:
Bridging Mathematics and Programming Modules for BSc in Computer Science
students
Natalia
Yerashenia
Lecturer
in Data Science and Analytics, MSc projects Supervisor for Business
Intelligence & Analytics students, British Computer Society academic
member, IEEE Conference of Business Informatics conference speaker (2022)
Alexander
Bolotov,
Ester Bonmati Coll,
Barbara Villarini
- Through
CODEMATICS, we aim to create a conceptual mapping between level 4 mathematics
and software development. This map will serve as an open-access resource for
students. We are constructing a website that hosts a task library
illustrating the intersection of math and programming principles in
problem-solving. Additionally, we strive to formulate a methodology to
evaluate the synergy effect of math and computing on student learning.
- We
intend to expand the conceptual map to cover higher education levels and
enrich the task library with additional relevant examples. We will also
investigate the pedagogical implications of the synergy between computational
and mathematical thinking and consider potential opportunities for
integrating mathematics into other disciplines.
- CODEMATICS
University of Westminster workshop (April, 2023)
Our
research is fundamental in understanding and teaching the intrinsic
relationship between maths and software development. The conceptual mapping,
task library, and methodologies developed through CODEMATICS will directly
benefit students, while providing educators with deeper insights into student
needs. We anticipate the outcomes of this project to be directly implemented
in relevant modules, impacting a large student population. This will provide
students with practical problem-solving insights and a strong foundation for
later studies in AI and Data Analysis.
DCDI CSE Towards
text-based Process Mining
Rolf
Bänziger
r.banziger@westminster.ac.uk - - - Bänziger,
R.B., Basukoski, A., Chaussalet, T. (2023). Discovering Process Models from
Patient Notes. In: Mikyška, J., de Mulatier, C., Paszynski, M.,
Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational
Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10475.
Springer, Cham. https://doi.org/10.1007/978-3-031-36024-4_18

Banziger, R.B., Basukoski, A. and Chaussalet, T., 2018, June. Discovering
Business Processes in CRM Systems by leveraging unstructured text data. In
2018 IEEE 20th International Conference on High Performance Computing and
Communications; IEEE 16th International Conference on Smart City; IEEE 4th
International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
(pp. 1571-1577). IEEE.
Self-funded Submit
paper to top Process Mining Conference.

Investigate combination of text-based Process Mining and discrete event
simulation.

Publish PhD Thesis.
DCDI CSE Generative
AI for Programming Education
Roubert s.roberts4@westminster.ac.uk - - WIUT - WIUT-UOW
RESEARCH COLLABORATION FUND 2023
[Submitted]
WP1.
Literature review and identification of potential areas of intervention
WP2. Testing Potential of generative AI in programming classrooms
WP3. Designing formative assessment
WP4. Data collection
WP5. Evaluating students' understanding
WP6. Evaluating students' input on feedback
WP7. Analysis and results
Research
Project on Generative AI for Programming Education is expected to have a
direct impact on our teaching and inform the way generative AI can be used to
support teaching and learning activities, assessment design and conduct, and
the provision of constructive feedback.
DCDI CSE Sentiment
analysis for financial forecasting
Roubert s.roberts4@westminster.ac.uk - - - - supervision
with Dr Chountas
DCDI CSE AI
and Vehicular Sensing
Dr
Anastasia Angelopoulou
- - - Hertfordshire
University, UK, Karunya University, India and Alicante University, Spain
16
published outputs in journals and conferences since 2013
- - - - -
DCDI CSE Data
privacy and AI
Dr
Anastasia Angelopoulou
- - Law
school at Westminster
- - - - - - -
DCDI CSE AI
driven Applications for the automatic segmentation and reconstruction of
abdominal organs from medical images
Dr.
Barbara Villarini
b.villarini@westminster.ac.uk Keynote
and Invited Speaker:
- 05/08/2023 - Keynote speaker - 4th
International Conference on Innovations in Info-business & Technology
(ICIIT 2023)
Artificial Intelligence for the Automatic Organ Reconstruction and
Morphological Features Extraction from Medical Images. The Impact on
Healthcare.

- 03/09/2022 Invited speaker - Royal Academy of Engineering – Research
Programme Induction Event - AI-Driven
Organs Analysis and Reconstruction for Medical Application

- 05/2022 Keynote speaker - WIUT-UoW Computing Conference 2022

- 11/05/ 2023 – Invited Speaker for “The Value of Design & the Arts for
Collaborative Healthcare Interventions - UoW Workshop”

- 26/02/2021 - UCL - Computer Assisted Navigation, Diagnosis and
Intervention Seminars – UCL

- 13/05/2021 Research talk, Computational Radiology Lab, Harvard Medical
School - 3D Deep Learning for Organ
Segmentation from medical images

Consulting/Advisor:
23/03/2023 Member of External Advisory Board for a European EU project
called TERMINET (https://terminet-h2020.eu) Programme: H2020-ICT-2020-1
Conference Organization:

IoTI5 2023 – Organizing Committee
5th International Workshop on IoT Applications and Industry 5.0. Coral Bay,
Pafos, Cyprus, June 19 to 21, 2023
To be held in conjunction with IEEE DCOSS-IoT 2023
Link: http://ioti5-2023.cs.ihu.gr/committees

Memberships:
I am member of the:
- IEEE Institute of Electrical and Electronics Engineers
- TCCL Technical Committee on Computational Life Sciences.
- BMVA – The British Machine Visio Association

Committee Member:
MICCAI 2023 – Medical Image Computing and Computer Assisted Intervention
(every year since 2017)
CBMS 2023 – IEEE International Symposium of Computer Based Medical
Systems
LIM 2021 – London Imaging for Deep Learning
ICDP 2019 – International Conference on Imaging for Crime Detection and
Prevention

