PhD Position: Explainable AI for Crowd Risk Management

A major challenge in crises is the combination of complexity, time pressure and moral decisions. AI has the potential to support crowd crises decisions, yet the increasing use of AI has led to a debate about the legal and ethical implications.
In this PhD project, our primary focus is to harness the capabilities of Explainable Artificial Intelligence (XAI) to better understand and manage crowd dynamics by integrating diverse data sets that include contextual information such as weather conditions, social media sentiment, and specific event characteristics. The objective is to develop predictive models that not only forecast crowd behaviors under various scenarios but also explain the underlying reasons for such predictions to facilitate transparent decision-making. This involves creating advanced AI algorithms capable of handling real-time data, ensuring data accuracy, and overcoming the challenges posed by the dynamic and often unpredictable nature of crowd movements. By improving the interpretability of AI outputs, stakeholders—from event organizers to city planners and emergency response teams—can make more informed decisions, enhancing safety and efficiency during large-scale public events.
The research will proceed through several progressive phases, each building upon the insights and technologies developed in the preceding one. Initially, we will focus on the development and validation of predictive and forecasting models for crowd management, utilizing regression trees, ensemble models, and techniques like XGBoost for feature selection and interpretability. Subsequent phases will involve the integration and categorization of risks using XAI to assess and predict potential incident scenarios and their impacts. This multi-disciplinary approach will extend into crowdsourcing and gamification strategies to collect diverse data, which will be used to continuously train and refine our models. The ultimate goal is to develop a robust, scalable system that not only predicts and categorizes risks but also provides actionable, data-driven advice on crowd management interventions. These interventions will be optimized through continuous learning frameworks and evolutionary algorithms, ensuring that the system evolves in response to new data and changing environments.
The position is a part of the AI-COMPASS team of three PhD researchers that will collectively research crowd crisis management at the TU Delft. This position is embedded at the Faculty of Civil Engineering and Geosciences (CEG) and will be jointly supervised with the faculty of Technology, Policy and Management (TPM). As such, the candidate will be joining a vibrant and growing community. You will be supervised by Prof. Serge Hoogendoorn and Prof. Tina Comes, and you will closely collaborate with Dr. Sascha Hoogendoorn-Lanser. This embedding ensures access to a broad network of partners in research, policy and practice. You may also gain experience in supervising MSc students and engage in teaching and training. Via our network and tailored mentoring, we will create opportunities for you to develop your career through support for conferences, collaborations and training possibilities.

Requirements:

You are a highly motivated and enthusiastic researcher with the ambition to conduct high-quality interdisciplinary research that pushes the boundaries of human-centred AI research in crises. Specifically:

• You have a Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• You have strong programming skills and experience with machine learning tools and techniques.
• You have excellent analytical and problem-solving abilities
• You have excellent study results and excellent command of English. Dutch language skills are a plus.
• You are keen to collaborate with various project partners and to translate your insights into practice and policy.
• You thrive in a collaborative and multi-disciplinary environment (essential). 

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Salary Benefits:

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged. 
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

36 - 40 hours per week

Mekelweg 2