Best Technical Advance in the field of Data Science/AI from a Research Organisation

Entry Criteria

Entries for this award must be either self-nominated or in the case of entries from academia, either self-nominated or nominated by the academic supervisor. The nominee can be an individual or team of people working together on the solution. Entries should clearly explain the technical advance in the research field of Data Science/AI by the nominee.

Entries must have been undertaken in either an industrial research organisation or an academic research organisation or a collaboration involving both. The research work must have been undertaken within the past 36 months.


Scoring (out of 100 points):

Nominees will be scored on a number of different criteria, receiving a score out of 100:


Clearly explain the research challenge, the context, and the work of others in the particular field of Data Science/AI. Explain how the project came about and how funding was secured to undertake it. [10 Points]


Explain the nature of the technical advance you have achieved and how it has moved the understanding of the field forward. Explain the complexities and challenges in developing the advance and how you overcame them. [15 Points]

Describe the Data Science/AI skills, tools and techniques that were applied in order to deliver this advance. [15 Points]


Outline the novelty in your solution. What differentiates it from other approaches that have been applied to the same problem? [20 Points]


If the research has been patented and/or published what has been the reaction of the research community? Clearly, describe how your advance might find application outside the research lab [30 Points]


Describe your vision for your taking the advance forward. [10 points]


DR. Mick Kerrigan

Chief Science Officer | RecommenderX DAC

Peter Elger
Peter Elger

CEO | fourTheorem

Sinead Flahive
Sinead Flahive

Senior Data Scientist | World Programming

Murhaf Hossari

AI Architect | ADAPT Centre, Trinity College Dublin