IfI Summer School 2025
The IfI Summer School is a week-long event for PhD students and research assistants in informatics and related fields, where invited experts teach a number of different topics in day-long courses.
Dates and Location
The IfI Summer School will take place between 23 June - 27 June 2025 at the University of Zurich, Department of Informatics.
Course location:
Binzmühlestrasse 14
8050 Zurich
Class room BIN 2.A.01
List of Courses
| Day | Course | Instructor | ECTS credits |
|---|---|---|---|
| Monday, 23 June |
Designing AI Agents for Collaborative Data Analysis |
Prof. Anamaria Crisan, PhD | 0.5 : Doctoral |
| Tuesday, 24 June |
The Art of Scientific Computing | Prof. Tülin Kaman, PhD | 0.5 Methodology |
| Wednesday, 25 June |
The Real World Use and Non-Use of Care Technologies | Prof. Dr. Aisling O'Kane | 0.5 Doctoral |
|
Thursday, |
Understanding the Impact of Online Platforms | 0.5 Doctoral | |
| Friday, 27 June |
GPU code optimisation with CUDA | 0.5 Methodology |
Please note: All courses cover a full day. You need to attend the full day to get the 0.5 ECTS credits!
Please make sure your register for each course you want to attend separately.
Daily Schedule
| 08:45 - 09:00 | Check-in |
| 09:00 - 10:15 | Instruction |
| 10:15 - 10:45 | Coffee break |
| 10:45 - 12:00 | Instruction |
| 12:00 - 13:00 | Lunch break |
| 13:00 - 15:00 | Instruction |
| 15:00 - 15:30 | Coffee break |
| 15:30 - 17:00 | Instruction |
Registration and Fees
The Summer School is primarily targeted towards doctoral students in computer science and related fields from the University of Zurich as well as from other universities.
Registration via registration portal is now open until 17 June 2025
- The fees can only be paid by credit card, PostFinance or TWINT using the registration links.
- Please make sure your register for each course you want to attend separately.
- Please note that we cannot issue any invitation letters for visa issues.
- Contact: Karin Sigg
Links for registration and fees
- Registration is free for IfI research assistants, IfI doctoral students, and IfI postdocs. (Registration via link sent by email)
- For all other UZH participants, fees are 50 CHF per course day. Registration here.
- For all other participants, fees are 100 CHF per course day. Registration here.
ECTS Credits
For UZH students, you can find the ECTS credit awarded by each course in the overview above. Non-IfI students who would like to acquire credits, need to talk with the person who is in charge of credit transferring at their home university first and find out if the ECTS credits awarded by IfI at UZH are accepted/recognized.
Courses and Instructors
|
MONDAY 23 June |
Designing AI Agents for Collaborative Data Analysis |
| Course Description |
AI agents are being developed for variety of applications, from the creation of art, to writing support, as tutors, and as coding assistants. In this course, we will explore using AI agents to help humans carrying our data analysis and visualization. We will place priority on the human-AI collaboration relationship, considering the unique sociotechnical challenges of designing analytic agents. This course is divided into two parts: a lecture component and a hands-on exercise. The lecture component (3 hrs) will cover the challenges of designing visual analytic systems with AI assistants. The hands-on component (3hrs) will work towards developing and testing a visualization analytic AI assistant. We will use Streamlit, a light-weight Python library for developing front-end interfaces, to create an analytic chatbot system. Working with data presents unique challenges. AI agents not only need to write code, but they also need to understand the dataset and produce reasonable responses for the human to review. Moreover, the needs for the human analyst or final data consumer need to be taken into account in order to ensure the analysis is robust and trustworthy. The course will draw on perspectives from the Human-Computer Interaction, Information Visualization, and Natural Language Processing research community for explore the unique partnership between people and AI agents. |
| Instructor | Prof. Anamaria Crisan, PhD |
|
|
Anamaria (Ana) Crisan is an Assistant Professor at the University of Waterloo. Her interdisciplinary research areas concern the development of visualization systems that support the application of human-centered AI/ML technology to data work. Prior to joining the University of Waterloo, Ana held several industrial research appointments, most recently as a Lead Research Scientist at Tableau (2019 – 2024). Her award-winning research appears in top -tier venues of ACM (CHI, FAccT) and IEEE (Vis) in addition to highly ranked biomedical journals (Nature, Oxford Bioinformatics, PLOS). She has served on the program committees for CHI, FAccT, CSCW, and Vis, is the current papers co-chair of the Visualization in Data Science Symposium. |
TUESDAY 24 June |
The Art of Scientific Computing |
| Course Description | Computational Science and Engineering (CSE) is a rapidly growing field. Theory and experiments are supported by computational work to understand the behavior of complex systems in science and engineering applications. The set of knowledge and skills needed in CSE lies at the intersection of mathematics, computer science, and natural sciences and engineering. Many scientific and engineering problems are described by mathematical models, the models are analyzed and solved using numerical algorithms, which in turn are implemented using programming languages. The development of efficient, accurate, and robust software for the numerical simulation of complex systems is the key point in CSE research. The course offers students opportunities to explore a diverse set of projects and improve the programming skills necessary to understand ideas and algorithms in parallel scientific computing and scientific machine learning. Training for the next generation of computational scientists includes the ability to think about, formulate, organize, and implement scientific computing programs. The course content is a mixture of theory and practice in numerical methods, high performance computing, and machine learning. No prior knowledge is needed for this course. The hands-on activities will be carried out using programming languages C/C++/Fortran. |
