Winning Team


TAPAS: Enabling developing countries to track climate change adaptation in their agri-food sectors 

NUI Galway 



Special Prize


AI_PREMie: Reducing the Burden of Preeclampsia 

University College Dublin



Seed Phase Teams

*Teams co-funded by DFA


AI for Fetal Wellbeing

Reducing Neonatal Morbidity and Mortality

Challenge Intrapartum fetal monitoring is used to identify oxygen deprivation to the fetal brain during labour and delivery, to reduce the risk of neonatal morbidity and mortality. However, the current “gold-standard” approach to fetal monitoring is not accurate, is susceptible to misinterpretation and is unreliable.  

Solution The AI-4-Life team will develop a novel AI-based system to monitor the vital signs of mother and baby during labour to quickly identify any issues. 

UN SDG Alignment GOAL 3: Good Health and Well-being

Team Liam Marnane (UCC), Geraldine Boylan (UCC), Mairead O'Riordan (Cork University Maternity Hospital)


The first Digital Biomarker in Female Reproductive Health – uncloaking Endometriosis and filling the Diagnostic Gap

Reducing the impact of endometriosis through timely diagnosis

Challenge Endometriosis affects 1 in 10 women and can lead to significant health issues. Despite this, diagnosis can take up to 7 years.  Timely diagnosis has the power to transform women’s lives, enabling appropriate treatment to stop the progression of the disease and preserve fertility. 

Solution The Cailín team will develop a non-invasive digital biomarker for endometriosis by measuring disease-specific symptoms and applying advanced machine learning techniques. This disruptive AI-enabled technology will end the diagnostic delay. 

UN SDG Alignment GOAL 5: Gender Equality

Team Siobhan Kelleher (NUIG), John Breslin (NUIG), Kathleen King (Endometriosis Association of Ireland)

GreenWatch *

AI for Anti-greenwashing

Co-funded by Department of Foreign Affairs and Trade

Developing AI-based methods to detect greenwashing (to improve the measurement of progress towards the United Nations Sustainable Development Goals (SDGs))

Challenge Developing AI-based methods to detect greenwashing to improve the measurement of progress towards the United Nations Sustainable Development Goals (SDGs). 

Solution To tackle the issue of greenwashing and to enable stakeholders to identify and take action against it, new detection and measurement techniques must be developed. The GreenWatch team proposes to build a machine learning / natural language processing system to sift through large quantities of SDG related disclosures to identify instances of greenwashing. 

UN SDG Alignment GOAL 9: Industry, Innovation and Infrastructure

Team Andreas Hoepner (UCD), Georgiana Ifrim (UCD), Pat Cox (Sustainable Nation Ireland)


A Disruptive Non-Surgical Treatment for Lung Cancer

Surgery free AI-driven endoscopic ablation therapy for lung cancer

Challenge Lung cancer kills more citizens than breast, colon and prostate cancer combined, with over 9.6 million new cases diagnosed annually worldwide. Lung cancer is currently treated via invasive open surgery. We propose to improve the treatment of this disease. 

Solution The SmartAblate team will develop an AI-driven endoscopic ablation therapy for localised lung cancer treatment. This disruptive approach will negate the need for open-surgery and will provide for safer and more effective treatment for patients suffering with lung cancer. 

UN SDG Alignment GOAL 3: Good Health and Well-being

Team Martin O'Halloran (NUIG), Aoife Lowery (NUIG), Anne-Marie Baird  (TCD)

Concept Phase Teams

Empower and promote the social, economic and political inclusion of people with full or partial limb loss

Challenge Patients with full or partial limb loss can experience reduced social and economic inclusion when constrained to using prosthetic devices with sub-optimal functionality. We propose to advance the delivery of ‘right first time’ prostheses that can be upgraded regularly at low cost to meet a patient’s unique needs as they change over time. 

Solution The 3D3P team proposes to develop a low-cost 3D printed, high strength carbon-fibre prosthetic device for patients with lower limb amputations. The team proposes to leverage machine learning and data from prostheses as they are being used to dramatically reduce the cost and effort required to produce prosthetics customised for an individual’s needs. 