Regular Reviewer for:
Data Mining and Knowledge Discovery – Springer
Information Sciences – Elsevier
IEEE Transactions on Multimedia
Signal Processing: Image Communication –Elsevier
MDPI Sensors
SPIE journal of Medical Imaging
Prof.
Jimmy Bell, Prof. Louise Thomas
Harvard
medical School, Boston Children’s Hospital, UCL
*
Royal Academy Of Engineering Research Fellowship (09/2020-01/2022)

*Web application for the automatic organ reconstruction - open source and
available online

*Journal and Conference publications:
Asaturyan, H., Villarini, Barbara, Sarao, Karen, Chow, Jeanne S, Afacan,
Onur and Kurugol, Sila 2021. Improving Automatic Renal Segmentation in
Clinically Normal and Abnormal Paediatric DCE-MRI via Contrast Maximisation
and Convolutional Networks for Computing Markers of Kidney Function. Sensors.
21 (23) 7942.

B. Villarini, H. Asaturyan, S. Kurugol, O. Afacan, J.D. Bell, E.L. Thomas.
“3D Deep Learning for Anatomical Structure Segmentation in Multiple Imaging
Modalities”. 34th IEEE International Symposium on Computer-Based Medical
Systems (June 2021) - Best Paper Award (First Classified)

Villarini, B. and Asaturyan, H. 2022. AI Driven IoT Web-Based Application
for Automatic Segmentation and Reconstruction of Abdominal Organs from
Medical Images. IEEE International Conference on Distributed Computing in
Sensor Systems (DCOSS). Los Angeles, California 30 May - 01 Jul 2022 IEEE .

Asaturyan, H., Thomas, L. E., Fitzpatrick, J., Bell, D. J. and Villarini,
B. (2019). Advancing Pancreas Segmentation in Multi-protocol MRI Volumes
Using Hausdorff-Sine Loss Function. International Workshop on Machine
Learning in Medical Imaging (MLMI) in conjunction with International
Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
2019, Springer.
Asaturyan, H., Thomas, E.L., Bell, J.D., Villarini, B., “A Framework for
Automatic Morphological Feature Extraction and Analysis of Abdominal Organs
in MRI Volumes”, Journal of Medical Systems, Springer (December 2019)
[External] Start Date: 11 November
2018
End Date: 31 October 2020
Project title: Evolution of Enriched-Phenotypes for Health Exploration and
Discovery
Funder: Calico
Funding received: £570,170.00
Status: Awarded
PI: Jimmy Bell
Co-I: Louise Thomas, Barbara Villarini

[Internal] Submission Date: June 2021
Funding: Research Development Office – University of Westminster
Duration: 24 months
Award: Research development Award
Funding awarded: £10,000.00

Submission date: April 2022
Project Title: Swarchestrate - Swarm-based distributed self-organising
application-level orchestrator for the cloud to things
continuumArchitecture
Call: HORIZON-CL4-2023-DATA-01-04
Duration: 36 months
Funding requested: €722,692.00
PI: Tamas Kiss
Co-I: Gabor Terstyanszky, Barbara Villarini, Francesco Tusa
Result: Submitted
In
the last few years, I have been working on a research project on “AI-driven
Organ Reconstruction and Morphological Features Extraction from Medical
Images” awarded by the Royal Academy of Engineering -Leverhulme Trust
Research Fellowship. The project helped to consolidate collaborations with
world-leading institutions such as Harvard Medical School and University
College London. The projected lead to numerous publications and one best
paper award in the IEEE Conference of Computer Based and Medical System.
The project has been considered with a great potential for impact in the
health system and currently, with the support of the College Director Prof.
Gregory Sporton and the Research Office, we are planning to hire a REA for
few months in order to improve the prototype, including 3D visualisation and
VR features, and make it usable in real case scenarios. The aim is to produce
a strong first prototype and then apply for WelcomeTrust or MRC’s grant at
the beginning of next academic year and involve a company that could be
interested in a potential commercialisation of the framework.
2016-2020–
Director of Studies Hykoush Asaturyian “Automatic Pancreas Segmentation and
3D Reconstruction for Morphological Feature Extraction in Medical Image
Analysis”, Awarded PhD with no
corrections.
External Collaboration: Harvard Medical School, Boston children’s
Hospital


2021/22 -today – Director of Studies-
Miss Rim El Badaoui “Title Robust Federated Deep Learning for Brain
Tumour Segmentation & Classification on multimodal medical images”.
Conference
Organization:

IoTI5 2023 – Organizing Committee
5th International Workshop on IoT Applications and Industry 5.0. Coral Bay,
Pafos, Cyprus, June 19 to 21, 2023
To be held in conjunction with IEEE DCOSS-IoT 2023
Link: http://ioti5-2023.cs.ihu.gr/committees

Memberships:
I am member of the:
- IEEE Institute of Electrical and Electronics Engineers
- TCCL Technical Committee on Computational Life Sciences.
- BMVA – The British Machine Visio Association

Committee Member:
MICCAI 2023 – Medical Image Computing and Computer Assisted Intervention
(every year since 2017)
CBMS 2023 – IEEE International Symposium of Computer Based Medical Systems
LIM 2021 – London Imaging for Deep Learning
ICDP 2019 – International Conference on Imaging for Crime Detection and
Prevention

Regular Reviewer for:
Data Mining and Knowledge Discovery – Springer
Information Sciences – Elsevier
IEEE Transactions on Multimedia
Signal Processing: Image Communication –Elsevier
MDPI Sensors
SPIE journal of Medical Imaging

Keynote and Invited Speaker:
- 05/08/2023 - Keynote speaker - 4th
International Conference on Innovations in Info-business & Technology
(ICIIT 2023)
Artificial Intelligence for the Automatic Organ Reconstruction and
Morphological Features Extraction from Medical Images. The Impact on
Healthcare.

