Record number of new Doctors and Licentiates

Fri 10 Sep 11:59

A record number of doctoral students at STC presented their theses in the spring of 2021. We are proud to introduce six new doctors and four new licentiates.

Images of all new phc anc licentiates during spring 2021

Doctoral theses


Dr. Xinyu Ma
"Power Estimation for Indoor Light Energy Harvesting /Harvest energy from indoor lights"

The growing popularity of indoor light energy harvesting for wireless sensor systems and low-power electronics has created a demand for systematic power estimation methods for different lighting conditions.

Xinyu Ma’s study provides new insights into the indoor light energy harvesting system design and makes a contribution to research on available energy estimation of the ambient environment.

Watch Xinyus presentation

Read the thesis: Power Estimation for Indoor Light Energy Harvesting

 

Dr. Stefan Haller
"Towards Low-Voltage High-Current − A pioneering drive concept for battery electric vehicles"

The first electric low-voltage vehicles were constructed in the mid-19th century, but by the early 20th century they were progressively replaced by successors with internal combustion engines. As the consequences of using fossil fuels are better understood, our society is now transitioning back. The strong driving force towards electric transportation can be traced to several events and trends. The foremost of these is perhaps the rising awareness of climate change and the necessary reduction of the environmental footprint, as well associated political will for change.

Stefan Haller’s thesis provides an introduction to low-voltage, high-current, battery-powered traction drives. With the aim of increasing efficiency, safety and redundancy while reducing cost, a solution that breaks with century-old electric machine design principles is proposed and investigated.

Watch Stefans presentation

Read the thesis: Towards Low-Voltage, High-Current: A pioneering drive concept for battery electric vehicles

 

Dr. Javier Aranda
"Towards Self-Powered Devices Via Pressure Fluctuation Energy Harvesting"

The growing interest in the Internet of Things has created a need for wireless sensing systems for industrial and consumer applications. In hydraulic systems, a widely used method of power transmission in industry, wireless condition monitoring can lead to reduced maintenance costs and increase the capacity for sensor deployment.

The results of Javier Aranda’s work provide new insights into the development of power supplies for self-powered sensors for hydraulic systems using pressure fluctuation energy harvesters.

Watch Javier's presentation

Read the thesis: Towards Self-Powered Devices Via Pressure Fluctuation Energy Harvesting

 

Dr. Waqas Ahmad
"High Efficiency Light Field Image Compression - Hierarchical Bit Allocation and Shearlet-based View Interpolation"

Over the years, the pursuit of capturing the precise visual information of a scene has resulted in various enhancements in digital camera technology, such as high dynamic range, extended depth of field, and high resolution. However, traditional digital cameras only capture the spatial information of the scene and cannot provide an immersive presentation of it.

In Waqas Ahmad’s thesis, compression of LF data captured using a plenoptic camera andmulti-camera system (MCS) is considered.

Watch Waqas presentation

Read the thesis: High Efficiency Light Field Image Compression - Hierarchical Bit Allocation and Shearlet-based View Interpolation

 

Dr. Irida Shallari
"Intelligent Partitioning of IoT - Design Space Exploration for a Data Intensive IoT Node"

The technological shift towards the Internet of Everything has resulted in an ever-increasing interest in smart sensor nodes. The required deployment of these nodes in a variety of environments, powered by constrained energy sources such as energy harvester or conventional batteries, is reflected in the significant constraints in terms of energy consumption for the smart sensor node.

Furthermore, the range of applications is expanding, and the processing complexity is subsequently growing, resulting in high data volume and energy constrained IoT nodes. The aim of Irida Shallari’s thesis is to address the energy efficiency of these smart sensor nodes and enhance their design process, which would inherently shorten their time-to-market.

Watch Irida's presentation

Read the thesis: Intelligent Partitioning of IoT - Design Space Exploration for a Data Intensive IoT Node

 

Dr. Elijs Dima
"Augmented Telepresence based on Multi-Camera Systems: Capture, Transmission, Rendering, and User Experience"

Observation and understanding of the world through digital sensors are an ever-increasing part of modern life. Systems of multiple sensors acting together have far-reaching applications in automation, entertainment, surveillance, remote machine control, and robotic self-navigation.

The purpose of Eljis Dima’s work is to gain a more comprehensive understanding of how multi-sensor systems lead to Augmented Telepresence, and how Augmented Telepresence can be utilized for industry-related applications.

Watch Elijs presentation

Read the thesis: Augmented Telepresence based on Multi-Camera Systems: Capture, Transmission, Rendering, and User Experience

 

Licentiate theses


Tech Lic. Yali Nie
"Automatic Melanoma Diagnosis in Dermoscopic imaging based on a Deep Learning System"

Melanoma is one of the deadliest forms of cancer. Unfortunately, its incidence rates have been increasing all over the world. One of the techniques used by dermatologists to diagnose melanomas is an imaging modality called dermoscopy. The skin lesion is inspected using a magnification device and a light source. This technique makes it possible for the dermatologist to observe subcutaneous structures that would be invisible otherwise.

Yali Nie’s thesis provides an overview of our deep learning (DL) based methods used in the diagnosis of melanoma in dermoscopy images.

Watch Yali's presentation

Read the thesis: Automatic Melanoma Diagnosis in Dermoscopic imaging based on a Deep Learning System

 

Tech. Lic. Javier Brugés
"Surface characterization methods for quality assessment of polyethylene-coated paperboard"

In manufacturing processes, the quality of a product often depends on its surface, and careful control of surface properties is critical to meet customer requirements.

The overall goal of Javier Brugés thesis is to provide new methods to characterize the surface properties of PE-coated paperboard. Specifically, to determine imaging techniques for measuring surface parameters that affect its barrier functionality and surface roughness.

Hur påverkar barriärfunktionalitet och ytjämnhet en produkts kvalitet?

I tillverkningsprocesser beror kvaliteten på en produkt ofta på dess yta, och noggrann kontroll av ytegenskaper är avgörande för att möta kundernas krav.

Det övergripande målet med Javier Brugés licentiatavhandling är att ta fram nya metoder för att karakterisera ytegenskaperna hos PE-belagd kartong. Specifikt, för att bestämma bildtekniker för att mäta ytparametrar som påverkar dess barriärfunktionalitet och ytjämnhet.

Watch Javier's presentation

Read the thesis: Surface characterization methods for quality assessment of polyethylene-coated paperboard

 

Tech. Lic. Johannes Lindén
"Extracting Text into Meta-Data - Improving machine text-understanding of news-media articles"

Society is constantly in need of information. It is important to consume event-based information of what is happening around us as well as facts and knowledge. As society grows, the amount of information to consume grows with it. Johannes Lindén’s thesis demonstrates one way to extract and represent knowledge from text in a machine-readable way for news media articles.

Watch Johannes presentation

Read the thesis: Extracting Text into Meta-Data - Improving machine text-understanding of news-media articles