UN SDG Alignment GOAL 10: Reduced Inequality

Team Padraig Cunningham (UCD), Andrew Dickson (UCD), Breda Clancy (Atlantic Prosthetic Orthotic Services Ltd) 

Supporting social justice and equality by eliminating bias in AI

Challenge As AI-based systems make more decisions for us, there is an important need to ensure that these systems do not reproduce and exacerbate existing social biases and forms of discrimination. 

Solution The Fair AI team proposes to develop a platform that will evaluate and identify evidence of bias in relation to gender, race and political ideology in AI training sets. There are growing calls from both governmental institutions and industry for solutions to mitigate algorithmic bias. The Fair AI team will develop a scalable system that could be employed across a range of applications to evaluate training data for evidence of bias, thus working towards the goal of fairness in AI. 

UN SDG Alignment GOAL 10: Reduced Inequality

Team Eugenia Siapera (UCD), Susan Leavy (UCD), Mary Hearne (LinkedIn)

Reducing the burden of diabetes through earlier diagnosis 

Challenge Diabetes is a global pandemic requiring urgent attention. It currently affects approximately 1 in 10 people and causes significant disease of the eyes, kidneys, nerves and cardiovascular system if undiagnosed and untreated. Early detection of diabetes is crucial so that treatment can be initiated earlier to improve human health. 

Solution The Digital Diabetes team proposes to develop a novel digital biomarker for diabetes diagnosis. This innovative approach will use state of the art big data and artificial intelligence techniques to diagnose diabetes significantly earlier than current methods. 

UN SDG Alignment GOAL 3: Good Health and Well-being

Team Derek O'Keeffe (NUIG), Andrew Simpkin (NUIG), Fidelma Dunne (NUIG)

Enabling remote sports injury assessment

Challenge Injuries associated with contact sports, such as rugby, create a significant societal burden and can act as a barrier to participation and can prevent the full benefits of getting involved in these sports from being realised. To increase the safety of these sports, rapid assessment of collisions is needed to guide injury prevention strategies. 

Solution The VideoForce team proposes to develop an AI-based approach that can be applied to sports video footage to assess collisions. In this way coaches and players will gain quantitative information to guide injury prevention strategies.

UN SDG Alignment GOAL 3: Good Health and Well-being

Team Ciaran Simms (TCD), Aljosa Smolic (TCD), Garreth Farrell (Leinster Rugby)

Palliative care that meets the needs of an aging society

Challenge Currently, specialist palliative care services in the community operate by delivering a “one size fits all”, but as the needs of patients change, this model is no longer fit for purpose. New palliative care models are needed to ensure that patients can live longer while meeting their evolving health and wellbeing needs. 

Solution The pCCare team will develop a transformative and innovative approach to the allocation of specialist palliative care in the community supporting the needs of patients, families, and healthcare workers. 

UN SDG Alignment GOAL 3: Good Health and Well-being

Team Ciara Heavin (UCC), Armagan Tarim (UCC), Fiona Kiely (Marymount Hospice Cork)

Supporting independent living for people with epilepsy 

Challenge Due to privacy concerns, video-based smart-home monitoring and auto-logging systems cannot always be applied despite being the most accurate. There is a need to develop new high-performance approaches that preserve privacy for a range of applications that support independent living.

Solution The WirelessTouch team proposes to use 3D-wireless sensor technology to enable real-time measurement with a higher degree of privacy than conventional video-based monitoring. 

UN SDG Alignment GOAL 3: Good Health and Well-being

Team Lina Xu (UCD), Quan Le (UCD), Edel Curran (Epilepsy Ireland) 


Reduce electronic waste generation by empowering people to repair, reuse and refurbish electrical and electronic equipment

Challenge The societal impact of citizen-driven initiatives aimed at enabling the repair and reuse of electrical and electronic products is currently limited by a lack of access to relevant information and spare components.  

Solution The REEP team proposes to empower people to repair, reuse and refurbish electrical and electronic equipment by building an online marketplace that uses AI to meet the needs of reuse facilities, repair communities and citizens.  

UN SDG Alignment GOAL 12: Responsible Consumption and Production

Team Mathieu d'Aquin (NUIG), Umair Ul Hassan (NUIG), Vincent Carragher (Galway Waste Coop)