- 03/09/2022 Invited speaker - Royal Academy of Engineering – Research
Programme Induction Event - AI-Driven
Organs Analysis and Reconstruction for Medical Application

- 05/2022 Keynote speaker - WIUT-UoW Computing Conference 2022

- 11/05/ 2023 – Invited Speaker for “The Value of Design & the Arts for
Collaborative Healthcare Interventions - UoW Workshop”

- 26/02/2021 - UCL - Computer Assisted Navigation, Diagnosis and
Intervention Seminars – UCL

- 13/05/2021 Research talk, Computational Radiology Lab, Harvard Medical
School - 3D Deep Learning for Organ
Segmentation from medical images
The
research projects that I am working on and that I intend to propose are
multidisciplinary works where computational techniques, image processing and
artificial intelligence approaches are utilised to improve the medical field.
This will have an enormous impact on the population wellbeing and health
condition. This is perfectly in line with the “Being Westminster” strategy,
which aims to make a stronger contribution to the world’ learning and
wellbeing through our research. Furthermore, the interdisciplinary nature of
the proposed research will unify the research community of Computer Science,
Engineering, Life Sciences, Biomedical and Biology. Numerous research outputs
will be produced and the teaching will be enriched by the research activity.
The students will learn state-of-the-art approaches and techniques in the
field of image processing and AI that could be applied in different fields
and areas. This will have an impact on module such as Applied AI (Level 6
module), and also final years project could be linked to this research topic,
providing valuable guidance and collaborations with external
institutions.
Furthermore, Collaborations with world-leading institutions will foster
exchange programs that could enrich our students experience. In particular
Harvard Medical School has already agreed to a 6-months exchange program with
one of our PhD students. This kind of collaborations will bring vibrant
opportunities to our students raising the University of Westminster
visibility and recognition.
DCDI CSE Development
of brain tumour segmentation methods based on deep learning and transformers
Dr.
Barbara Villarini
b.villarini@westminster.ac.uk - Dr.
Ester Bonmati, Dr. Alexandra Psarrou
- El
Badaoui, R., Bonmati Coll, E., Psarrou, A., Villarini, B. “3D CATBraTS:
Channel Attention Transformer for Brain Tumour Semantic Segmentation”, IEEE
36th International Symposium on Computer Based Medical Systems (CBMS) 2023.
June 22-24 – L’Aquila, Italy (In press)
[External] Funding body: Royal
Academy of Engineering – Leverhulme Trust
PI: Barbara Villarini
Result: Awarded
Funding awarded: £66,133.00

[Internal] Submission
Date: June 2023
Project title: AI-Driven Melanoma Detection at Early Stages with Mobile
Application
Call: WIUT-UOW RESEARCH COLLABORATION FUND 2023
Duration: 12 months
Funding Requested: £9,600.00
Collaborators: Hamid Reza Shahbazkia, Barbara Villarini, Ester Bonmati,
Shokhrukh Sultanov

European Project: Call HORIZON-CL5-2023-D6-01-10. The project is about the
development of a new monitoring and maintenance framework for providing and
improving European urban and secondary rural roads safety. Budapest
university is currently leading the project proposal.
Project submission: 05/09/2023
A
second project that I would like to work next year is about the development
of novel techniques for the early diagnosis of Crohn’s Disease. In
particular, I aim to apply for an EPSRC New Investigator Grant: The idea is
to build upon the fellowship project and apply AI, deep learning techniques,
for multimodalities image registration for the early diagnosis and evaluation
of the Crohn’s Disease. This will lead to the development of non-invasive and
safe procedures improving the conditions of patients suffering of this
disease. The proposed methods will be assessed in a clinical trial carried
out at the Boston Children Hospital in collaboration with Harvard Medical
School.

Also, in collaboration with University of Perugia and Kingston University
we are looking at the development of a deep learning federated approach for
Brain Tumour segmentation from different medical images modalities and
different medical images quality. Currently my PhD student is working on this
project and the aim is to identify some external funding in order to have at
least another researcher working on this topic.

Furthermore, an application in collaboration with WIUT has been submitted
to the WIUT-UOW RESEARCH COLLABORATION FUND 2023. The project aims to use AI
techniques to develop an accurate system for the detection of skin cancer
from mobile.

Furthermore, I have been working on building consortium for the submission
of proposal for the Horizon Europe Framework programme. In the 2022/23
academic year I have participated at two calls and I am currently awaiting
the results for one of them. If the results are positive part of the research
work will be dedicated to this project (my involvement is linked to the
application of deep learning techniques for the understanding and analysis of
images and data).
DCDI CSE Development
of novel AI approaches for scene understanding with application in healthcare
and autonomous vehicles
Dr.
Barbara Villarini
b.villarini@westminster.ac.uk - - Kingston
University
Bandy,
A.D., Spyridis, Y., Villarini, B. and Argyriou, V. 2023. Intraclass
Clustering-Based CNN Approach for Detection of Malignant Melanoma. Sensors.
23 (2), p. 926. https://doi.org/10.3390/s23020926

Rajegowda, M.g., Spyridis, Y., Villarini, B. and Argyriou, V. 2023. An
AI-Assisted Skincare Routine Recommendation System in XR. 2023 7th
International Conference on Artificial Intelligence and Virtual Reality
(AIVR2023). Springer. Kumamoto, Japan 23 July - 21 July 2023 Springer.

