Welcome

The 8^th  Summer School on Computational Interaction, ACM Europe School will be held at the University of Luxembourg, Belval campus, Luxembourg.  It will take place on June 03 - 07, 2024.

This summer school teaches HCI students, researchers, and industry professionals computational methods and their application in user interface design, interactive systems, user modeling, and more. Each day will feature one or two outstanding speakers who will share their expertise on a technical topic relevant to Computational Interaction. Individual lectures will give students an overview of different topics in Computational Interaction, and will include exercises that will give students hands-on experience with Computational Interaction research.

Important Dates

• January 31^st, 2024 - Applications for the summer school open Apply here.
• February 28^th, 2024 - Application Deadline
• March 22^nd, 2024 - Application Deadline (first round)
• March 29^th, 2024 - Admissions notifications (first round)
• April 30^th, 2024 - Application Deadline (second round)
• May 3^rd, 2024 - Admissions notifications (second round)
• June 3^rd, 2024 - Start of Summer School
• June 7^th, 2024 - End of Summer School

All deadlines are in Anywhere on Earth (AoE) time zone.

Topics

We put together a remarkable program that features the leading experts in the area of computational interaction. These are the confirmed topics so far:

• Optimization methods for interface design and adaptation by Anna Maria Feit and João Belo, Saarland University, Germany.
  
  
This session will introduce a range of optimization techniques, encompassing exact mathematical methods, approximation algorithms, and multi-objective approaches. With hands-on examples, participants will learn how to apply these methods to problems in user interface design. We will explore how optimization can improve the usability of classic desktop and learn about its crucial role for emerging technologies such as Augmented Reality.



• Modeling and understanding user interfaces from pixels by Amanda Swearngin, Apple Inc., Washington, DC, USA.
  
  
This session will introduce modern techniques for UI understanding from pixels including object detection, transformers, and multi-modal models for understanding user interfaces at multiple levels of abstraction. These techniques are becoming rapidly adopted for a range of applications such as accessibility, design and developer tooling, and UI automation.



• Parameterization and Selection of Behavioural Models by Gilles Bailly, ISIR Lab, Sorbonne Université, France.
  
  
This session will introduce different methods inspired from compuational neurosciences to carefully evaluate computational models of human behaviour, including model simulation, parameter estimation and model comparison. We will especially focus on models of learning and decision making.



• Forward and inverse modelling in input by John H. Williamson, University of Glasgow, Scotland.
  
  
This session will discuss approaches to extracting user intention from signals. It will contrast forward (traditional ML) modelling, which optimises a mapping from sensors to inferred states; and inverse (Bayesian) approaches, which infers a distribution over inferred states given a model of how sensed states would occur. The session will bring together probabilistic Bayesian filtering and direct forward modelling for input devices.



• Charting the routes of thoughts in LLM-empowered conversational interactions by Xiaojuan Ma, Hong Kong University of Science and Technology (HKUST).
  
  
This session will introduce three computational frameworks for modeling the reasoning process of large language models (LLMs), naming chain-of-thought (CoT), tree-of-thoughts (ToT), and graph-of-thoughts (GoT). These frameworks aim to simulate how humans breakdown (and combine) ideas in complex reasoning and problem solving. One of their typical applications is to resemble human communication techniques and generate proper responses in highly dynamic conversations. We will discuss the conceptual models behind these frameworks, their benefits and limitations, and possible implementation in conversational interactions.



• Augmenting Ideation and Sensemaking in the age of LLMs: Concepts, Examples, and Opportunities from an HCI Perspective. by Gonzalo Ramos, Microsoft Research Redmond, Washington, USA.
  
  
The capabilities of emerging large language models and generative AI bring within line of sight having interactions with systems that mediate how we consume, process, and produce information and knowledge. This lecture, will focus on the question of GenAI to support and augment sensemaking and ideation activities by first introducing useful theories and frameworks to think about them and identify moments where GenAI can act in supporting them and how. Susequentely, it describes how some of these support ideas can be translated into practice and what are the human factors to consider. Finally participants will be guided, to implement some of the ideas and concepts presented, and to experience them in interactive form.



• Supporting rich interactions in mixed reality by John Dudley, University of Cambridge, UK.
  
  
This session will review the challenges inherent to supporting rich interactions in mixed reality and introduce effective methods for mitigating some of these challenges. We will explore strategies and techniques for accommodating ambiguous user input in the context of hand gesture input and text entry.