Welcome to the internal ISY pages

B-huset

The Department of Electrical Engineering (Institutionen för systemteknik, ISY) is central in our engineering programmes both for base knowledge and applied courses. The research is primarily focused on industrial needs and reaches from foundational questions to more application-centered issues.

Undergraduate education

The department offers more than 100 different courses within four undergraduate education areas: Images, Electronics, Automatic control, and Telecommunication. Within the university’s programs there are a number of specialisations coordinated by us.

Research

Research and research education is performed within the subject areas: Computer vision and learning systems, Electronics and computer engineering, Vehicular systems, Information coding, Communication systems och Automatic control.

Master’s thesis

Here you can read about how to find and finish a Master’s thesis with us.

Thesis defenses

  • 2026-09-10 kl 10:00 i Transformen

    Evaluation of Embedded Scalable Platforms (ESP) – A Case Study on RISC-V Processor and HLS Accelerator Integration

    Författare: Mari Jenn Barcebal Cabalquinto
    Opponent: Zihan Li
    Handledare: Abdolvahab Khalili Sadaghiani
    Examinator: Jose Nunez-Yanez
    Nivå: Avancerad (30hp)

    Modern heterogeneous system-on-chip (SoC) architectures increasingly combine
    general-purpose processors with specialized hardware accelerators. Frameworks such as
    the Embedded Scalable Platform (ESP) aim to simplify the development of such systems
    by providing reusable architectural components, standardized interfaces, and automated
    accelerator-integration mechanisms. However, the practical usability of the complete ESP
    development workflow depends not only on these architectural abstractions, but also on
    the surrounding development environment, external CAD tools, configuration procedures,
    and debugging process.
    This thesis evaluates ESP from a practical developer and system-integration perspective through an engineering case study. An ESP-based heterogeneous SoC was configured using an Ibex 32-bit RISC-V processor and a custom General Matrix Multiplication
    (GEMM) accelerator implemented using high-level synthesis (HLS).

  • 2026-09-10 kl 10:00 i Transformen

    Implementing a Graph Neural Network Accelerator on a Resource-Constrained FPGA – A Case Study on the Reliability of High-Level Synthesis Resource Estimates

    Författare: Zihan Li
    Opponent: Mari Jenn Barcebal Cabalquinto
    Handledare: Abdolvahab Khalili Sadaghiani
    Examinator: Jose Nunez-Yanez
    Nivå: Avancerad (30hp)

    Graph neural networks combine sparse, irregular aggregation over a graph’s edges
    with dense matrix multiplication, and FPGA accelerators for them are typically developed
    and evaluated on large, capable devices. This thesis ports one such accelerator, SGRACE,
    onto a substantially smaller one — the Zynq-7020 of a PYNQ-Z2 board — and determines
    whether a real FPGA implementation and bitstream can be produced there, and at what
    cost.

  • 2026-09-10 kl 15:15 i Stora Visionen

    Self-Supervised Learning for Repeat-Pass Sonar Imagery: A DINO-Based Approach

    Författare: August Gustafsson
    Handledare: Pavlo Melnyk
    Examinator: Leif Haglund
    Nivå: Avancerad (30hp)

  • 2026-09-11 kl 13:15 i Systemet

    Learning from Reality - Evaluating SABIM for Semantic 3D Segmentation on Buildings

    Författare: Alexander Josefsson
    Opponent: Nils Forssén
    Handledare: Bryan Adams
    Examinator: Per-Erik Forssén
    Nivå: Avancerad (30hp)

  • 2026-09-14 kl 10:15 i Systemet

    Single-bit Frequency Modulation Transmitter on an Altera FPGA Board

    Författare: Erik Håkansson, Hamza Keifo
    Handledare: Oscar Gustafsson
    Examinator: Anders Nilsson
    Nivå: Grundnivå (16hp)

  • 2026-09-14 kl 13:00 i Nollstället (ISY)

    Design of Ring Oscillator-Based Differential Capacitive Sensor for Life Science Application

    Författare: Ramkumar Paramasivam
    Opponent: Simon Eldridge
    Handledare: Saghi Forouhi
    Examinator: Alireza Saberkari
    Nivå: Avancerad (30hp)