Villarini, B., Radoglou-Grammatikis, P., Lagkas, T., Sarigiannidis, P. and
Argyriou, V. 2023. “Detection of Physical Adversarial Attacks on Traffic
Signs for Autonomous Vehicles”. THE IEEE INTERNATIONAL CONFERENCE ON INDUSTRY
4.0, ARTIFICIAL INTELLIGENCE, AND COMMUNICATIONS TECHNOLOGY. Bali, Indonesia
13 - 15 July IEEE. (In press)

Li, V., Villarini, B., Nebel, JC. and Argyriou, V. 2023. “A Modular Deep
Learning Framework for Scene Understanding in Augmented Reality
Applications”. THE IEEE INTERNATIONAL CONFERENCE ON INDUSTRY 4.0, ARTIFICIAL
INTELLIGENCE, AND COMMUNICATIONS TECHNOLOGY. Bali, Indonesia 13 - 15 July
2023 IEEE. (In press)

V. Li, B. Villarini, J-C. Nebel, T. Lagkas, P. Sarigiannidis and A.
Vasileios, “Evaluation of Environmental Conditions on Object Detection using
Oriented Bounding Boxes for AR Applications”, 5th International Workshop on
IoT Applications and Industry 5.0, in conjunction with IEEE DCOSS-IoT 2023,
June 19-21 Pafos, Cyprus(In press)
- A
third EU project proposal is in preparation (Safe, Resilient Transport and
Smart Mobility services for passengers and goods (HORIZON-CL5-2023-D6-01), to
be submitted in September 2023. The aim is the development of a new
monitoring and maintenance framework for providing and improving European
urban and secondary rural roads safety. My contribution is related to the
design development of AI approaches. The project proposal is currently led by
Budapest University.

My research interests are about applying AI and computer vision techniques
also in other fields, e.g. for urban street safety and maintenance. One paper
is in preparation on this topic as a mobile app has been developed for this
purpose. Also, a paper has been recently accepted about the automatic
detection of road signal attacks for autonomous vehicles. The paper will be
presented next month to the IEEE International Conference on Industry 4.0,
Artificial Intelligence, and Communication Technology.
All these applications could lead to a potential impact on the society,
contributing to improve the quality of life through the use of technology.
DCDI CSE Distributed
computing architectures to support AI applications
Tamas
Kiss
t.kiss@westminster.ac.uk Several
conference keynotes, e.g. IOTBDS/Complexis 2023, PDGC 2020
Commercial platform to support manufacturing SMEs with cloud-based
execution of AI-based Digital Twins: https://www.emgora.eu/
Gabor
Terstyanszky, Francesco Tusa, Hamed Hamzeh, Gabriele Pierantoni, Huseyin
Dagdeviren, Jozsef Kovacs, James DesLauriers, Antonis Michalas, Amjad Ullah,
Huankai Chen, Alim Gias, Yang Ma, David Chen You Fee, Dimitris Kagialis
- 15+
journal publications, 30+ conference papers
[External] 8 EU projects with overall
value for the University £4 million+

[Under review]: 1 EU
proposal, value for UOW £700K+
Developing
a completely decentralised platform, based on SWARM computing and
decentralised AI, to support data and computing intensive application
execution in the cloud to edge computing continuum.
- Invited
lectures detailed in estemm.
In
module 6BUIS018W Information Driven Entrepreneurship and Enterprise most of
the industry facing research in heavily utilised.
DCDI CSE Medical
imaging & AI
Ester
Bonmati
e.bonmaticoll@westminster.ac.uk I
am a member of the Medical Image Computing and Computer Assisted Intervention
Society

I was part of the program committee at MICCAI 2022, the top conference in
medical imaging:
Link: https://conferences.miccai.org/2022/en/PROGRAM-COMMITTEE.html

Which led to the outstanding area chair award:
Link:
https://conferences.miccai.org/2022/en/OUTSTANDING-AREA-CHAIR-AWARDS.html

I was a reviewer for MICCAI 2021:
Link: https://www.miccai2021.org/en/LIST-OF-REVIEWERS.html

I am also a reviewer for UKRI (See review activity):
Link: https://orcid.org/0000-0001-9217-5438

I am also a reviewer of multiple top international journals and conferences
such as (selection):
- Medical Image Analysis (Impact factor of 13.828) -
https://www.sciencedirect.com/journal/medical-image-analysis
- IEEE Transactions in Medical Imaging (Impact factor of 11.037) -
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=42
- Expert Systems with Applications (Impact factor of 8.665) -
https://www.sciencedirect.com/journal/expert-systems-with-applications
- Computer Methods and Programs in Biomedicine (Impact factor of 7.027) -
https://www.sciencedirect.com/journal/computer-methods-and-programs-in-biomedicine
- IEEE Journal of Biomedical and Health Informatics (Impact factor of
7.021) -
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221020
- International Journal of computer Assisted Radiology and Surgery (Impact
factor of 3.421) - https://www.springer.com/journal/11548

And international conferences:
- Medical Image Computing and Computer Assisted Intervention (MICCAI) -
http://www.miccai.org/
- Information Processing Computer-assisted Interventions (IPCAI) -
https://www.ipcai.org/home
- Advances in Simplifying Medical UltraSound (ASMUS) -
https://miccai-ultrasound.github.io/#/asmus23?id=organizers
- Computer Assisted Radiology and Surgery (CARS) -
https://www.cars-int.org/

