Welcome to Cyber security
Organizer: Rasmus Løvenstein Olsen
Lecturers: Jens Myrup Pedersen, Rafal Wisniewski, Jaron Skovsted Gundersen
ECTS: 3
Date/Time:
26/2: Kroghsstræde 3 – lokale 4.128
28/2
4/3
5/3
Deadline: 5 February 2024
Max no. Of participants: 40
Venue: TBA
Description: Typical attacks on critical infrastructures: How hackers can abuse the Internet of Things, and how attacks can be prevented and detected. In the course, we will introduce you to cyber security and the most important cyber security threats. You will learn about different vulnerabilities and how they can be mitigated, focusing on a very hands-on session where you will be able to play around with vulnerabilities in virtual labs. Further focus will be on discuss public-key cryptosystems, which are widely used for secure data transmission. Public key cryptography aims at solving the problem of how two parties can communicate securely when they have not agreed on some secret common key, which is often the case in for example communication through the internet. It includes both public-key encryption, which guarantees the secrecy of a message, and digital signatures, which provide authentication and integrity. We will introduce some of the more classical, but still widely used, public-key cryptosystems, such RSA and El Gamal/ Diffie-Hellman and we will discuss which security properties are usually required from them nowadays. Subsequently, we will investigate the problem of secret sharing and secure multi-party computation. Secret sharing is about how to share a secret among a number of parties in such a way that the individual parties does not learn the secret. Secure multi-party computation studies how to ""compute on encrypted data"": how several mutually distrustful parties can collaborate to jointly perform computations involving private data without needing to actually reveal their private information to others. We will show how to develop secure optimization algorithms. Finally we will also address network and the type of analysis used to asses network security where we study some cases.
Prerequisites: Calculus, programming skills, network and computer knowledge
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Jaron Skovsted Gundersen
- Teacher: Rasmus Løvenstein Olsen
- Teacher: Jens Myrup Pedersen
- Teacher: Rafal Wisniewski
Welcome to Methods for data collection with human subjects
Organizer: Rodrigo Ordoñez
Lecturers: Rodrigo Ordoñez and others.
ECTS: 3
Date/Time: 14,15 March & 16,17 May 2024
Deadline: 22 February 2024
Max no. Of participants: 20
Description: Much of technical scientific research has as an ultimate goal to develop technological devices that will be used by people. Either as services, or products that may end up being an integral part of peoples’ lives. In order to investigate if a given technology can be used in a given context, experiments with human subjects are indispensable. These types of experiments can be time consuming and expensive and if not properly designed and executed the results may not be reliable.
This course takes both a theoretical and practical approach to data collection from human subjects, in order to avoid mistakes and common pitfalls while improving the reliability of the results. From an understanding of cognitive and perceptual processes of human interaction with the environment, we will investigate implications of these processes in different data collection scenarios.
The scenarios presented will be based on research activities, for example:
1. Evaluation of sound environments and interactive control.
2. Hearing aid aided performance ratings.
3. Listening effort
The course consist of lectures and practical work, where you will design and participate in experiments.
Prerequisites: Knowledge of basic data analysis models, such as CHI-square, T-tests, ANOVA is an advantage, but not strictly required. Programming in any language capable of making simple user interfaces and data analysis, such as Python or Matlab.
Course participants should have plans to run a data collection experiment with human subjects during their PhD work.
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Rodrigo Ordoñez
Welcome to Self-Supervised Learning
Organizer: Zheng-Hua Tan
Lecturers: Zheng-Hua Tan
ECTS: 2
Date/Time: November 18-20, 2024
Deadline: 28 October 2024
Max no. Of participants: 50
Description: The course gives an introduction to self-supervised learning methods for learning representations of single- and multiple-modality data, covering deep architectures, training target and loss functions used in state-of-the-art methods, and selected downstream applications. A focus will be given to loss functions including both contrastive and predictive losses.
