PhD/MSc by Research Poster Event at UCD

It was a wonderful experience presenting a poster at the PhD/MSc by Research Poster Event organised by the UCD School of Computer Science.  We presented and shared our recent findings to get valuable feedback from other researchers. We are grateful for the effort put forth by the organising committee to make this event possible.

Having Pizza afterwards.


Yuhan’s PhD Viva

Huge congratulations to Yuhan who successfully passed her PhD Viva on 15 December 2022! And big congratulations to Catherine having her third PhD students finished!

Yuhan’s thesis title is “Explainable Clinical Decision Support for the Prediction of Complications in Pregnancy”.

Many thanks to her external examiner, Dr Dympna O Sullivan, TU Dublin, and internal examiner, Dr Soumyabrata Dev, and to Dr David Lillis for arranging and chairing the viva.

Many thanks to Yuhan’s co-supervisor, Prof Fionnuala McAuliffe, UCD School of Medicine and National Maternity Hospital, and to Yuhan’s RSP, Dr Mark Matthews and Dr Derek Greene, for their support and guidance over the last four years.


Lan attended the 2022 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB 2022), the conference of IEEE SPMB held virtually on December 3, 2022.

Lan presented a poster co-authored by Dr. Catherine titled “Investigating the Need for Pediatric-Specific Automatic Seizure Detection”. Approximately 1 in every 150 children is diagnosed with epilepsy during the first ten years of life. These children experience seizures, which disrupt their lives and directly harm the developing brain. Electroencephalography (EEG) is the main tool used clinically to diagnose seizures and epilepsy. However, the interpretation of EEGs requires time-consuming expert analysis. Automated detection systems are a powerful tool that can help address the issue by reducing expert annotation time.

Research on the automatic detection of seizures in pediatric EEG has been limited. Most seizure detection methods have been developed and tested using larger numbers of adult EEGs. However, research has shown that brain events in EEG change with ageing. Therefore, models trained on EEGs from adults may not be suitable for children. To test this hypothesis, we trained a seizure detection model on adult EEG and tested it on adult and pediatric EEG recordings. We find that a seizure detection model trained on adult EEGs is not suitable for children. Therefore, there is a need to develop a pediatric-specific method.

Happy Birthday Yuhan and Welcome Mercy to the LiSDA group

Today we celebrated Yuhan’s Birthday and met Mercy for the very first time. It was a nice day to celebrate.

On behalf of the team, we would like to wish you again a very “Happy Birthday”, Yuhan. You are the coolest member of our team. Thanks for being so helpful all the time.

Welcome to our unique, collaborative, dynamic and energetic team, Mercy.  You are a great addition to the team. Hope we will have fun together.


“Understanding Cancer” Workshop

The “Cancer Awareness Workshop in Bangladeshi Community”  was hosted by Precision Oncology Ireland as part of UCD Science week on 19th November. It was worth attending this workshop.  They highlighted the importance of the patient voice in Cancer Research.  They are aiming for inclusive Cancer Research, including minority groups.  As a member of a minority group, it will be a milestone for our community.

Best wishes to Dr. Anna for the future

Today is Dr. Anna Markella Antoniadi’s last day in UCD. Huge thanks to Anna for being a remarkable member of the LiSDA research group! We have been lucky to have you as a PhD student and a post-doctoral researcher for the past five years. You are highly appreciated for being a wonderful researcher, colleague and friend! LiSDA will remember you with fond memories, and we wish you the best of luck for your new career in industry!


The Role of XAI in Advice-Taking from a Clinical Decision Support System

Delighted that our paper titled “The Role of XAI in Advice-Taking from a Clinical Decision Support System: A Comparative User Study of Feature Contribution-Based and Example-Based Explanations” has been published on Applied Sciences.

This paper presents interesting findings from our user study with healthcare practitioners to investigate the role of XAI in a CDSS. It revealed what type of explanations healthcare practitioners need and would like to see, and how explanations affect their decision-making. Check it out at:

— Yuhan

Congratulations to Dr. Claudia and Mercy !!

Huge congratulations to Dr. Claudia Mazo for her well-deserved success. Best wishes for your new role as Assistant Professor at DCU.  You are an inspiration to us and we are proud of you.

Congratulations to Mercy for getting a School of Computer Science PhD Scholarship and starting her Ph.D.!!!  You are very welcome to our team — we are looking forward to working with you. 

Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles

Delighted our paper ‘Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles‘ has been published in Computers in Biology and Medicine.