Generative AI special interest group (UoW)
Barbara
Villarini
- Research
papers, detection models
- - I
supervise Rim El Badoui together with Dr. Barbara Villarini and Dr. Aleka
Psarrou. This work is on brain segmentation using AI, and federative
learning. The supervision has recently led to a conference presentation.
- There
are several ways in which I use my research to inform my teaching, as
examples:
- Show real-world examples: I used an example on medical image
classification in cancer to demonstrate how AI can help in the medical
domain.
- State-of-the-art techniques: I use examples of recent papers to show
students what is the state-of-the art in AI techniques.
- Critical thinking: I use my research to develop student’s critical
thinking skills, by looking at the outputs of AI and evaluating the impact of
the results.
DCDI CSE Image
synthesis
Ester
Bonmati
e.bonmaticoll@westminster.ac.uk Sophie
Triantaphillidou
- - - - -
DCDI CSE AI
& Cancer detection
Ester
Bonmati
e.bonmaticoll@westminster.ac.uk CANDI
group (UCL)
Cancer
detection models, research papers
- - - - -
DCDI CSE Effect
of image quality in deep networks robustness
Dr
Alexandra Psarrou
psarroa@westminster.ac.uk leading
positions in AI& Data related organisations/bodies/societies, conference
chairing/PC membership, invited talks/lectures
Special Session: Machine Learning and Deep Learning Methods applied to
Vision and Robotics (MLDLMVR), Co-Chair,
IJCNN 2023
17th International Work-Conference on Artificial Neural Networks
(IWANN2023), program committee
Sophie
Triantaphillidou/ Rob Jenkins
A
framework for the metrification of input image quality in deep networks,
Electronic Imaging Conference, January 2023
[External] Sponsored PhD scholarship
(through S. Triantaphillidou). 3 years
scholarship started January 2023
- Mr
Pooryaa Cheraaqee - Image Quality for Deep Learning
- Research
will inform module in MSc Applied AI, and UG /PG projects
DCDI CSE Deep
Learning for Brain Tumour
Dr
Alexandra Psarrou
psarroa@westminster.ac.uk Rim
El Badaoui, Barbara Villarini, Ester Bonmati-Coll
3D
CATBraTS: Channel Attention Transformer for Brain Tumour Semantic
Segmentation, CBMS, June 2023
- - Miss
Rim El Badaoui - Robust Federated Deep Learning for Brain Tumour Segmentation
& Classification on multimodal medical images
- -
DCDI CSE Explainable
AI
Dr
Alexandra Psarrou
psarroa@westminster.ac.uk J.M. Gorizz et al, Review paper
with 20 collaborators
Computational
Approaches to Explainable Artificial Intelligence: Advances in Theory,
Applications and Trends, IWINAC 2022, International Work-Conference on the
Interplay Between Natural and Artificial Computation, June 2022
- Expand this area of research
towards valuation of image quality data using reinforcement learning and explainable AI
- - -
DCDI CSE Development
and implementation of a Decision Support Software tool for service redesign
including scenario generator. Exploration and development of novel hybrid
data mining algorithms through process modelling and simulation
Salma
Chahed
chaheds@westminster.ac.uk leading
positions in AI& Data related organisations/bodies/societies, conference
chairing/PC membership, invited talks/lectures
Associate editor – BMC Health Services Research (BMC HSR) - since January
2018
https://bmchealthservres.biomedcentral.com/about/editorial-board

Member of programme committee for WIUT-UoW Computing Conference 2022:
https://conference.wiut.uz/silkroadigital2022/

Member of a workshop Programme committee – The 4th International Workshop
on Health Informatics: Patient-Centred Solutions and Educational Approaches
in the Digital Health Era (IEEE HOPE'21) [part of the ACS/IEEE International
Conference on Computer Systems and Applications AICCSA 2021, Tangier,
Morocco, Nov 30 – Dec 03, 2021]

https://www.aiccsa.net/AICCSA2021/index.php/symposiums-and-workshop/2-uncategorised/72-hope21


