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Digital Tech Summit 2024 – AI Transforming Business

digital tech summit 2024

AI Transforming business

Digital Tech Summit is the largest deep tech conference in the Nordic countries and the annual meeting place for researchers from the country's universities, their partners in Danish industry, startups and students from all danish universities.

Artificial intelligence (AI) has already transformed large parts of our industry and society. More than one out of four Danish companies are already using AI in production and process management, IT security, logistics, HR, sales, and marketing.

Danish universities and research institutions are at the forefront in applying AI in the pursuit of developing future production technologies and researching how technology can help solve some of society’s biggest challenges at the highest international level. The areas of application are almost unlimited, and development is rapid.

The conference is split into six central themes with AI as the overall themes:

  • Smart Energy
  • Digital Health
  • Smart Production
  • AI Boosters
  • Digital Defence
  • AI Ethics

None of this has any future without a strong group of talents. With the universities as the driving force, we will have as many students as possible at the conference.

There will be activities such as career advice and guidance and the possibility to be matched with corporations for both jobs, internships, or project-related collaborations.

Finally, the expo has a startup area where early stage startups will present upcoming technologies.  


Danish Digitalization, Data Science and AI – D3A 2.0


Danish Digitalization, Data Science and AI – D3A 2.0

We are bringing together researchers, students, and professionals from a wide range of fields to share the latest research and insights, gain new knowledge, exchange ideas, and make valuable connections across geography, scientific domains, and sub-fields. 

D3A – Danish Digitalization, Data Science and AI 2.0 will bring together researchers, students, and professionals from a wide range of fields to share the latest research and insights, gain new knowledge, exchange ideas, and make valuable connections across geography, scientific domains, and sub-fields. 

D3A is a national conference hosted by Pioneer Centre for AI (P1), Danish Data Science Academy (DDSA) and DIREC. 

It is a scientific conference where the newest research and insights will be discussed. The aim is to grow the Danish digitalization, data science, and AI communities and strengthen the network for PhD students, postdocs, senior researchers, and professionals. We want to foster a collaborative and inclusive environment across Denmark. 


Aarhus Summer School on Learning Theory

Summer School

Aarhus Summer School on Learning Theory

The Aarhus Summer School on Learning Theory brings together top international PhD students to educate them on fundamental topics in theory of machine learning. The summer school takes place in beautiful Aarhus, Denmark.

Aarhus is often mentioned as one of the happiest cities in the world and a hidden gem for travelers. This makes for a relaxing and inspiring environment for excursions, discussions, and collaborations.


Shai Ben-David
Shai Ben-David grew up in Jerusalem, Israel. He attended the Hebrew University studying physics, mathematics and psychology. He received his PhD under the supervision of Saharon Shelah and Menachem Magidor for a thesis in set theory. Professor Ben-David was a postdoctoral fellow at the University of Toronto in the Mathematics and the Computer Science departments, and in 1987 joined the faculty of the CS Department at the Technion (Israel Institute of Technology). He held visiting faculty positions at the Australian National University in Canberra (1997-1998) and at Cornell University (2001-2004). In August 2004 he joined the School of Computer Science at the University of Waterloo.

Amin Karbasi
Amin Karbasi is currently an associate professor of Electrical Engineering, Computer Science, and Statistics & Data Science at Yale University. He is also a research staff scientist at Google NY. He has been the recipient of the National Science Foundation (NSF) Career Award, Office of Naval Research (ONR) Young Investigator Award, Air Force Office of Scientific Research (AFOSR) Young Investigator Award, DARPA Young Faculty Award, National Academy of Engineering Grainger Award, Bell Lab Prize, Amazon Research Award, Google Faculty Research Award, Microsoft Azure Research Award, Simons Research Fellowship, and ETH Research Fellowship. 

His work has also been recognized with a number of paper awards, including Medical Image Computing and Computer Assisted Interventions Conference (MICCAI) 2017, Facebook MAIN Award from Montreal Artificial Intelligence and Neuroscience Conference 2018, International Conference on Artificial Intelligence and Statistics (AISTAT) 2015, IEEE ComSoc Data Storage 2013, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2011, ACM SIGMETRICS 2010, and IEEE International Symposium on Information Theory (ISIT) 2010 (runner-up). His Ph.D. thesis received the Patrick Denantes Memorial Prize 2013 from the School of Computer and Communication Sciences at EPFL, Switzerland.

Amir Yehudayoff
Amir received his Ph.D. from the Weizmann Institute of Science and was a two-year member at the Institute for Advanced Study in Princeton. He is currently a professor in the Department of Computer Science in the University of Copenhagen, and in the Department of Mathematics at the Technion. His main research area is theoretical computer science, with a recent focus on the theory of machine learning.

Nikita Zhivotovskiy
Nikita Zhivotovskiy is an Assistant Professor in the Department of Statistics at the University of California Berkeley. He previously held postdoctoral positions at ETH Zürich in the department of mathematics hosted by Afonso Bandeira, and at Google Research, Zürich hosted by Olivier Bousquet. He also spent time at the Technion I.I.T. mathematics department hosted by Shahar Mendelson. Nikita completed his thesis at Moscow Institute of Physics and Technology under the guidance of Vladimir Spokoiny and Konstantin Vorontsov.

