Docent lectures at the Faculty of Science and Engineering

Here we are announcing docent lectures at the Faculty of Science and Engineering.

9 October 2023

Wireless Power Transmission Enabling mm - Size Batteryless Implantable Devices

Subject: Electrical Engineering with specialization in Integrated Circuits and Systems
Lecturer: Alireza Saberkari, ISY
Time: 10:30 – 11:30
Location: Nollstället, floor 3, entrance 27, B Building, Campus Valla


Wireless power transmission (WPT) is a promising solution that has the potential to revolutionize the way we power up devices and machines. The basic principle of WPT is the transfer of electrical energy without physical conductors, potentially eliminating the need for batteries. The increasing miniaturization of electronic devices has led to increasing demand for WPT solutions for mm-scale sensors and implants. These tiny devices are typically used in a wide range of applications, such as medical implants, sensor networks, and Internet of Things (IoT). However, there are still challenges involved in widespread applications which need to be addressed. One of the major challenges in WPT is the ability to maintain high efficiency while increasing the distance between the external device or reader and the mm-scale sensor or implanted device.

The first part of this lecture provides an overview of available energy sources for implantable devices and their pros and cons. Specifically, RF energy harvesting and wireless power transmission will be discussed as a cost-effective technology for powering up devices. In addition, challenges associated with delivering power to implantable devices with mm-size antennas are highlighted leading to new research questions in terms of extending power telemetry range. The rest of the lecture will address the research that has been conducted toward the implementation of a battery-free wireless implantable device and extending the power transmission range.


12 October 2023

Mathematical modelling - a tool to discover drugs and promote health

Subject: Biomedical Engineering
Lecturer: Peter Gennemark, IMT
Time: 10:15 – 11:00
Location: IMT1, Building 462, Campus US


The lecture introduces and discusses how mathematical modelling can be used to increase knowledge of biology, physiology, disease progression and drug intervention. First, a set of dynamic mathematical models in form of ordinary differential equations of metabolic and body composition systems is described. These models are discussed with respect to their scopes, levels of complexity and types of research questions they can address. Second, mathematical models used in the discovery of nucleic acid-based drugs are introduced and their usage is exemplified. These examples are discussed in the context of typical pharmacokinetic och pharmacodynamic models used in drug discovery, and the importance of translational models that scale between species, such as mouse, monkey and human. Third, the rapid development of advanced in vitro systems is exemplified by a two-organ micro-physiological system and corresponding mathematical description. This system is discussed in relation to how drug discovery can be efficient and ethical, e.g., by reduced dependence on animal experiments. Finally, I give an integrated view that connects the three points above to the research on digital twins conducted by Gunnar Cedersund at IMT.


29 May 2023

Systems analysis for sustainability: Lessons from biogas solutions

Subject: Environmental Management and Engineering
Lecturer: Roozbeh Feiz Aghaei, IEI
Time: 13:15-14:00
Location: ACAS, A Building, Campus Valla


Contemporary societies face complex challenges such as climate change, environmental degradation, and resource depletion. A viable solution lies in transitioning towards a sustainable biobased economy, which necessitates a comprehensive understanding of the sustainability implications of different proposed solutions. By adopting a broad perspective, we can identify effective and feasible development pathways while minimizing the risk of shifting problems from one area to another.

In this lecture, I will present my research on biogas solutions to showcase the practical applications of different systems analysis methods. These include methods such as mass and energy flow analysis, life cycle assessment, multi criteria analysis, and spatial analysis. They enable us to address questions regarding potential, feasibility, environmental impact, economic performance, and the overall sustainability of different development pathways. I will argue that through the study of biogas solutions, we can derive valuable lessons that are applicable to Sweden's broader transition towards a sustainable biobased economy. By the end of this talk, attendees will gain a better understanding of the importance of systems analysis in realizing sustainable solutions in Sweden and beyond.


26 May 2023

Distributed Machine Learning over Wireless Networks: A Communications Perspective

Subject: Electrical Engineering
Lecturer: Zheng Chen, ISY
Time: 14:15-15:45
Location: Systemet, ISY, B Building, Campus Valla


Collaborative machine learning (ML) from decentralized data has gained significant attention in both academia and industry in recent years. Its key characteristic lies in multiple agents/nodes collaboratively training a shared ML model, either through the coordination of a central parameter server or in a fully decentralized manner using peer-to-peer information exchange. However, distributed ML over wireless networks introduces new challenges due to communication resource limitations (such as frequency, time, and space) and channel uncertainty, which can greatly impact learning performance and training latency.