Member of a workshop Programme committee – The International Workshop on
Health Informatics: Patient-Centred Solutions and Educational Approaches in
the Digital Health Era (HOPE’18) [part of the ACS/IEEE International
Conference on Computer Systems and Applications AICCSA 2018]
http://aiccsa.net/AICCSA2018/2-uncategorised/48-hope18
(Co-)chair sessions at various conferences, e.g. GISEH, IMA, EURO
- Hounslow
Primary Care Trust
Tadjer,
M., Chaussalet, T.J., Fouladinejad, F., Chahed, S. “Using data mining and
simulation for health system understanding and capacity planning: an
application to urgent care”, in: the 38th ORAHS conference, 15-20 July 2012,
Enschede, the Netherlands.
Tadjer, M., Chaussalet, T.J., Fouladinejad, F., Chahed, S., Saiyed, S. and
Redzanovic, S. “Towards a full implementation of collaborative care plan. OR
Informing National Health Policy”, in: Harper, P., Knight, V., Vieira, I.,
Williams, J. (eds.) Operational Research Information National Health Policy:
proceedings of the 37th ORAHS conference, 24-29 July 2011, Cardiff
University.
Demir, E., Chahed, S., Chaussalet, T., Toffa, S. and Fouladinajed, F.
(2010) “A Decision Support Tool for Health Service Re-design”, Journal of
Medical Systems, Volume 36, Number 2, 621-630.
Chaussalet, T., Demir, E., Chahed, S. and Fouladinejad, F. “A tool for
supporting health service redesign decisions”, in: the 36th ORAHS conference,
18 – 23 July 2010, University of Genova, Italy.
- - - - Research
was used to inform teaching of Level 5 module “Business Analytics”:
• Use of a simulation model developed as part of a KTP project to introduce
simulation modelling which is one of the 4 topics covered in this
module.
• Use of a real-life case study/problem for a coursework:
o Problem investigated during a postgraduate project for a coursework: The
objective was about improving the performance of a one-stop clinic dedicated
to GP referred chest pain patients. [Real problem but fictious data].
o Problem researched during a PhD project for a coursework: The main aim
was about evaluating the neonatal care demand and adjusting the capacity of
the neonatal care system accordingly. The students had to develop forecasting
models to evaluate future neonatal care demand. [Real problem. Publicly
available dataset was used instead of the originally used dataset for the PhD
thesis. This data was obtained from Public Health Scotland website
(https://www.isdscotland.org/health-topics/maternity-and-births/births/).]
Use of examples extracted from my research interests and projects to
explain certain analytical concepts and techniques, e.g. business analytics,
data visualisation and dashboarding, service operations management.
My research has also influenced the (re-)design of the BSc course I am
leading, namely BSc Data Science and Analytics, e.g. programme structure and
topics covered.
DCDI CSE Predictive
Risk Modelling for Integrated Care
Salma
Chahed
chaheds@westminster.ac.uk - Docobo Chaussalet,
T.J., Mesgarpour, M., Worrall, P. and Chahed, S. (2017). Emergency
Readmission for Integrated Care (ERIC) Model: Using an Automated Feature
Generation & a Multi-Task Learner. In: Operational Research Applied to
Health Services 2017, 24 to end of 28 Jul 2017, Bath, UK.
Mesgarpour, M., Chaussalet, T.J., Worrall, P. and Chahed, S. 2016.
Predictive Risk Modelling for Integrated Care: a Structured Review. IEEE 29th
International Symposium on Computer-Based Medical Systems. Dublin and Belfast
20 to end of 23 Jun 2016 IEEE.
[External] Docobo – SBRI (Small
Business Research initiative) Healthcare – SBRI-COLAB-5731 (NHS England) ~
£156,000 – November 2015 – Jan 2019 - Predictive Risk Modelling for
Integrated Care – PI: Thierry Chaussalet; Co-I: Philip Worrall and Salma
Chahed
- One
PhD student, Nodira Nazyrova, started in October 2021 (QHT Studentship). APR2
approved. Supervisory team:
• Director of study: Salma Chahed
• Co-supervisors: Thierry Chaussalet and Miriam Dwek.
• External collaboration for third part of PhD project: Dr Marc Farr, East
Kent Hospitals University NHS Foundation Trust
• Project topic: Identifying risk factors and predicting hospital
readmission in older adults receiving home care services within 30 days of
discharge.
- -
DCDI CSE Impact
of temperature disparity on emergency readmissions
Salma
Chahed
chaheds@westminster.ac.uk Policy
Studies Institute (PSI) at UoW
- Islam,
M.S., Chaussalet, T.J., Ozkan, N., Chahed, S., Demir, E. and Sarran, C. “The
impact of temperature disparity on emergency readmissions and patient flows”,
in: Olive, M. and Solomonides, T., (eds.) Proceedings of CBMS: the 24th
International Symposium on Computer-Based Medical Systems, June 27th – 30th,
2011, Bristol, United Kingdom.
[External] Hounslow Primary Care
Trust – EPSRC (50%)/Innovate UK(50%): • Partnership objective: Development
and implementation of a Decision Support Software tool for service redesign
including scenario generator. Exploration and development of novel hybrid
data mining algorithms through process modelling and simulation •2 KTP
associates •Lead academics: Thierry Chaussalet and Panagiotis Chountas;
Knowledge Base team: Salma Chahed and Eren Demir •Grant amount: £160,968 +
PCT contribution •Duration: November 2009 – March 2013
- - - -
DCDI CSE Drug-Drug
interactions and hospital readmission
Salma
Chahed
chaheds@westminster.ac.uk Dr
Stephen Getting and Dr Miriam Dwek, School of Life science at UoW
- Nazyrova,
N., Chahed, S., Dwek, M., Getting, S.J. and Chaussalet, T.J. (2023).
Discovering Drug-Drug Interactions using Association Rule Mining from
Electronic Health Records. To be submitted to The 17th International
Conference on Innovations in Intelligent Systems and Applications (INISTA
2023) [https://conferences.sigappfr.org/inista2023/]
- - - - -
DCDI CSE Automated
Verification of Software Specifications
Algorithms for Proof Search and Model Checking
Algorithms for Realisability Problem and Synthesis
Algorithms for Problem-Solving Frameworks

Alex
Bolotov
A.Bolotov@wmin.ac.uk 2
International Projects (Collaboration with university of Liverpool,
University of Manchester, University of Basque Country, University of Poznan,
Moscow University, University of Lodz)
15+
journal publications, 30+ conference papers

Automated Model Checker for Certified Model Checking
Software Realisability Solver
- - - - -
DCDI CSE Digital
Health Evidence Generator: engaging students to develop its Computational
Ontology with embedded Digital Equality principles (UoW Employability
Project)
Development of Ontology Based Assessment techniques for Digital Health
Evidence Generation
Creating a novel transitional educational content (as synergy of
Mathematics, English and Generic Skills with the embedded
socio/economic/community engagement dimension) for young Uzbek generation
leaving high school and piloting it in Uzbek regions.
Alex
Bolotov
A.Bolotov@wmin.ac.uk Several
Invited talks/lectures (e.g. Stanford University), PC Chair, UK Automated
Reasoning Chair,
Graph-Based Knowledge and Learning Platform SMARTEST
(https://smartestknowledge.org/), SMARTEST was evaluated as one of the most
influential QHT projects
David
Chan (CPC), Emanuela Volpi (Life Sciences), Paulina Bondaronek (LAS)
15
partners including universities, industry, research institutes
SMARTEST
- Graph Based Knowledge and Learning Platform
https://smartestknowledge.org/
[External] Research UK Global
Challenges Funding, QR International Collaboration - 75K