| Instructor | Prof. Tülin Kaman, PhD |
|
|
Tülin Kaman is an associate professor in the Department of Mathematical Sciences at the University of Arkansas (US), Senior Fellow of the Collegium Helveticum at the Swiss Institute for Advanced Study at ETH Zurich and a guest professor in the Department of Informatics at the University of Zurich. She received her Ph.D. in Applied Mathematics and Statistics from Stony Brook University in New York (US), winning the Woo Jong Kim Dissertation Award in 2012. She was a Paul Scherrer Institute Fellow, a postdoctoral researcher, and a lecturer in the Department of Computer Science at ETH Zurich, and the Institute of Mathematics at the University of Zurich. At the University of Arkansas (UofA), she established the Computational and Applied Mathematics Group as the Lawrence Jesser Toll Jr. Endowed Chair. She served as a faculty advisor for the UofA Association for Women in Mathematics (AWM) and the Society for Industrial and Applied Mathematics (SIAM) Student Chapter. She is currently a member of the AWM Membership & Community Portfolio Committee. Her research focuses on modeling and simulations in fluids, numerical methods for partial differential equations, numerical algorithms in parallel scientific computing, and uncertainty quantification. |
|
WEDNESDAY 25 June |
The Real World Use and Non-Use of Care Technologies |
| Course Description | There are many opportunities to harness technology innovation in the provision of health and care. However, the real-world use and adoption of these technologies can be less than straightforward – people are diverse, unpredictable, and just plain weird. In this course, we will discuss approaches to studying people's use of technology outside clinical settings, involving end users in the design process, leveraging existing commercial technologies for care, and engaging with the weirdness of everyday healthcare. |
| Instructor | Prof. Dr. Aisling O'Kane |
|
|
Aisling Ann O'Kane is an Associated Professor of Human-Computer Interaction at the University of Bristol. As part of the Bristol Interaction Group (BIG), she studies digital health and care technologies in people's everyday lives. Her work focuses on studying and designing technologies for use outside of clinical settings, including AI, medical devices, smart home technologies, wearables, and social media. Her research covers a wide range of conditions and contexts, including diabetes, mental health, social care, Parkinson's, menopause and parenting. She publishes in HCI venues such as ACM CHI, CSCW, and DIS, and is currently involved in UKRI AI4CI, EPSRC TORUS, ESRC Centre for Sociodigital Futures, and EPSRC CDT Digital Health and Care. |
THURSDAY 26 June |
Understanding the Impact of Online Platforms |
| Course Description | Measuring and understanding the impact that online platforms, such as Google Search, YouTube, or Twitter, have on information consumption is a challenging yet crucial research area. In this course, we will examine concerns about the online information ecosystem that are often discussed in metaphorically compelling yet operationally limited terms (e.g., filter bubbles, echo chambers, and rabbit holes) and explore an interdisciplinary set of methods, tools, and concepts that can provide a more robust foundation for evaluating the core elements underlying such concerns. This includes considering the complex relationships between users, algorithmic systems, and content creators, understanding the pros, cons, and tradeoffs of different measurement approaches, and adapting that knowledge to understand the impact of emerging technologies (e.g., ChatGPT and Claude). |
| Instructor | Ronald Robertson, PhD |
|
|
Ronald E. Robertson is a research scientist at the Stanford Cyber Policy Center who designs experiments and software to explore human-algorithm interactions in digital spaces, especially as they relate to influence and information seeking. His research on these topics has been published in general interest journals, including Nature, Science Advances, and PNAS, and computer science conferences, such as the Proceedings of the ACM: Human-Computer Interaction, the Proceedings of the Web Conference (WWW), and Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM). |
FRIDAY 27 June |
GPU code optimisation with CUDA |
| Course Description | This intensive block course on GPU optimisation harnesses Nvidia’s CUDA platform to unlock the full performance potential of modern graphics hardware. Participants will explore best practices for designing and fine-tuning CUDA kernels, optimising memory management across various hierarchies, and fully exploiting parallel processing capabilities. The curriculum addresses common GPU bottlenecks—such as memory bandwidth constraints, thread divergence, and synchronization overheads—while also delving into advanced techniques like warp-level programming and concurrent kernel execution. Through a blend of in-depth theory and hands-on exercises, students will gain the expertise needed to achieve peak throughput and efficiency in GPU-centric applications. |
| Instructor | Prof. Dr. Douglas Potter |
|
|
Dr. Douglas Potter obtained a PhD in computational astrophysics from the University of Zurich and now serves as the managing director of its Department of Astrophysics. With a rich background that spans both industry and academia—including prior roles as a consultant and software developer—Dr. Potter specializes in developing high-performance computing applications for large-scale simulations by leveraging GPU and parallel programming technologies. In addition to his involvement in research projects, he also imparts his expertise through courses on high-performance computing, bridging the gap between scientific research and practical, real-world applications in computational science. |
