Fall Term 2026

We are delighted to welcome a number of distinguished computer scientists to the upcoming IfI colloquium in the Fall Term HS 2026. We are looking forward to inspiring encounters with our guests, presenting topics from different areas of computer science.

The IfI colloquium is a free public event for researchers, students and the interested public and does not require registration. 

The IfI colloquium is held in English and takes place from 17:15 to 18:30 in room BIM 4-033 at the Department of Informatics (IfI), Binzmühlestrasse 11, 8050 Zürich. 

All the talks are held onsite.

If you have further questions please contact Karin Sigg.

Flyer to download (PDF, 392 KB)

Newsletter IfI Colloquium
We announce our IfI Colloquium talk series every semester via email. If you want to subscribe to this mailing list please send an email to Karin Sigg.

01.10.2026 – High-Performance Scientific Simulations of Chaotic Fluid Systems 

Speaker:  Prof. Dr. Tülin Kaman

Host: Prof. Dr. Renato Pajarola

Abstract

Understanding and predicting the behavior of complex systems in science and engineering applications requires “solving” the computational problem through desired capabilities such as high-resolution simulations, accurate and robust numerical algorithms, efficient algorithm implementation and the development of scalable software frameworks. The first step is mathematical modeling which explains the observed physical phenomena using equations. The second step is computational modeling which is based on the choice of spatial discretization methods and numerical algorithms. Computational scientists and engineers achieve better agreement between numerical simulations and experiments through careful verification, validation and uncertainty quantification studies. Software developers need be aware of the challenges from the effective usage of computational resources to the trade-offs between communication, computation and memory on modern, massively parallel computing systems. In this talk, we focus on the computational aspects of numerical algorithms in particular efficiency and scalability of algorithms on high-performance computing. We discuss the skills needed to design and develop a massively parallel, highly-scalable, accurate and robust software framework and its applications in computational fluid dynamics for the numerical simulations of hydrodynamic instabilities to understand the dynamics of turbulence.

Bio

Tülin Kaman is an affiliated associate professor in the Department of Mathematical Sciences at the University of Arkansas (UofA), Fayetteville, USA, and a guest professor in the Department of Informatics (IFI) at the University of Zurich (UZH). 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. She joined the IFI as an academic guest during her 2024-2025 Collegium Helveticum Senior Fellowship at the Swiss Institute for Advanced Study at ETH Zurich and received the 2025-2026 Verena Meyer Visiting Professorship, supported by the Faculty of Business, Economics, and Informatics at UZH. As the Lawrence Jesser Toll Jr. Endowed Chair at UofA, she established the Computational and Applied Mathematics Group and served as a faculty advisor for the UofA Association for Women in Mathematics (AWM) and UofA Society for Industrial and Applied Mathematics (SIAM) Student Chapters. In Fall 2025 semester, with her students she established the Women in Informatics Network Zurich (WINZ) and the University of Zurich Association for Computing Machinery (ACM-W) Student Chapter to support undergraduate and graduate students in their education and careers across all computing fields.

22.10.2026 – Are We Automating Our Own Future Away? The Socio-Technical Cost of AI Agents in Open Source Ecosystems

Speaker:  Prof. Dr. Igor Wiese

Host: Prof. Dr. Thomas Fritz

Abstract

For decades, the sustainability of Open Source Software (OSS) has relied on an onboarding process in which newcomers overcome complex socio-technical barriers. This developmental process is not merely transactional; it is deeply rooted in human motivation, communication, and the strategic guidance of experienced maintainers who act as community gatekeepers. Empirical research demonstrates that while technical excellence is required, social dimensions such as mentorship, empathy, and technical fun are what ultimately build a sustainable sense of belonging and long-term contributor retention. Great maintainers explicitly dedicate their attention to fostering this contribution environment, recognizing that communication and mutual human recognition form the very bedrock of open-source sustainability. Today, however, the unprecedented introduction of AI agents and generative tools threatens to overhaul the human-centric ecosystem. As AI automates lower-complexity tasks (and maybe more complex ones), it optimizes short-term individual productivity while paradoxically compromising the practical training grounds where newcomers build self-efficacy and initial project familiarity. In this talk, we will reflect on whether AI agents signify the peak of software engineering efficiency, or whether we are quietly automating a sense of belonging that keeps our communities alive, exploring the interplay between human motivations and the rise of agentic automation.

