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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.

Speakers:

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

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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.  

Accessibility


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.




Preparation

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

  1. 

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.
  2. 

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

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Events

Young Researcher Entrepreneurship Bootcamp

phd course

Young Researcher entrepreneurship bootcamp

Join this PhD-course 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.

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Afholdte arrangementer

Summer School on Missing Data, Augmentation and Generative Models

phd summer school

Missing Data, Augmentation and Generative Models

This summer school will introduce the state-of-the-art for handling too little or missing data in image processing tasks. The topics include data augmentation, density estimation, and generative models.

Missing data is a common problem in image processing and in general AI based methods. The source can be, for example, occlusions in 3D computer vision problems, poorly dyed tissue in biological applications, missing data points in long-term observations, or perhaps there is just too little annotated data for a deep-learning model to properly converge.

On this PhD summer school, you will learn some of the modern approaches to handling the above-mentioned problems in a manner compatible with modern machine learning methodology.

This summer school will introduce the state-of-the-art for handling too little or missing data in image processing tasks. The topics include data augmentation, density estimation, and generative models. The course will include project work, where the participants make a small programming project relating their research to the summer school’s topics.

The summer school is the fifteenth summer school jointly organized by DIKU, DTU, and AAU. DIREC is co-sponsor of the PhD school.

Photo from the summer school in 2022

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Phd school Afholdte arrangementer

IC2S2 – 9th International Conference on Computational Social Science

IC2CS

9th International Conference on Computational Social Science

IC2S2 has emerged as the dominant conference at the intersection of social and computational science, bringing together researchers from around the world in economics, sociology, political science, psychology, cognitive science, management, computer science, statistics and the full range of natural and applied sciences committed to understanding the social world through large-scale data and computation.

IC2S2 has emerged as the dominant conference at the intersection of social and computational science, bringing together researchers from around the world in economics, sociology, political science, psychology, cognitive science, management, computer science, statistics and the full range of natural and applied sciences committed to understanding the social world through large-scale data and computation.

The conference will begin with a one-day session of tutorials in a range of social and computational methods (July 17). This will be followed by a full-scale three-day conference (July 18-20) featuring research and researchers from around the world, across a broad range of relevant fields, and working on all areas of computational social science to advance its many frontiers.

Unlike important social computing and associated computer science conferences, the IC2S2 community actively balances and maintains a conversation between social and computational scientists which integrates technological advances and opportunities with social scientific rigor and insight.

DIREC is co-sponsor of IC2S2.

Picture “Sunset at Nyhavn” courtesy of Jim Nix

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Afholdte arrangementer Phd school

Contemporary Computer Supported Cooperative Work Research

phd course

Contemporary Computer Supported Cooperative Work Research

This PhD course is for PhD students conducting their research within the areas of Computer Supported Cooperative Work (CSCW) and Human Centred Design – currently working on positioning their research theoretically to push the boundaries for the novel and contemporary research contributions in CSCW research.

Contemporary CSCW research – How to create the literature scaffolding of contemporary CSCW PhD research which link to foundational aspects of CSCW while pushing the CSCW research into new contemporary areas of research.

Theoretical themes include (but not limited to) Articulation work & Coordination, Classifications & Categories, Awareness & Translucence; Infrastructures & Invisible Work; Knowledge Sharing & Common Information Spaces.

Learning outcome

  • Develop CSCW research questions looking to the past and thinking about the future
  • Identify and discuss contemporary CSCW research literature directions
  • Analyze, and extend current CSCW research towards future contemporary research directions and frameworks

After the course, students will have a foundational base for developing their theoretical research framework for their CSCW thesis – which both connects to the past, while focus on future contemporary directions. 

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Afholdte arrangementer

Young Researcher Entrepreneurship Bootcamp

phd summer school

Young Researcher entrepreneurship bootcamp

Calling all young researchers in AI and data science with an interest in entrepreneurship!

Did you know that only 12-13% of PhDs end up in a tenure track academic career? The good news is that there are other exciting, fulfilling, flexible career paths, which you can shape yourself.

Join the Young Researcher Entrepreneurship Bootcamp (YREB) PhD summer school (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.

Aarhus University is the host of YREB’23.   

The programme

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

Day 1: Explore the unknowns through design thinking.
Day 2: Develop your entrepreneurial knowledge, skills, and mindset.
Day 3: Bring an idea into praxis – customer fit and technical practicalities.
Day 4: Commercialize an idea through business model and pitch training.

The programme is co-developed by AAU, AU DTU, KU, DIREC and AI Pioneer Centre.

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.

What you will learn

By developing your entrepreneurial mindset you will be better able to:

  • Generate research ideas that meet an actual need and validate whether they have the potential to become a viable business.
  • Grasp the fundamentals of creating a novel startup.
  • Understand the basics of ML Ops as a prerequisite for building an AI startup.
  • Take the steering wheel in your current research and future career.
  • Cultivate innovative thinking and presentation skills.
  • Navigate how to collaborate with tech transfer and innovation officers (e.g. Investores and intellectual property (IP)).