The Deep-spindle webserver is also available online.

Sleep spindles are an indicator of the development and integrity of the central nervous system in infants. Identifying sleep spindles manually in EEG is time-consuming and typically requires experienced experts. Automated detection of sleep spindles would greatly facilitate this analysis. Deep learning methods have been widely used recently in EEG analysis. We have developed a deep learning-based automated sleep spindle detection system, Deep-spindle, which employs a convolutional neural network (CNN) combined with a bidirectional Long Short-Term Memory (LSTM) network, which could assist in the analysis of infant sleep spindles. The Deep-spindle system can reduce physicians’ workload, demonstrating the potential to assist physicians in the automated analysis of sleep spindles in infants.



We (Brett Becker and Catherine Mooney) are just back from the 21st European Conference on Computational Biology (ECCB), held in Sitges, Barcelona on 12-21 September 2022 (

We presented a poster “Investigating Student Sense of Belonging in Biology and Computer Science” co-authored by Shamima Nasrin Runa and Anna Markella Antoniadi.

Our results showed that 75% of the women in Computer Science and 29% of the women in Biology who completed the survey identified as a minority, but for different reasons (Computer Science; Biology): gender (61%; 29%), sexual identity (17%; 29%), race/nationality (44%; 33%), disability (6%;14%), and socio-economic status (11%; 10%). These results provide insight that may help improve the SoB of our undergraduate students and ensure that we create inclusive learning environments for all students.

UKICER Conference 2022.

My very first participation in UKICER-2022 conference.

I am delighted to present our poster in this conference. I couldn’t thank you enough for being my inspirational supervisor Dr. Catherine Mooney and co-supervisor Dr. Brett A. Becker.

Highly appreciate to be a member of the LiSDA group.



ITiCSE 2022

The 27th annual ACM conference on Innovation and Technology in Computer Science Education (ITiCSE) took place in UCD this year. LiSDA members were involved in the organising committee and conference volunteers who made this hybrid version of ITiCSE a huge success! The great talks of the conference were complemented by the extremely fun reception at the Technological University of Dublin (TU Dublin) , excursion at Powerscourt house/gardens, and banquet at Taylor’s Three Rock. A memorable experience!

IDEATE IRELAND 2022 Competition

Such an interesting and illuminating experience, taking part in the IDEATE IRELAND 2022 Competition! We are proud to have been among the 10 finalists- a group of brilliant entrepreneurs- and to finally win third place. Congratulations to the entire MetHealth team, and especially, to Dr Fiona McGillicuddy, the leader of the MetHealth project, for the amazing work and pitch!
-Dr Anna Markella Antoniadi

“Future You” Summer School 2022

The first “Future You” Summer School post-COVID-19 was concluded today. We really enjoyed the 3 days of workshops with these amazing problem-solvers and we all had a blast!
Anna Markella Antoniadi (LiSDA) and Ioannis Karvelas

The UCD Future You Summer School is an opportunity for school pupils to experience college life through interactive academic workshops and a variety of social and sports activities alongside other 5th year school pupils who aspire to study at university (more information here).

Women+ in STEM UCD outreach

The Women+ in STEM society in UCD invited post-doc Anna Antoniadi to give a talk about Computer Science in their final outreach session of the year with TY students. It was a great experience, and, according to the student’s feedback, they really enjoyed the programme, including the workshops but also the talks at the end! LiSDA members are frequently taking part in outreach activities to encourage girls to pursue a career in Computer Science or STEM in general and we are looking forward to the next opportunity!

International Women’s Day 2022

International Women’s Day, Tuesday 8th March 2022 is a global day celebrating the social, economic, cultural and political achievements of women – while also marking a call to action for accelerating gender equality.
In the field of Computer Science, people often have a stereotyped image of what a computer scientist looks like, the type of work they do and interests they have. We invite everyone to #BreakTheBias.

Theses Submitted!

Celebration day for LiSDA today as Anna Markella Antoniadi and Lan Wei submitted their PhD thesis copies to the Student Desk! Congratulations to both Dr Lan and Dr Anna for a huge achievement and best wishes for the future from the entire LiSDA group!

“Science Day in UCD”

Celebrating Science Day  in UCD 

Today there were some student societies who demonstrated their extraordinary scientific experimental discoveries and also showed some very interesting projects. While physics societies have shown their formula for making liquid ice cream using physics equations, the School of Earth Science societies have been presented with a few rare collections of stone, glass, and fossils. Women+ in STEM Society  put music in STEM. They showed off their banana piano tests there and they also added another test called Glow-in-the-Dark Jar. There were couple of societies who also have participated this demonstration table to successfully celebrate Science day in UCD.



