Search
Close this search box.
Categories
Events

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

Categories
Previous events

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

Categories
Previous events

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.

Categories
Previous events

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

Categories
Phd school Previous events

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

Categories
Previous events

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.
Categories
Phd school Previous events

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. 

Categories
Phd school Previous events

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

Categories
Previous events

Summer School on Privacy-Preserving Machine Learning

Summer School on Privacy-Preserving Machine Learning

From August 1 to August 4, 2022, the Departments of Computer Science at ITU Copenhagen and Aarhus University invite you to the Summer School on Privacy-Preserving Machine Learning.

Privacy-Preserving Machine Learning is an important and exciting research subject that investigates how to benefit from machine learning techniques while preserving the privacy of training data and learned models.

At the PPML School 2022 lecturers with both a theoretical and applied background will cover a broad spectrum of subjects such as Multiparty Computation, Fully Homomorphic Encryption, Differential Privacy, Federated Learning as well as practical attacks. Current confirmed speakers are:

  • Emiliano De Cristofaro (UCL)
  • Rafael Dowsley (Monash University – tentative)
  • Divya Gupta (Microsoft Research)
  • Peter Kairouz (Google)
  • Yuriy Polyakov (Duality)
  • Yang Zhang (CISPA)

The school is aimed at PhD and Master students in the areas of Security as well as Machine Learning, but we also encourage researchers as well as other people with an interest in the area to attend.

Registration for the school is now open for a fee of 500 DKK (approximately 70 USD or 67 EUR). Students can obtain 3 ECTS for attending the school.

The event is organized by Bernardo David, Associate Professor at ITU Copenhagen and Carsten Baum, Assistant Professor at Aarhus University and will take place from August 1st until August 4th on the campus of ITU Copenhagen. We are currently investigating a remote participation option, but this is so far not decided.

More information will be provided soon. We will provide information about potential stipends at a later point of time.

Registration deadline is on June 30th!

The event is supported by the International Association for Cryptologic Research, the Danish Data Science Academy, the Pioneer Centre for Artificial Intelligence as well as the Digital Research Centre Denmark (DIREC).

Categories
News Phd school Previous events

MOVEP 2022: Five Intensive Days on Modelling and Verification

17 JUNE 2022

MOVEP 2022: Five Intensive Days on Modelling and Verification

Automated systems like self-driving cars and AI-based decision support are becoming an increasingly large part of our everyday lives, and so is the need for modelling and verification of the software running these systems. At the MOVEP 2022 Summer School, hosted by the Department of Computer Science, Aalborg University, leading researchers, students and people from the industry convened to discuss challenges and opportunities within this field.

By Stig Andersen, Aalborg University

The five-day MOVEP Summer School 2022 (June 13-17) on modelling and verification of parallel processes had attracted 70+ participants, primarily PhD students, but also people from the industry.

With the lecture hall of the Department of Architecture, Design and Media Technology right at Aalborg’s harbour front as a great venue, they enjoyed a packed programme of talks and tutorials from 11 leading researchers on model checking, controller synthesis, software verification, temporal logics, real-time and hybrid systems, stochastic systems, security, run-time verification, etc.

An exciting field

One of the speakers was Christel Baier, Professor and Head of the chair for Algebraic and Logic Foundations of Computer Science at the Faculty of Computer Science of the Technische Universität Dresden, and together with Joost-Pieter Katoen, the author of a key publication in the field, Principles of Model Checking (MIT Press, 2008). She has been working within the broad field of verification and analysis techniques for stochastic operational models for more than twenty years.

– I really had not expected to work so long within this area, but as it often turns out in science, apparently simple problems are not at all simple and will require more research. So, if the students at this summer school would take the message that this is an exciting and very important field and choose to explore it further, I would be very happy. MOVEP is a very nice event, and being able to come to Denmark and not least being able to meet again after the Corona shutdown is really great, she says.

