Attendees

This page provides information about the programme, keynotes, venue, registration and accommodation recommendations:

Location, Facilities and Rooms:

The venue for the HCAI-ep 2023 conference is located in the TU Dublin, Tallaght Campus Sports Science Building.

Google Map to get the Sports Science Building: https://maps.app.goo.gl/EXkH4Kj1ThjkAb1SA

The location of the registration and the poster presentations is in the main foyer just inside the front door of this building. The conference room is TC003, which is just straight in from the front door, past the stairs on the right-hand side. This building has accessible WC, gender-neutral facilities and several free rooms for quiet rooms. In addition, there is a multi-faith prayer room in the main campus and please do not hesitate to ask any committee members how to get there. There will be amplification for the presenters (with an induction loop system) and HDMI inputs, as well as a desktop machine to download and access your slides and presentations, as well as USB access. We will have an HDMI cable but no adapters so please bring any adapters needed if you are presenting using your machine.

Programme:

The final programme is now released
A reminder that this is an in-person-only conference.

Please find web based program here or PDF below:

Programme Download

Keynote Speakers:

Georgiana Ifrim

Going The Distance: Reflections on Using Robot Racing Cars for Teaching Machine Learning

Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, UCD, co-lead of the SFI Centre for Research Training in Machine Learning (ML-Labs) and SFI Funded Investigator with the Insight Centre for Data Analytics and VistaMilk SFI Centre. Dr Ifrim holds a PhD and MSc in Machine Learning, from Max-Planck Institute for Informatics, Germany, and a BSc in Computer Science, from University of Bucharest, Romania. Her research focuses on effective approaches for large scale sequence learning, time series classification and text mining. She has published more than 50 peer-reviewed articles in top ranked international AI journals and conferences, regularly holds senior positions in the program committees for IJCAI, AAAI and ECML-PKDD and is a member of the editorial board of the Machine Learning Journal, Springer. More details are available at: https://people.ucd.ie/georgiana.ifrim.

Susan McKeever

Case studies in using AI for fixing real-world problems

Susan McKeever is a senior lecturer at TU Dublin School of Computer Science. She holds a Bachelor of Engineering (Telecommunications and Micro-Electronic) from Trinity College Dublin, an MSc in IT for Strategic Management (DIT). She received her PhD from UCD in 2011. Her main research areas are in the area of machine learning including deep learning, activity recognition, text mining, evidence theory and the general domain area of data analytics. Current projects include: Determining how to detect and automatically moderate and analyse content in social media – including abusive text and automated video analysis; Examining how best to detect and track the health and well being of elderly people at home, through the use of activity monitoring. She is also a collaborator in the CeADAR research group ( Centre for Applied Data Analytics). CeADAR work with industry to bring data analytics in to address real world business and future business problems. Prior to joining DIT, Susan worked in IT sector, including Accenture as an IT Consultant, and as a contract project manager.

Venue:

Registration Type	Registration fee in € (Euro)
Early-Bird Chapter/ACM Member	€180
Early-Bird Chapter/ACM Student Member	€90
Early-Bird Non – Chapter/ACM Member	€200
Early-Bird Non-Chapter/ACM Student Member	€110

Late/Onsite Chapter/ACM Member	€200
Late/Onsite Chapter/ACM Student Member	€100
Late/Onsite Non-Chapter/ACM Member	€220
Late/Onsite Non-Chapter/ACM Student Member	€120