You Can Be What You Can See: Role Models in pSTEM

We are proud to celebrate International Day of Women and Girls in Science in UCD today.

UCD is marking International Day of Women and Girls in Science by launching a series of videos to encourage more girls to consider a career in pSTEM. The video series, entitled “Role Models in pSTEM: You Can Be What You Can See”, showcases ten female role models from across Ireland who have studied physics, maths, engineering, or computer science. Three of the videos were revealed at an event in UCD today to mark International Day of Women and Girls in Science.

Commissioned by UCD’s School of Mathematics and Statistics, and School of Computer Science, the full suite of videos will launch in May 2022. The videos will be accompanied by an educational resource for teachers which can be used in schools across Ireland – with a particular focus on DEIS schools – to encourage students to identify their own local role models, while highlighting the varied and exciting career opportunities open to young women in pSTEM.

Leading the project are Dr. Aoibhinn Ní Shúilleabháin, Assistant Professor at the School of Mathematics and Statistics, and Dr. Catherine Mooney, Associate Professor in the School of Computer Science at University College Dublin.

We (Lan Wei, Yuhan Du, Shamima Nasrin Runa) are proud to volunteer and participate in the event to hear the inspiring talks by the female role models.

You can find the videos on our YouTube channel:
Our temporary webpage (to be updated for the full launch) is here:

XAI for Prediction of Gestational Diabetes

Our paper “An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus” is published in Scientific Reports today.

Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity. Interventions initiated early in pregnancy can reduce the rate of GDM in these women, however, untargeted interventions can be costly and time-consuming. We have developed an explainable machine learning-based clinical decision support system (CDSS) to identify at-risk women in need of targeted pregnancy intervention. Maternal characteristics and blood biomarkers at baseline from the PEARS study were used. After appropriate data preparation, synthetic minority oversampling technique and feature selection, five machine learning algorithms were applied with five-fold cross-validated grid search optimising the balanced accuracy. Our models were explained with Shapley additive explanations to increase the trustworthiness and acceptability of the system. We developed multiple models for different use cases: theoretical (AUC-PR 0.485, AUC-ROC 0.792), GDM screening during a normal antenatal visit (AUC-PR 0.208, AUC-ROC 0.659), and remote GDM risk assessment (AUC-PR 0.199, AUC-ROC 0.656). Our models have been implemented as a web server that is publicly available for academic use. Our explainable CDSS demonstrates the potential to assist clinicians in screening at risk patients who may benefit from early pregnancy GDM prevention strategies.

Check it out at:


The Irish Times featuring LiSDA

Anna Markella Antoniadi was interviewed for the “Research Lives” column in the Irish Times. She discussed her work on Amyotrophic Lateral Sclerosis and her life as a researcher; academic interests and hobbies, moving to Ireland, completing her PhD.

You can find her interview here.

Lan Wei’s PhD Viva

Congratulations to Lan Wei who successfully passed her PhD Viva this morning.

Lan’s thesis title is “Automatic Detection and Characterization of Seizures and Sleep Spindles in Electroencephalograms Using Machine Learning”.

Many thanks to her external examiner, Prof. Lijuan Duan, and internal examiner, Dr Ruihai Dong. Many thanks also to Assoc. Prof. Brian Mac Namee for arranging and chairing the Viva via zoom, and to Lan’s co-supervisor, Prof. Madeleine Lowery, for her support and guidance of Lan over the last four years.Many thanks to Lan’s  Research Studies Panel (Prof. Madeleine Lowery, Assoc. Prof. Gianluca Pollastri, and Dr Andrew Hines)  for their advice during the past four years.

Finally, a big thank you to our collaborators, Soraia Ventura, Dr Gareth Morris, Prof. David C. Henshall, Dr Sean Mathieson, Prof. Geraldine B., Mary Anne Ryan, Halima Boutouil, Boylan Rogerio Gerbatin, Dr Cristina R Reschke, Dr Omar Mamad and Dr Mona Heiland for their assistance, patience, attention and all the advice throughout Lan’s PhD.



Delighted our paper ‘Detection of spontaneous seizures in EEGs in multiple experimental mouse models of epilepsy‘ has been published in the Journal of Neural Engineering.

The Epi-AI webserver is also available online.