The first part of this talk provides an overview of important research directions in distributed ML over wireless networks. These include resource allocation design, the effect of asynchronous training, privacy and security issues, and energy efficiency. Specifically, the concept of Over-the-Air (OtA) computation will be introduced as an efficient method for data aggregation and distributed computation of functions over networked nodes. The application of OtA computation in federated learning will be presented, which leads to new research questions in terms of communication design and signal processing. Finally, the last part of the talk focuses on the impact of medium access control (MAC) layer design and communication topology on the performance of consensus-based decentralized ML systems.


9 May 2023

Broad perspectives in environmental systems analysis and policy studies of biogas solutions

Subject: Environmental Management and Engineering
Lecturer: Marcus Gustafsson, IEI
Time: 10:15-11:00
Location: ACAS, A Building, Campus Valla


Biogas solutions can contribute to addressing many societal challenges, including reduced climate impact, access to renewable energy, waste management and nutrient circulation. There are well-established technologies for producing and using biogas, and with the present geopolitical situation in Europe, self-sufficiency in energy and other resources is becoming a pressing issue. Yet, waste-based biogas is a largely unexploited resource, not least in Sweden where studies suggest a potential 5-7 times higher than the current production. However, it is not clear how this potential could be realized, especially with a policy framework that provides insufficient support and fails to acknowledge all the benefits that biogas solutions could bring.

In this lecture, I will talk about the importance of broad perspectives in the context of environmental systems analysis and policy studies of biogas solutions. This comprises the use of life cycle perspective when assessing environmental performance, as well as acknowledging the multi-functional and cross-sectoral aspects of biogas solutions when assessing the policy framework. I will bring up examples on the climate performance of biogas and present a model for analyzing the policy landscape of biogas solutions. Finally, I will go into the challenges of developing the Swedish biogas sector.


22 March 2023

Structural integrity and durability of aircraft structure

Subject: Solid Mechanics
Lecturer: Zlatan Kapidzic, IEI
Time: 15:15-16:00 
Location: ACAS, A Building, Campus Valla


Structural strength, durability and damage tolerance are important issues for aircraft flight safety and economic life. To achieve and maintain adequate levels of these properties during the entire service life of the aircraft, the manufacturer performs a structural integrity assessment program. The program addresses all aspects that affect aircraft structural integrity, such as material properties, manufacturing, function, loading, operational conditions and maintenance. In this context, understanding the structural and material behavior under loading and the ability to predict them is essential. Traditionally, this knowledge has largely been based on experimental and development testing and today numerical simulations are increasingly used also. A large part of contemporary research is directed towards development of material modelling and simulation technique. As the requirements for light weight in aircraft structures continue to increase, so does the need to consider new materials and structural solutions and to understand their properties, function and the effects it has on service life and structural integrity. This lecture will give an outline of the aircraft structural integrity program and show some fatigue and damage tolerance related issues in fighter aircraft structure. Typical failure behavior of composite and metal will be presented and how they can be modelled in a hybrid, bolted and integrated structures. Some highlights of the resent research and an outlook towards the future trends will be given.


1 March 2023

Image synthesis and augmentation for data-centric machine learning

Subject: Visualization and Media Technology
Lecturer: Gabriel Eilertsen, ITN
Time: 15:30-16:15 
Location: K2, Kåkenhus, Campus Norrköping


Machine learning (ML), especially by means of deep learning, has made substantial progress over the last decade, e.g., for solving complex problems such as image classification, medical diagnosis, personalized recommendations, and natural language processing. However, the data-hungry nature of deep learning means that the full potential of a model is often inhibited by lack of data. Deep learning so far has to a large extent been model-centric, and the general view on data has been "more is better". In most situations there could be larger gains in improving the training data, in a data-centric formulation. In imaging applications, one promising technique for expanding and improving training data is through image synthesis. With the advancements of generative deep learning, there are many possibilities for data-centric ML in the intersection between computer graphics and deep generative modeling.

This lecture will introduce data-centric ML and image synthesis, and highlight some projects within computer vision and computer graphics where data has been in focus. This includes, e.g., data augmentation techniques for deep high dynamic range image reconstruction and for self-supervised learning, as well as deep generative modeling for data augmentation, anonymization, and anomaly detection. One of the main application areas has been medical imaging, and in particular digital pathology. Here, data-centricity and image synthesis is especially promising since data is expensive to capture, relies on medical expertise for annotation, and is of sensitive and protected nature.


Faculty of Science and Engineering