[Internal] QHT
funding (50K), Employability scheme (15K), UoW-WIUT collaborative fund (20K),
Multiple Students as CO-creators Projects
Development-
of Digital Health Evidence Generation ontology and an automated assessment
system for digital health evidence generation
Development of the fully functional software realisabilty solver
Upgrade of the SMARTEST platform with Ontology Handling Engine and
implementation of relevant visualisation techniques
Integrating semantic components into the developed data mining system,
enabling AI to contextually interpret data, formalisation of the theoretical concepts using RDF or OWL
Ontology and development of the unified framework for data analysis,
specifically targeting financial data prediction. Development of the
comprehensive library of concepts for users and developers, facilitating
better collaboration in AI and data analysis projects within the finance
sector.
Development of CS Ontology to assist Final Year Projects
Natalia
Yerashenia (completed 2022)
Invited
lectures detailed above, workshops on using the SMARTEST platform for WIUT
pre-university courses, associated schools and colleges, Co-design workshop
with Digital Health Innovators
-
DCDI CSE Enhancing
Data Mining Systems via Ontological Semantic Methods
Alex
Bolotov
A.Bolotov@wmin.ac.uk David
Chan (CPC)
2
conference papers
- - - - -
DCDI CSE AI
and Machine Learning Technologies for IoT
Djuradj
Budimir
d.budimir@wmin.ac.uk Westminster
International University of Tashkent and Qualcomm Technologies, USA
Conference
paper
EPSRC
panel member, conference chair, IEEE TC member
Supervising
four relevant PhD projects.
My
teaching is mainly a research based
DCDI CSE 5G
IoT technologies
Djuradj
Budimir
d.budimir@wmin.ac.uk University
of Essex
Appx
£1.5 m, EPSRC grant, Awaiting ICT panel decision
EPSRC
panel member, conference chair, IEEE TC member
Supervising
four relevant PhD projects.
My
teaching is mainly a research based
DCDI CSE AI
for 6G technologies
Djuradj
Budimir
d.budimir@wmin.ac.uk University
of Birmingham,
University of Glasgow,
The University of Manchester
Surrey University
QMUL
NPL
Appx
£3.5m, EPSRC grant, In preparation
EPSRC
panel member, conference chair, IEEE TC member
Supervising
four relevant PhD projects.
My
teaching is mainly a research based
DCDI Architecture
and Cities
Use
of AI for sustainability and decarbonisation practices in logistics and
supply chains
Jacques
Leonardi
j.leonardi@westminster.ac.uk Research
of Amr Fawzy
Title: The Impact of Artificial Intelligence on
Sustainable Logistics Practices
DCDI Architecture
and Cities
VivaCity
AI traffic/active travel flows
Rachel
Aldred
r.aldred@westminster.ac.uk Active
Travel Fund: Local Authority Capital Funding - ‘Active Travel Fund
Evaluation’
DCDI Architecture
and Cities
Predictive
ML models for airline’s operations management
Andrew
Cook
cookaj@westminster.ac.uk
DCDI Architecture
and Cities
Data
analysis (e.g. clustering) for analysis and modelling of flight traffic and
trajectories.
Andrew
Cook
cookaj@westminster.ac.uk
DCDI Architecture
and Cities
Reinforced
learning for airline processes optimisation
Andrew
Cook
cookaj@westminster.ac.uk
DCDI Architecture
and Cities
Meta-modelling
and active learning for air transport modelling.
Andrew
Cook
cookaj@westminster.ac.uk
DCDI Architecture
and Cities
Multi-agent
based simulation including machine learning models to describe operational
processes
Andrew
Cook
cookaj@westminster.ac.uk
DCDI Media
and Communications
Deepfakes/synthetic
media
Graham
Meikle
G.Meikle@westminster.ac.uk
DCDI Media
and Communications
Critical
AI/data Studies, AI in media, Participatory AI/ML, AI for the Social Good,
news personalisation
Pieter
Verdegem
p.verdegem@westminster.ac.uk
DCDI Media
and Communications
Critical
AI/data studies, AI for the Social Good, Decolonizing AI
Andrea
Medrado
a.medrado@westminster.ac.uk
DCDI Media
and Communications
Deepfakes/synthetic
media
Sam
Gregory
Executive
Director of WITNESS (New York).
PhD
comprises a portfolio of reports and articles on deepfakes. Heavily involved
in interdisciplinary work in this area, including content authenticity
initiatives with partners including Adobe, BBC, Microsoft, New York Times,
and major public outreach/KE projects such as WITNESS/MIT YouTube series
Deepfakery.
DCDI Media
and Communications
Media/digital
policy, public service media, AI policy and regulation
Maria
Michalis
m.michalis@westminster.ac.uk
DCDI School
of Arts
The
Virtual Image
Prof
David Bate / Dr Paula Gortazar
Multiple
grants sought. Published research already across prestigious Journals and
events with Photographers Gallery
DCDI School
of Arts
Artificial
intelligence and the everyday: grassroots knowledge through co-creative
practice
Dr
Matthias Kispert
Post
Doctoral Researcher based in CREAM
DCDI School
of Arts
Site
Assembly; Virtual Assembly and Site Integrity
Dr
Julie Marsh
Ongoing
research with RIBA
DCDI School
of Arts
Immersion
and Creative Technology
Dr
Lucy Harrison / Dr Kirsten Hermes
DCDI School
of Arts
AI
& Ecological Systems Illustrations / Immersion
Dr
Shezad Dawood
Senior
Research Fellow. 0.2 with International Profile
Dawood
works with his own production company UBIK on multiple large scale Museum
commissions. Working with scientists and animators, his VR work has been
commissioned by Frieze, Sharjah Biennale and multiple venues.
Dawood
will be developing new Project with Design Observatory for 2024-5 and is one
of our planned Impact case studies.
LAS Law Synthetic
Voices: creation, legal status and ownership'.
Dr
Danilo Mandic
D.Mandic@westminster.ac.uk
LAS Law ADI and Data protection law Dr Diana Sancho D.Sancho1@westminster.ac.uk collaboration
with computer science