Bio

Dr. Igor Scaliante Wiese is a Full Professor of Computer Science at the Federal Technological University of Paraná (UTFPR) - Brazil and a CNPq Research Productivity Fellow. Dr. Wiese’s research focuses on mining software repositories and qualitative analysis to understand multiple phenomena in open source communities. Currently, Dr. Wiese’s active research addresses initiatives to foster gender diversity and a sense of belonging among underrepresented contributors. Concurrently, his latest projects examine the intersection of human and cognitive styles with agentic tools, focusing on how Generative AI can reshape onboarding barriers. His research brings an essential socio-technical lens to the ongoing AI transition, challenging our fundamental paradigms of developer productivity and community sustainability. During his career, he has been widely recognized, receiving the ACM SIGSOFT Distinguished Paper Award (2021), the IEEE TCSE Distinguished Paper Award (2020), and an Honorable Mention Award at the ACM CSCW conference (2020).

29.10.2026 – Towards Robust and Scalable Multi-Agent Aerial Manipulation

Speaker:  Dr. Sihao Sun

Host: Prof.  Dr. Davide Scaramuzza

Abstract

Aerial manipulators act as flying hands, enabling physical interaction with the environment and the manipulation of objects. However, their limited load capacity restricts the forces and torques that each platform can exert on the objects. Multi-agent aerial manipulation offers a promising direction to fundamentally overcome these limitations. In this presentation, I will present our recent work on a centralized approach to the cooperative aerial manipulation of a cable-suspended load, along with our explorations of decentralized solutions aimed at improving scalability and fault tolerance. I will also discuss related work in the field of mechanical design, as well as learning-based and model-based planning and control for aerial manipulators. These developments open the door to future dexterious, robust, and scalable multi-agent aerial manipulation systems.

Bio

Sihao Sun is a postdoctoral researcher funded by NWO (Dutch Research Council) Veni grant, embedded in the Department of Cognitive Robotics at Delft University of Technology. He received his PhD in Aerospace Engineering from TU Delft in 2020, after which he held postdoctoral positions with the Robotics and Perception Group at the University of Zurich and the Robotics and Mechatronics Group at the University of Twente. He is the winner of an IEEE Robotics and Automation Letters Best Paper Award, and the NASA Tech Briefs Award. His work has been published in leading journals, including Nature, IEEE Transactions on Robotics, and Science Robotics. His research focuses on planning, control, and perception for aerial robots.

12.11.2026 – tba

Speaker:  Prof. Dr. Aviv Tamar

Host: Prof.  Dr. Giorgia Ramponi

Abstract

tba

Bio

Aviv Tamar is an associate professor at the Electrical and Computer Engineering department at Technion. His work focuses on reinforcement learning and robot learning. Aviv is the recipient of the Krill prize, an ERC starting grant, and best paper awards at NeurIPS and NSDI.

26.11.2026 – Can We Trust the Scoreboard? Toward Reliable AI4SE Evaluations

Speaker:  Prof. Dr. Maliheh Izadi
 

Host: Prof.  Dr. Alberto Bacchelli

Abstract

Large language models and autonomous agents are increasingly used to write, test, and repair software, and benchmarks are the primary instrument for measuring their progress. Yet as AI for Software Engineering (AI4SE) has grown explosively, rigorous evaluation has not kept pace: benchmark knowledge is fragmented across tasks, selecting contextually relevant benchmarks is difficult, benchmark creation lacks standardization, and many widely used benchmarks suffer from flaws, such as data contamination and unrealistic tasks, that undermine the conclusions drawn from them. This talk maps out these challenges and presents our efforts to address them: systematically organizing and assessing the benchmark landscape, developing guidelines and tooling for rigorous benchmark construction, and building new benchmarks that evaluate LLMs and agents on realistic software engineering tasks.

Bio

Dr. Maliheh (Mali) Izadi is currently a senior research scientist at Google LLC, Switzerland. She is also an assistant professor in the Faculty of Electrical Engineering, Mathematics, and Computer Science at Delft University of Technology, the Netherlands. Her research focuses on solving challenges of building and tailoring LLMs and autonomous agents to source code and software engineering processes, such as rigorous evals, model memorization, IDE integration, and in-IDE Human-AI interaction. At TU Delft, she leads theAISE (AI-enabled Software Engineering) research lab. Her work has been supported by various funding and awards, including a Google Research Scholar Award (2025) and an Amazon Research Award (2024), as well as industry collaborations such as JetBrains Research (AI4SE) and Meta (FUSE lab). 

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