More about the summer school


Summer course: CyberSafe – Mastering the Art of Cybersecurity

Summer course:

CYbersafe: Mastering the art of cybersecurity

Participate in a course with students from other Danish universities and international students as an elective on your study programme. The course will be an immersive course designed to cater to students interested in cybersecurity.

The course will cover the basics of cyber-security including the cyber threat landscape, network security, information security, cyber-security applications in IoT and robotics, cryptography, security awareness and best practices, incident response and digital forensics, and legal and ethical aspects of cybersecurity.  The course will include practical labs and hands-on exercises to allow participants to apply their knowledge and skills in a safe and controlled environment.

The practical experiences will help attendees to deepen their understanding of cybersecurity concepts. The course will be taught by cybersecurity experts from both academia and industry, to provide the participants with basic knowledge and advanced concepts coupled with practical insights from real-world experiences.

The course is aimed at university students studying computer science, information technology, cybersecurity, or related fields, Early Career Professionals, IT and Security Professionals. Those looking to specialize in cybersecurity and gain hands-on experience in the field.

Housing costs

To cover housing costs, 16 grants are offered to students from Danish universities supported by DIREC.

Apply here before May 1 to be considered for one of the grants


PhD School: Confronting Data through Design Methods – Speculating with Generative AI

phd school:

Confronting data through design methods

– Speculating with generative AI (GAI)

This course is aimed at PhD students, researching within the fields of Computer-Supported Cooperative Work (CSCW), Human-Computer Interaction (HCI), Science- and Technology Studies (STS), Participatory Design (PD) & Critical Data Studies, but the course is open to PhD students from all areas of work- and design studies. The course is given as a mix of hands-on exercises with GenAI tools and lectures and seminars on speculative design and critical responses to GenAI interwoven throughout the 3-day course. In addition, the students engage in peer-feedback as part of the development of their essays, which focus on applying GenAI in relation to their own PhD project.

The course explores how we can use design methods to probe, construct, question, and critique different types of data. The goal of the course is that participants are introduced to both theoretical, concrete, and practical knowledge about different modes of doing research through design as well as gaining an overview of current debates regarding how data-driven technologies can be made ethical and responsible.

This year’s course focus on applying GenAI for data analysis within this area of research.

The rapid introduction of GAI into organizational work through formal digital transformation initiatives as well as informal adoption of freely available tools is quickly reconfiguring the conditions of collaborative organizing and the means through which we speculate futures labor and society. How do we approach, for example, which practices and skills we automate or retain as requiring human experience? What futures are rendered more realizable through AI-enhanced data analysis methods and techniques? How is this moment of GAI hype and increased accessibility impacting forms of expertise, authority, and accountability in data work?

While GAI is entering data work for its expediency and utility, it is not always held accountable as a method of speculation and design even as it shapes the methods and tools through which we develop future scenarios with and through data analysis. Adopting a design perspective, we will also attend to the people in each case who are the subjects of data and have a stake in design outcomes of working with large-scale data, accessible for them with GAI.

Participants will obtain concrete skills in designing participatory “scenario-based workshops” utilizing GenAI tools, including DALL-E and ChatGPT. Furthermore, the course is set up to facilitate discussions and to generate ideas relating to the participants own PhD projects.

Working hands-on with GAI in a speculative design and research through design approach, will enable participants to enter into debates over responsible use of AI and other data-driven technologies through concrete application of these tools. By applying speculative methods to consider future scenarios of organizing and collaborative work students will problematize and concretize opportunities for designing/using data-driven technologies ethically and responsibly in their own cases.

The course is offered as a collaboration between DIREC, ITU and UCPH.  


If any participants have any special needs in order to attend the course, they are kindly requested to contact the organizers and we will try to accommodate such needs.


In order to prepare for the course, the course participants need to:


Read the literature from the reading list prior to the course (the course curriculum will be distributed after enrollment in the course). Download free version of DALL-E and ChatGPT.

Submit their essays before May 15 2024 (2-4 pages) reflecting on the question: “How might combining methods from speculative design and GenAI help you think about your data in new ways? 

The readings and the essays are a way to reflect upon the topics prior to the course. The essays will also help us to identify participants interests/considerations prior to the course. Furthermore, this preparatory work aims to support their active participation throughout the course.

Read more


Young Researcher Entrepreneurship Bootcamp

phd course

Young Researcher entrepreneurship bootcamp

Join the Young Researcher Entrepreneurship Bootcamp (YREB) PhD-course (2.5 ECTS) to grow your entrepreneurial mindset and learn how that can benefit both your current research and future career.

The course specifically leverages AI, data science, and computer science in the service of societal and environmental challenges in for instance health-tech, green-tech, manufacturing, and business. The aim is to build entrepreneurial capacity and to increase the establishment of university-based startups. 
Participants are not expected to bring their own startup ideas. Instead, you will be introduced to idea generation techniques to create your own concepts in teams during the course.
Target group: We welcome PhD students and Post-doctoral researchers from computer/data related disciplines with little to no business experience from any Danish university.


The programme

The themes for each of the four days are as follows:

May 27:  Entrepreneurial Mindset
May 28:  Design Thinking & Concept Development
May 29:  ML Ops & Venture Building
May 30:  Commercialization & Pitch Readiness
May 31:  Culminating Pitches & Looking Ahead

The programme is co-developed by AAU, DTU, DIREC and AI Pioneer Centre.
This year the course takes place in DTU Skylab and we recommend you to stay at Zleep Hotel Lyngby
We look forward to seeing you at DTU Skylab.