Firms are increasingly investing in AI to support their operational decision-making processes. Via this workshop, we want to create a realistic picture of the opportunities and limitations of AI for decision support via real-time dashboards. A special focus will be given to control rooms as this sector is increasing in importance with the digitization of operations. The workshop covers three topics:
FORMAT Study day/workshop
TIMING October 7, 2022
LOCATION University Ghent, Faculty of Economics and Business Administration, Faculty board room/Faculteitsraadzaal
Industry: 250 €
Researchers: 80 €
Technical skill level: Basic knowledge of AI terminology is a prerequisite (you know what AI is), no mathematical/coding experience is required.
Job profiles: Digital managers, data scientists and researchers in the field of digital operations, and predictive analytics.
Industries: Safety-critical settings, utilities, transportation, control rooms.
Moderator: Bart Roets, Infrabel
8.30 Keynote, tbd
10.00 coffee break
12.00 lunch + (small) poster session
Evelina Gabasova, The Alan Turing Institute
14.30 coffee break
15.15 Debate: Making it real: Industry demand as a driver for further research
16.00 Closing workshop
Marijn Verschelde, IÉSEG School of Management
16.45 Networking Drink
door Leon Sobrie - On Track Lab
Digitisation and employee workload (im)balance are intertwined. To address undesirable workload peaks and lows, we propose a 2-step machine learning model to provide real-time workload analytics per controller in digital safety-critical control rooms. The advocated model leverages a rich real-time data structure with disaggregated event-level taskload data. Next to exploring different machine and deep learning approaches, we compare the performance of a model that predicts aggregate workload with the performance of the aggregate of different models that predict specific task loads. We develop a business application that utilizes the proposed model to provide detailed predictive analytics that open the black box of workload imbalance and, in this way, empowers the control room manager with real-time insights.
door Christophe Hurter - ENAC
The Decision Making Process is already associated with AI. The algorithms are meant to help ATCOs in daily tasks, but they still face acceptability issues. Today’s automation systems with AI/Machine Learning do not provide additional information on top of the Data Processing result to support its explanation, making them not transparent enough. The Decision Making Process is expected to become a “White Box”, giving understandable outcome through an understandable process. XAI SOLUTIONS: Transparency and Explainability: ARTIMATION’s goal is providing a transparent and explainable AI model through visualization, data driven storytelling and immersive analytics. This project will take advantage of human perceptual capabilities to better understand AI algorithm with appropriated data visualization as a support for explainable AI, exploring in the ATM field the use of immersive analytics to display information.
door Riccardo Patriarca - Sapienza Université di Roma & Antonio Licu - Eurocontrol
Modern systems are complex and understanding the nuances of everyday work requires to explore thoroughly system properties. EUROCONTROL recognized these needs when publishing its white papers on Resilience Engineering almost 15 years ago. The project called “Weak Signal” continued on that side. Besides the theoretical foundation on weak signals definition, detection and management, one of this project’s outputs is the development of a novel tool called SECA (Structured Exploration of Complex Adaptations). SECA helps detecting weak signals in normal air traffic management operations, creating shared organizational knowledge. This latter arises from a collaborative elicitation process that span from tacit and explicit dimensions. SECA is designed to support data gathering and data analysis, integrating traditional thematic analyses with modern Natural Language Processing. The presentation will show the early results of its adoption in two different European ANSPs and the way to scale it up from a prototype to a full-fledged solution, also including the possibility to use the same approach in other industries.
Dr Evelina Gabašová is a data scientist and machine learning researcher, working in The Alan Turing Institute, the UK’s national centre for data science and artificial intelligence. She writes about data science, machine learning and software development.
Christophe Hurter is a Professor working at the University of Toulouse, France, leading the Interactive Data Visualization group (DataVis) of the French Civil Aviation University (ENAC). His research covers explainable A.I. (XAI), big data manipulation and visualization (InfoVis), immersive analytics, and humancomputer interaction (HCI). He investigates the design of scalable visual interfaces and the development of pixel-based techniques. He is an associate researcher at the research center for the French Military Air Force Test Center (CReA, Base militaire de Salon de Provence) and at the Brain and Cognition Research Center (CerCo, Hospital University Center of Toulouse). He published 2 books, 4 book chapters, 20 patents, 25 journal papers, more than 100 per reviewed international research papers.
Tony is cumulating Head of Digital Transformation Office and Head of Operational Safety, SQS and Integrated Risk management Safety (NMD/SAF) Unit within Network Manager Directorate of EUROCONTROL (European Organisation for the Safety of Air Navigation).
He leads the deployment of safety management and human factors programmes of EUROCONTROL. He has extensive Air Traffic Control operational and engineering background (master degree in avionics).
Tony’s role as head of DTO (the organisational vehicle driving the Digital Transformation of Eurocontrol Network Manager) is to manage technology, innovation and Digital Transformation for iNM in close cooperation with EUROCONTROL organisational entities and the industrial partners
Riccardo Patriarca is a tenure track assistant professor at Sapienza University of Rome (Italy) – Dept. of Mechanical and Aerospace Engineering. He holds an BSc in Aerospace Engineering, an MSc in Aeronautical Engineering and a PhD in Industrial and Management Engineering (Doctor Europaeus). He has published widely (about 100 manuscripts published in academic journals and conference proceedings) on methodological and epistemological aspects of risk, safety, and resilience management as well as operations management in general. He aims to make systems safer and resilient when - and especially before - things go awry.
will be completed soon
will be completed soon
will be completed soon