Application in different fields

Another speaker was Nir Piterman, Professor in the Department of Computer Science and Engineering, University of Gothenburg and Chalmers, and a prominent figure within formal verification and automata theory. He kicked off the summer school programme Monday morning with a tutorial on reactive synthesis, which is a technique for automatically generating correct-by-construction reactive systems from high-level descriptions.

 – In my tutorial, I tried to give the participants a taste of the so-called discrete two-player turn-based games technique, where you think about the environment as one player and the system as another player. The interaction is like a game between the two, and the system has to come up with a strategy to satisfy some goal, he explains.

Nir Piterman also sees an event like MOVEP as a very good opportunity for young researchers to be exposed to concepts and techniques that they would not necessarily be exposed to otherwise.

– It is my hope that the talks and tutorials at this event will fertilize their work and provide them with new ideas about how to apply these techniques in different fields. One possible usage of two-player games is synthesis, but the usage could be wider and potentially applied to other problems, he says.

Nir Piterman is currently the holder of an ERC consolidator grant to study the usage of reactive synthesis for multiple collaborating programs.

Explainability

In her tutorial, Christel Baier focused on explication, which refers to a mathematical concept that in some way sheds light on why a verification process has returned a given result.

– Explainability is important. We have to make systems more understandable to everyone – scientists, designers, users, etc. Today, everybody is an IT user, so this is not only relevant for computer scientists, she says.
According to Christel Baier, there is a higher purpose:

– Since systems make decisions, users should have the opportunity to understand why decisions were made. Moreover, users should be supported in making decisions by themselves and be given an understanding of the configuration of these systems and their possible effects. Again, it comes down to the question of cause and effect, which was a recurring theme of my tutorial.

The research on the results presented by Christel Baier at her tutorial has been carried out within and is motivated by the missions of the collaborative projects “Center for Perspicuous Computing (CPEC)” and “Centre for Tactile Internet with Human-in-the-Loop (CeTI)”.

Correct-by-construction

Research within modelling and verification of parallel processes may also explore the question: Could we automatically generate systems that perform exactly according to the specifications instead of checking afterwards that they do? Nir Piterman dealt with this topic in his tutorial.

– Techniques to automatically generate correct-by-construction reactive systems from high-level descriptions have been explored in academia for quite a number of years. It has proven to work in some domains, but it would not be realistic to set as an ambition to build one synthesizer that you feed a specification to and expect it to auto-generate safe and error-free systems for all possible programming domains, he says.

According to Nir Piterman, the most successful applications so far have been within robotics. However, this success makes us think about what is the meaning of correct-by-construction.

– What does “correct” really mean? If it means that the system does exactly what was described in the specification, what happens if the specification is flawed? So, the focus of the correctness problem might change: Rather than making sure that the system matches the specification, the task is to ensure that the specification is thorough enough and reflects what the designer had in mind.

FURTHER INFORMATION

  • MOVEP 2022 is hosted by the Department of Computer Science, Aalborg University (primary organizer Martin Zimmermann, Associate Professor) and co-sponsored by DIREC an S4OS.
  • The first five editions of MOVEP took place in Nantes (France) every other year from 1994 to 2002. It then moved to Brussels (Belgium) in 2004, Bordeaux (France) in 2006, Orléans (France) in 2008, Aachen (Germany) in 2010, Marseille (France) in 2012, Nantes (France) in 2014, Genova (Italy) in 2016, Cachan (France) in 2018 and online in 2020.
  • More info on the MOVEP 2022 website.

CONTACT
Martin Zimmermann
Associate Professor
Department of Computer Science
Aalborg University
Mail: mzi@cs.aau.dk
Phone: +45 9940 8770

Stig Andersen
Communications Officer
Department of Computer Science
Aalborg University
Mail: stan@cs.aau.dk
Phone: +45 4019 7682

Professor Nir Piterman, University of Gothenburg and Chalmers

Professor Christel Baier, Technische Universität Dresden