Photo of Aya Rizk

Aya Rizk

Associate Professor

I am passionate about data, as well as the challenges and opportunities they bring to businesses and societies. My research focuses on how digital innovations, especially data-driven ones, emerge and develop within organizations.

Digitalization and datafiction of organizations

My research interests span two main areas within the discipline of information systems: digital innovation and artificial intelligence (AI).

I am particularly interested in interdisciplinary research where one or both areas are leveraged to help organizations. For example, AI offers knowledge about methods and techniques to generate insights from machine-readable data, while digital innovation researchers and practitioners – and their surrounding socio-technical structures – are increasingly looking at new ways of finding and assimilating new knowledge sources to inform their ideas and develop new services.

With the increasing availability of such data, data-driven innovation is one of my key research interests. In my research projects, I focus on understanding data-driven innovation (DDI) as a phenomenon. This was initially done through looking at the areas of data science, AI and digital innovation separately to understand potential research problems and gaps.

My empirical work focused on digital services developed in smart cities, in which data and analytics played a key role in delivering value to their intended user. Through iterative analysis between the empirical data and digital service innovation theories, innovation networks was used as a theoretical frame to analyze the social and cognitive interactions between innovators, end users – as data generators, and other types of actors. In addition to being prominent network participants, end users’ role in digital service innovation is also of particular interest to me as a researcher.

Hence, I am interested in understanding the adoption barriers pertaining to the diffusion of DDIs. The whole process from discovery to post-diffusion (e.g. termination or scaling) is explored in my research, as well as how the knowledge development in that field is shaped by exploring the dualism of innovation: as a process and as an outcome. This work points to two further specialized areas of interest.

First, innovation being a complex endeavor, the range of skills, capabilities and strategies that take an idea into market are of key interest. More specifically, I am interested to understand how thought patterns such as design thinking and data thinking relate to each other in realizing potential AI benefits.

Second, in socio-technical structures such as innovation networks where both machines and humans learn and have some agency, decision-making seems to take new forms and to utilize different combinations of resources.

Thus, one of my key interests is in understanding how data-driven decision making (D3M) and DDI relate to and shape one another. In addition to studying data as an element of phenomena I study, I use it as an indispensable tool in informing my research results and turn to data science techniques in my analyses. Techniques such as clustering, association rules and topic modeling are examples of those in my toolbox towards theory development and validation.

CV

Positions

  • 2022-present Associate professor, Linköping University
  • 2021-2022 Postdoctoral Researcher, Luleå University of Technology
  • 2015-2020 PhD Student, Luleå University of Technology
  • 2013-2015 Senior Business Analyst, Zoser AG
  • 2010-2013 Advanced Analytics Consultant, Teradata
  • 2009-2010 Teaching Assistant, German University in Cairo

Degrees

Doctor of Philosophy (PhD), Information Systems (2020)
Title: Data-driven Innovation: An Exploration of Outcomes and Processes within Federated Networks
Department of Computer Science, Electrical and Space Engineering
Luleå University of Technology

Master of Sciences (M.Sc.), Business Informatics – (2012)
Title: Trajectory data analysis in support of understanding movement patterns: A data mining approach
Faculty of Management Technology
German University in Cairo

Other positions

2018-Present Board member and innovation advisor, Riteband AB

Research projects

2020-2022: Data-driven decision making (D3M) in operations and maintenance
Project financed under the Applied AI in Digital Innovation Hub North program with the aim of developing a data-driven decision making framework that maps and improves collaborative decision making between AI-recommended decisions and human-based domain specific decisions.
Financier: European regional development fund & the Swedish agency for economic and regional growth (Tillväxtverket)

2019-2021: Swedish Space Data Lab
Project financed under the Data Labs and Data Factories framework, aimed at establishing a national resource for the use of satellite data to drive innovation in earth-bound application areas.
Financier: Swedish innovation agency (Vinnova)

2017-2019: U4IoT

An H2020 Coordination and Support Action to support large-scale pilots of Internet of Things (IoT) implementations in five vertical sectors.
Financier: Horizon2020 – Grant Agreement 732078

2015-2018: OrganiCity
Co-creating smart cities of the future through Experimentation-as-a-Service (EaaS), utilizing Internet of Things (IoT) and open data technologies. Testbeds: London, Århus and Santander.
Financier: Horizon2020 – Grant Agreement number 645198

Publications

Teaching

Bachelor's programme in Information Systems Analysis

1. 726G83 – Information systems development
2. 725G88 – Qualitative methods in theory and practice
3. Bachelor thesis supervision

Master programme in IT och management:

1. 725A48 – Introduction to IT and management
2. 725A44 – Qualitative research in IT and management
3. 725A37 – Diagnosis and design of business and IT
4. Master thesis supervision

Coworkers

Organisation

News