Prerequisites: Knowledge in machine learning or deep learning and basic skills in Python programming
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Zheng-Hua Tan
Welcome to Linear Matrix Inequalities in Control
Organizer: John Leth
Lecturers: John Leth, Jan Dimon Bendtsen
ECTS: 2
Date/Time: 18, 19, 20, 21, 22 November 2024
Deadline: 21 Oktober 2024
Max no. Of participants: 50
Description: In this course we will introduce the notion of a Linear Matrix Inequalities (LMI) and explore how this concept can be used for establishing tangible numerical methods for stability and performance of controlled dynamical systems. Stability is the most basic requirement for any controlled dynamical systems - if the closed loop system is perturbed by bounded disturbances, all internal states should remain bounded and eventually converge back to zero if the system is left alone. Once stability is established, one can ask for 'fast transient response', 'disturbance rejection' or similar; these are notions of performance. Stability will in this course be studied through the concept of dissipativity, which is a very fundamental system theoretical feature that relates to the dissipation of (kinetic) energy over time via friction. This is a reference to the classical mechanics-based concept of macroscopic systems such as rigid bodies 'slowing down' in the presence of e.g. air resistance, which in turn helps defining the notion of stability.
Prerequisites: A basic knowledge of mathematics and control theory as obtained through undergraduate engineering studies.
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Jan Dimon Bendtsen
Welcome to the 2024 CASPR Course on Acoustic Signal Processing for Hearing Assistive Devices
ECTS: 3
Date/Time: Monday 26th, February to Friday 1st, March, 2024.
Note: This is a one week (5 full days) course with mandatory physical presence. Reading material will be distributed before the course. A course assignment must be handed in after the course.
Place: AAU Copenhagen campus.
Deadline: 9 February 2024
Max no. Of participants: 25
Organizers:
- Prof. Jesper Jensen, Aalborg University and Oticon
- Prof. Jan Østergaard, Aalborg University.
- Prof. Zheng-Hua Tan, Aalborg University.
Lecturers:
- Prof. Steven van de Par, Oldenburg University
- Prof. Jesper Jensen, Aalborg University and Oticon
- Prof. Zheng-Hua Tan, Aalborg University
- Dr. Meng Guo, Oticon.
- Dr. Robert Rehr, Oticon.
- Dr. Michael Syskind Pedersen, Oticon.
- Dr. Dorothea Wendt, Eriksholm Research Center.
- PhD student Vasudha Sathyapriyan, Aalborg University and Oticon
- Ph.D student Payam Shahsavari, Aalborg University
- Ph.D student Andreas Fuglsig, Aalborg University
- Ph.D student Peter Leer Bysted, Aalborg University
- Ph.D student Philippe Gonzalez , Technical University of Denmark
- Ph.D student Asjid Tanveer, Aalborg University
- Ph.D student Sangeeth G. Jayaprakash, Aalborg University
- Ph.D student Holger S. Bovbjerg, Aalborg University
- Ph.D student Mohammad Bokaei, Aalborg University
Description:
Hearing assistive devices (HADs) are ubiquitous. They include, for example, devices such as headsets for speech communication in noisy environments (airplane crews, emergency/rescue teams, combat soldiers, police forces, etc.), headsets for office use, gaming, etc., and hearing care systems, e.g., hearing aids and cochlear implants.
The course consists of lectures and hands-on exercises, allowing the participants to understand in-depth the technical problems related to HADs and their potential solutions. The course is multi-disciplinary, focusing on applying theoretical results to real-world problems and practical do's and don'ts.
Course content
The course has three main parts.
The first part is a short introductory part, which lays the foundation for the rest of the course, covering fundamental topics such as auditory perception (normal and impaired hearing) and a discussion of the basic principles of HADs.
The second part provides an overview of fundamental signal processing problems encountered in HADs, and an in-depth treatment of state-of-the-art solutions. These include methods for beamforming and noise reduction, direction-of-arrival estimation, voice activity detection, feedback control, hearing loss compensation, etc. Furthermore, an overview is given of important methodologies for evaluating HADs in particular related to speech intelligibility and listening effort.
The third part of the course presents emerging technologies for HADs.
While the course focuses on HAD applications, many of the discussed techniques are general and find use in the much broader field of general sound processing.
The course also bridges the gap between theoretical background and practical/robust application.
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Jesper Jensen
- Teacher: Jan Østergaard