Epi-AI supports basic scientists to analyse EEG datasets by predicting if events are seizure events or not. Epi-AI supports single-channel EEG recordings in EDF, CSV, and PICKLE formats. If you upload an EEG in EDF format please choose which channel you want to analyse. If you upload a PICKLE or CSV file please choose which channel you want to analyse, the sampling frequency and the start time of your EEG recordings. Information about each detected seizure e.g. the number of seizures, start time, end time, duration, amplitude and corresponding spectrogram, will be available for download allowing for further analysis.



Delighted our paper ‘Spindle-AI: Sleep spindle number and duration estimation in infant EEG‘ has been published in IEEE Transactions on Biomedical Engineering.

The Spindle-AI webserver is also available online.

Spindle-AI allows the user to choose the sampling frequency of their data and submit a CSV file that contains a single-channel EEG signal. Spindle-AI will predict if the events are sleep spindle events or non-sleep spindle events. Spindle-AI then returns the start time, end time and the total number of the detected sleep spindle events.


LiSDA @ vGHC21

I (Yuhan Du) attended the Grace Hopper Celebration 2021 on Sep 27 – Oct 1 and presented my poster “Early Prediction of Macrosomia Using Machine Learning”, coauthored with Dr. Catherine Mooney. The poster described our research on predicting fetal macrosomia, which refers to infants born with excessive birth weight. In this study, we developed machine learning models to predict macrosomia in the early second trimester in secundigravid women who had a macrosomic birth history with a novel inclusion of usability. Our work has the potential to assist pregnancy care in a clinical setting.

You can find our poster at:

–Yuhan Du

Anna Markella Antoniadi’s PhD Viva

Congratulations to Anna Markella Antoniadi who successfully passed her PhD viva this afternoon.
Anna’s thesis title is “The Application of Explainable Artificial Intelligence in Modelling Quality of Life and Caregiver Burden in Amyotrophic Lateral Sclerosis to Inform Clinical Decision-Making”.
Many thanks to her examiners, Prof. Pierangelo Veltri, University of Catanzaro, and internal examiner Dr Mark Matthews. Many thanks also to Associate Prof. Gianluca Pollastri for arranging and chairing the viva via zoom, and to Anna’s Research Studies Panel (Prof. Pádraig Cunningham and Dr Marguerite Barry) for their support and guidance of Anna over the last four years. Finally, a big thank you to our collaborators, Prof. Orla Hardiman, Miriam Galvin and Mark Heverin in Trinity College Dublin for closely working with Anna throughout her PhD.


LiSDA @ ACM BCB 2021

I (Yuhan Du) attended the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) that was held online on Aug 1-4, 2021. I presented my poster entitled “Explaining Large-for-Gestational-Age Births: A Random Forest Classifier with a Novel Local Interpretation Method”, coauthored with Dr. Anthony R Rafferty, Prof. Fionnuala M McAuliffe and Dr. Catherine Mooney. In the poster, the authors proposed a novel local interpretation method for a random forest classifier based on feature occurrence frequency in trees that give the same prediction as the random forest classifier. The method shows promising results when applied to a random forest classifier for large-for-gestational-age births.

– Yuhan

What’s it like to be an MSCA fellow? Hear from Claudia Mazo

What’s it like to be a Marie-Sklodowska Curie Actions Fellow?

Check out these testimonials from our Postdoc Claudia Mazo

She would really recommend any early-career research to apply for this great opportunity. As she said: “This fellowship has allowed me to have the benefits of academia and industry together….. to broaden my current knowledge and develop technical, industrial, and research skills”. Having the opportunity to collaborate with different experts in her field from around the world also has made her much more competitive.



LiSDA @ ACM SAC 2021

Anna Markella Antoniadi attended the ACM SAC 2021 virtual conference and presented our work on the “Development of an Explainable Clinical Decision Support System for the Prediction of Patient Quality of Life in Amyotrophic Lateral Sclerosis” at the Health Informatics Track of the Conference. This work is a collaboration with Miriam Galvin, Mark Heverin and Orla Hardiman and it is a work towards the development of the first Clinical Decision Support System to automatically predict the Quality of Life (QoL) of people with Amyotrophic Lateral Sclerosis, easily and quickly, in order for clinicians to decide on the necessary supports. We found that the predictors of patient QoL are their age at disease onset, orthopnoea score, as well as their primary caregiver’s employment status before the disease onset. More details can be found in our paper in the proceedings.