27 May 2025
Computer Science
Title: Exploiting Problem Structure in AI Planning
Lecturer: PhD Daniel Gnad
Time: 10.15 -11:00
Location:Alan Turing, E-huset, Campus Valla
Abstract:
Planning is a core challenge in Artificial Intelligence. Developing systems that can achieve complex goals autonomously requires the capability of planning and thinking ahead. While recent advances in large generative models and foundation models have shown outstanding performance in many applications, they still fail to solve complex planning problems. AI planning in the form of model-based reasoning has focused on enabling such capabilities for many years, but, in practice, existing solutions often fail to scale to larger problems. By analyzing the inherent structure of the given problem, it is possible to push the limits of reasoning algorithms. This can take several forms that work on different levels of the algorithms. I will present two paradigms that exploit problem structure to make planning as state-space search more efficient. The first one is decoupled search, which decomposes the problem by analyzing the dependencies between model components. This leads to an exponential reduction in search effort, as it avoids enumerating reorderings of independent transitions. The second approach is exploiting problem structure to efficiently compute well-informed heuristics that guide the search process. This is done by identifying structurally simple components for which exact solutions can be computed in polynomial time, which leads to enhanced search performance and overall better scaling behavior.
16 May 2025
Fluid and Mechatronic Systems
Title: Robustness and Credibility in Distributed Modelling and Simulation
Lecturer: Robert Braun, IEI
Time: 10.15 -11:00
Location: ACAS, A-building, Campus Valla
Abstract:
Modelling and simulation play a critical role in engineering, supporting both the design of new products and systems, as well as the monitoring and continuous improvements of existing ones. The effectiveness of simulation tools depends on four key factors: performance, credibility, interoperability, and standardization. In other words, simulation software must be fast, reliable, and able to connect seamlessly with other tools via standardized interfaces.
This lecture presents how these requirements can be met using the Transmission Line Modelling (TLM) technique in combination with three open simulation standards: the Functional Mock-up Interface (FMI), System Structure and Parameterization (SSP), and the Distributed Co-simulation Protocol (DCP). TLM is a numerically robust method that ensures absolute stability when coupling simulation solvers. It can be employed for both parallel simulation and co-simulation and is well-suited for real-time applications.
The lecture will highlight recent research outcomes, including an approved change request to the FMI standard, the implementation of TLM-based co-simulation with adaptive communication step sizing, successful TLM co-simulation with DCP, and the development of several open-source software libraries and tools. Looking forward, the research aims to establish a modular, distributed co-simulation environment for real-time and faster-than-real-time applications with good accuracy and credibility. The commitment to open standards and open-source solutions ensures flexibility and helps avoid vendor lock-in.
14 May 2025
Electrical Engineering with specialization in Automatic control
Title: Reinforcement Learning: From myth to super intelligence
Lecturer: PhD Farnaz Adib Yaghmaie
Time: 13:15-14:00
Location: Ada Lovelace, B-building, Campus Valla
Abstract:
Reinforcement Learning (RL) is currently one of the most significant technological advancements. From its early successes in playing Atari games to recent breakthroughs in Large Language Models and robotics, RL has played a pivotal role. RL is closely connected to optimal control theory, a well-established field in control systems that focuses on controlling dynamical systems while optimizing a performance index. This lecture aims to explore RL within the context of Artificial Intelligence (AI), defining and redefining RL for control problems. I will discuss RL's position within the AI field and its unique features compared to other AI domains. I will highlight the connection between RL and optimal control problems. Additionally, I will examine the opportunities and challenges of applying RL to control problems, including key considerations such as stability, safety, reliability, efficiency, and real-time operation that RL solutions should provide for control applications. Finally, I will discuss recent developments in RL that bring the field closer to practical control applications.
15 April 2025
Applied physics
Subject: Advanced photophysical strategies in modern OLEDs
Lecturer: PhD Glib Baryshnikov
Time: 13:15-14:00
Location: K2, Kåkenhus, Campus Norrköping
Abstract
Over the past few decades organic electronics became one of the most important fields of science for the humanity. Huge consumer success and impressive technical abilities of novel electronic devices have resulted in the necessity of further scientific investigations and developments in this field. The significant competitive potential of organic light emitting diodes (OLEDs) and a number of design and technological features, that are unique to this class of devices, have created preconditions for commercialization of OLEDs as basic elements in display technologies, automotive engineering, biomedicine and dynamic lighting systems. The lecture summarizes some new strategies for development of revolutionary emitters for OLEDs. The “new strategies” involves the usage of organic luminescent radicals (for orange-green region), metal-free phosphors (for red, green, blue regions) and doubly thermally activated delayed fluorescent dyes (for whole visible region) as OLED emitters. The successful implementation of these strategies includes a combination of computational design with organic synthesis, a comprehensive study of newly synthesized materials and the fabrication of devices to make a breakthrough in OLED performance and to support a sustainable development in this field.
28 February 2025
Computer Science
Subject: Gamification and Serious Games for Health and Learning
Lecturer: Aseel Berglund
Time: 10:15-11:00
Location: Alan Turing, E-huset, Campus Valla
Abstract
Gamification and serious games have a strong potential to improve user engagement, enhance outcome, and motivate certain behaviors in both healthcare and education. This lecture explores research at the intersection of computer science, health informatics, educational technology, and behavioral psychology, demonstrating how gamified approaches can enhance digital interventions across multiple domains. Special attention will be given to the methodological contributions in developing and assessing gamified applications, particularly in the context of increasing physical activity and reducing sedentary behavior. Through case studies and practical examples, attendees gain theoretical and practical insights into the design and implementation of serious games and adding immersive gaming elements into nongame contexts, like a website, learning management system or business’ intranet to increase participation.