What is in it for you?

  • 2.5 ECTS
  • Insights into ideation, ML Ops, entrepreneurial mindset, testing business ideas etc.
  • Engaging, active learning approaches.
  • Meet inspiring, like-minded individuals, entrepreneurs, and educators.
  • Being invited to pitching event at Digital Tech Summit November 8th – 9th 2023.
  • This course is free of charge.
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Afholdte arrangementer

PhD course: Confronting Data Through Design Methods

PHD Course

Confronting Data Through Design Methods

 
Join this new PhD course and explore different modes of inquiry with data-applying design methods.


The focus will be on the implications for researchers working in the fields of Computer-Supported Cooperative Work (CSCW), Human-Computer Interaction (HCI), Participatory Design (PD) and Critical Data Studies, but the course is open to PhD students from all areas of work and design studies.


Lectures by:



  • Majken Overgaard, who is heading CATCH known for its curatorial focus on the possibilities of imagining new technological futures as activism. She is an external lecturer at ITU and the co-founder of Korridor – a new digital art collective – investigating emerging culture and art online right now, such as blockchains, web3 and NFT.
  • James Auger, who is the director of the design department at LMF, ENS Paris-Saclay and co-director of the Centre de Recherche en Design (ENS & ENSCI). He is also an Associate Professor at RMIT (Europe). His work explores ways through which practice-based design research can lead to more considered and democratic technological futures.
  • Naja Holten Møller, who is an Associate Professor at DIKU. She is the founder of the Confronting Data Co-lab, a cooperation of scholars working and acting together in support of the stakeholders we encounter and engage with in our research, focusing on critical public technologies.

The participants gain knowledge of:

  • speculative design as a method
  • how to apply speculative design in practice,
  • and the criteria for evaluating research within this field.

The PhD course is organized by Ass. Prof. Naja L. Holten Møller and PhD fellow Trine Rask Nielsen and Kristin Kaltenhäuser from the University of Copenhagen with support from DIREC.

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Afholdte arrangementer Phd school

VaMos 2023

VaMos 2023

17th International Working Conference on Variability Modelling of Software-Intensive Systems

VaMoS brings together researchers and practitioners to share ideas, results, and experiences about the quest for mastering variability.

Most of today’s software is made variable to allow for more adaptability and economies of scale, while many development practices (e.g., DevOps, A/B testing, parameter tuning, continuous integration) support this goal of engineering software variants.

VaMoS is the ideal venue to explore the underlying problems (automation, traceability, combinatorial explosion) and their solutions. As such, in addition to its usual call for technical research papers, VaMoS strongly supports the participation of aspiring young researchers as well as practitioners from industry.

Find more info about VaMoS

With support of the Carlsberg Foundation and DIREC, the organizers offer 10 free registrations for the VaMoS conference to motivated PhD students or postdocs that wish to attend the conference.

See how to apply for free registration

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Afholdte arrangementer

Gør din forskning synlig og forståelig uden for forskningsverdenen

27. september 2022

Gør din forskning synlig og forståelig uden for forskningsverdenen

På dette års DIREC-seminar inviterede vi ph.d.-studerende og andre interesserede i at synliggøre deres forskning uden for den akademiske verden til en workshop med Peter Hyldgård, som har mere end 20 års erfaring med videnskabsjournalistik og kommunikation.

Forskning er nøglen til vores forståelse af samfundets udfordringer, menneskets forudsætninger og teknologiens muligheder. Derfor er det vigtigt at forskning gøres tilgængeligt for så mange som muligt.

I forskningsverdenen har publicering i videnskabelige tidsskrifter en helt særlig status, og hvert år udgives millioner af forskningsartikler, doktorafhandlinger, bøger og antologier på tværs af kloden og inden for alle discipliner. Desværre er det meget få, der læser disse mange publiceringer. Det er derfor nødvendigt også at fokusere på andre typer formidling, der når ud til en bredere målgruppe, da det bidrager til at give forskning en mere tydelig rolle i samfundet og gør forskning mere interessant og vedkommende for den bredere befolkning.

På workshoppen var der fokus på, hvordan man fortæller en god historie om sin forskning, som alle kan forstå – uden at gå på kompromis med det faglige indhold, og hvordan man bygger bro til et publikum, der ikke umiddelbart har interesse i/viden om emnet

Peter Hyldgård præsenterede flere enkle værktøjer til at finde en historie om sin forskning, som kan bruges i mange sammenhænge: Når man skal søge midler, når man interviewes af en journalist – eller når man skal fortælle din onkel Adam om sit arbejde.

Workshoppen var en blanding af oplæg og små øvelser med en lidt større afsluttende øvelse, hvor deltagerne gav en – meget kort – mundtlig ‘pitch’ af deres forskning.