LAS Law Cryptocurrencies,
blockchain and legal regulation
Dr
Daniela Gandorfer
D.Gandorfer@westminster.ac.uk
LAS Life
Sciences
Computational
Genomics Sex and Ancestry Bias across global datasets Policies for EDI in
Precision Medicine Development of Markers for Longevity
Manuel
Corpas
2023
Enhanced consumables bid (£3.5k), University of Westminster to sequence
breast cancer patients from Uganda Biobank
2022 University of Westminster Internal School of Life Sciences PhD
studentship. My proposal was among the 3 accepted from 3 submissions for PhD
projects. (£42,330)
2022 Enhanced consumables bid (£6k), University of Westminster to access
tier 2 data from the UK Biobank.
2020 European Commission (EASI-Genomics): whole exome sequencing of 100
COVID-19 patients from the first wave of the infection, with the possibility
of further funds for whole genome sequencing of up to 300 samples. Estimated
value: euro 50K. Role co-PI, lead the genome analysis part.
2017 NIH Data Commons Pilot Phase: FAIR Data to Drive Cures (total grant
value; $800K). PI: Brandi Davis-Dusenbery
LAS Life
Sciences
Computational
genomics
in breast cancer with a focus on underrepresented groups and on
glycosylation pathways.
Miriam
Dwek
m.v.dwek@Westminster.ac.uk Manuel
Corpas
LAS Life
Sciences
Discovering
adverse drug-drug interactions from Electronic Health Records.
Miriam
Dwek
m.v.dwek@Westminster.ac.uk Steve
Getting, Salma Chahed and Thierry Chassaulet
LAS Life
Sciences
Deep-learning
analysis of MRI images using UK Biobank data
Profs
Jimmy Bell and
Louise Thomas
j.bell@westminster.ac.uk
L.thomas3@westminster.ac.uk
Evolution
of Enriched-Phenotypes for Health Exploration and Discovery funded by Calico
LLC £3,493.292 3 rounds of funding 2018-2020, 2020-2022
and 2022-2025
LAS Life
Sciences
Deep-learning
prediction of MRI based body composition from simple anthropometric
measurements
Profs
Jimmy Bell and
Louise Thomas
j.bell@westminster.ac.uk
L.thomas3@westminster.ac.uk
Prediction of visceral and liver
fat Muscle by Deep-Learning methodology funded by Antidote
Holdings LTDB £91,389 2021-2022
LAS Life
Sciences
AI-driven
sustainable food-waste solutions
Dr
Dipankar Sengupta
d.sengupta@westminster.ac.uk QHT (Quintin
Hogg Trust) funded project (£22,000; 2022-24). Also, this project is
vertically integrated with ‘Engaging Students in Research and Knowledge
Exchange’ project and has additional funding for ~40 student research
interns.
LAS Life
Sciences
Precision
Medicine: Algorithms for Patient Diagnostic and Prognostic (Longitudinal
Analysis) Applications
Dr
Dipankar Sengupta
d.sengupta@westminster.ac.uk 1.
Development of business intelligence model of personnel at higher altitude
for health care analysis and prediction [₹ 1,000,000; 2012-14] funded by
DIHAR, DRDO, India.
2. BridgeIRIS (http://bridgeiris.ibsquare.be) – Brussels big data platform
for the sharing and discovery in Clinical Genomics [€1,187,017; 2014-2016]
funded by Innoviris Brussels, Belgium.
3. IMAGica - Integrative personalised Medical Approach for Genetic diseases
[€300,000; 2016-21] funded by IRP, VUB, Belgium.
This is ongoing research (10+
years), focusing on developing AI algorithms
(Supervised/Unsupervised/Semi-supervised learning) exploring the large
heterogenous clinical and omics datasets (India, Belgium, and UK).
LAS Life
Sciences
AI
models for assessing DNA damage repair in cancer cells
Dr
Kalpana Surendranath
k.surendranath1@westminster.ac.uk
LAS Life
Sciences
AI
image analysis of immunohistochemical, immunofluorescent and in situ
hybridisation of tissue sections
Dr
Joan Liu
j.liu@westminster.ac.uk
LAS Life
Sciences
Analysis
and evaluation of human tissue biopsy and postmortem samples to assist in
classification
Joan
LAS Life
Sciences
Diagnosis
and treatment options for patients with Epilepsy and other neurological
diseases
Joan
LAS Social
Sciences
AI
in relation to ethics, biases, explainability, social impact, democratic
governance
Professor
Nitasha Kaul
Technology
and Diversity roundtable at the Difference Festival in February 2023 with
colleagues from life sciences/ mathematics/ computing to discuss this.
Kaul,
N. (2022) "3Es for AI: Economics, Explanation, Epistemology",
Frontiers in Artificial Intelligence, pp. 1-15.
https://doi.org/10.3389/frai.2022.833238
LAS Social
Sciences
Assessing
acceptability, Utilisation and Disclosure of Health Information
to an automated chatbot for advice about sexually Transmitted infections
in
minoritisED ethnic populations - AUDITED
Dr
Tom Nadarzynski
T.Nadarzynski@westminster.ac.uk NIHR
- AI_HI200028; £240,838.00; 10/2021 to 09/2023
LAS Social
Sciences
A
scoping review of studies on the public and health professionals’
perspectives and engagement with Artificial Intelligence (AI) services in
healthcare
Dr
Tom Nadarzynski
T.Nadarzynski@westminster.ac.uk Westminster
Diversity & Inclusion Fund, £4,345; 2020
LAS Social
Sciences
PAT
- a chatbot for information about sexual health;
Dr
Tom Nadarzynski
T.Nadarzynski@westminster.ac.uk Public
Health England; £46,190; 2019
LAS Social
Sciences
The
development of a Sexual HealthBot as an online triage system for digital
sexual health services in Hampshire, UK.
Dr
Tom Nadarzynski
T.Nadarzynski@westminster.ac.uk Solent
NHS Trust Research and Improvement Dragon’s Den Fund, £10,000; 2017
WBS Applied
Management
AI
in SME internationalisation
Sergio
De Cesare
s.decesare@westminster.ac.uk
WBS Applied
Management
Emotional
change of developers in adopting AI-powered technologies
Sergio
De Cesare
s.decesare@westminster.ac.uk
WBS Applied
Management
Emotional
change of developers in adopting AI-powered technologies
Farjam
Eshraghian
F.Eshraghian@westminster.ac.uk
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