TO REGISTER THIS COURSE - PLEASE FOLLOW THIS LINK - Reinforcement Learning and Dynamic Programming
The course will start from the basics of Bayesian learning, i.e., Bayes' theorem and it will focus on fundamenal concepts around the Baysiann treatment of the classical regression task. The power of the evidence function will be demonstrated, mainly via concepts and physical reasoning, and its reltaion to Occam's razor rule for adressing overfitting will be demonstrated. Then, the concept of latent variables and the EM algorith will be reviewed, with applications to regression, classification and clustering. Finally, extentions to the variational EM algortihm will be discussed with applications to regression and mixture modelling.
Organizer: Sergios Theodoridis
Lecturers: Sergios Theodoridis
ECTS: 1
Time: TBD in May
Place:
Zip code:
City:
Number of seats: 20
Deadline:
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 3.000 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.
FOLLOW THIS LINK TO REGISTER THIS COURSE: Quantum Information and Computing
During the last decade, small-scale quantum computers have emerged, with companies like IBM, Google and Microsoft as the frontrunners. The fundamental computational building block in quantum computing is the qubit. While millions of qubits are needed to outperform classical supercomputers, current state-of-the-art quantum computers only have hundreds of qubits available. However, with the rapid development in the field, we can expect this number to grow in the coming years and decades.
A quantum computer is no longer a dream and far-fetched future; it will be an accessible computing tool for computer scientists and engineers in the coming years. Therefore, the course will introduce the participants to the main concepts of quantum computing.
The course will cover the following subjects:
- Introduction to quantum computing and hardware,
- Bloch sphere, gates and circuits, introduction to Qiskit
- Quantum preliminaries, quantum algorithms
- Software stack and control stack
- Postulates of quantum mechanics, observable quantum operations, tensor products, measurements, partial trace
- Variational quantum algorithms
- Quantum communication,
- Quantum cryptography
Organizer: Rafal Wisniewski
Lecturers: Sven Karlson (DTU), Petar Popovski (AAU), and Rafal Wisniewski (AAU)
Number of seats: 40
ECTS: 3
Time:
5 - 9 June 2023
Deadline: 15 May 2023
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 3.000 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
Our future is envisioned to be filled with disruptive Internet of Things (IoT) applications that will revolutionize our everyday lives and also the industrial sector. However, these IoT applications present unique and widely different characteristics and traffic patterns that pose major challenges to the current wireless communications systems. Thus, to realize this ambitious vision, novel approaches to the design and optimization of wireless networking mechanisms are needed.
Specifically, it is envisioned that the wireless communications systems of the future will rely on recent advances on artificial intelligence (AI) and data-driven mechanisms to achieve self-optimization and self-adaptation capabilities. This four-day course provides a comprehensive review of:
(1) the technical and theoretical basis to design efficient access protocols for wireless IoT applications;
(2) the challenges and opportunities of IoT-enabling technologies;
(3) data-driven and machine learning techniques to enhance IoT connectivity; and
(4) novel communication architectures and infrastructures for the IoT.
Organizer: Israel Leyva-Mayorga
Lecturers: Israel Leyva-Mayorga, Cedomir Stefanovic, Jimmy J. Nielsen, Beatriz Soret, and Shasi Raj Pandei
ECTS: 3
Time: 6 - 9 November 2023
Place:
Zip code:
City:
Number of seats: 20
Deadline: 16 October 2023
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 3.000 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: Israel Leyva Mayorga
- Teacher: Jimmy Jessen Nielsen
- Teacher: Beatriz Soret
- Teacher: Cedomir Stefanovic
This course should provide the PhD candidates in the Wireless Communications program the necessary background on the physical aspects of radiowave communication.
The motivation follows the well-known fact that students in this program come from various backgrounds, often specialized in communication protocols and information theory, but lacking the necessary physical insight into electromagnetic fields, antennas and radiowave propagation. For the rest of the participants, this course should give a recapitulation of the previously acquired knowledge and extending it to meet the needs of their dissertation, as many of them will need to design an antenna and/or carry out electromagnetic simulations in their projects.
Both basic and advanced aspects of electromagnetic theory will be covered, together with numerical methods for solving electromagnetic fields at high frequencies. The course consists of total 12 hours of lectures divided in 4 days plus a mini-project of approx. 1 month duration supervised and evaluated by the lecturer. Criteria for assessment are attendance of the lectures and evaluation of the mini-project.
Organizer: Ondrej Franek
Lecturers: Ondrej Franek
ECTS: 3
Time: 20 - 23 March
9 - 12 October 2023
Place:
Zip code:
City:
Number of seats: 15
Deadline: 18 September 2023
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 3.000 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: Ondrej Franek
Graph Neural Networks (GNNs) are architectures for signal processing on graphs. GNNs explore the irregular structure of graph signals and exhibit superior performance in various wireless networks applications. This PhD course focuses on the fundamentals of and recent advances in graph learning as well as their application examples in wireless communications.
The focus will be on introduction to the concept of graph learning, representation of wireless networks as graph, application examples and provision of insights into latest development in graph learning to the students.
Organizer: Ramoni Adeogun
Lecturers: Ramoni Adeogun
ECTS: 2
Time: 22 - 23 May
Place:
Zip code:
City:
Number of seats: 20
Deadline: 1 May
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 3.000 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: Ramoni Ojekunle Adeogun
Wireless is identified as a major enabler of the Industry 4.0 vision. Factories of the future are indeed expected to replace the bulky wired control infrastructure with industrial wireless networks, aiming at supporting agile reconfiguration of production resources, non-linear production via usage of robot swarms, lean changeover; ultimately translating to major efficiency benefits and product customization. This course addresses how new wireless technologies can revolutionize the production paradigms in current factories and how to overcome the challenges that wireless communication encounters for achieving often demanding industrial requirements in terms of latency, reliability and throughput.
The main contents of the course are the following:
- Introduction of relevant industrial production use cases and associated communication requirements (considering the
multiple levels of the automation pyramid, from MES connectivity to fast closed loop control at sensor/actuator level) also
including new use cases that can only be enabled via wireless communication (e.g.,
robots fleets or swarms).
- Description of main candidate wireless technologies for Industry 4.0, with a critical analysis on their suitability in addressing
the communication requirements at different layers of the automation pyramid. In particular, 802.11 n/ac, 5G New Radio
(NR), 5G-Advanced for IIoT will be introduced.
- Introduction of open research challenges in a 6G perspective, including a vision for a new wireless system aiming at coping
with the more stringent Industry 4.0 use cases (e.g., support of closed loop control with below 0.1 ms cycles).
- From theory to practice: experimental verification of wireless technologies potential in a real industrial setup including
FESTO production lines and robot fleets, located in the 5G Smart Production Lab.
The course consists of frontal lectures, and laboratory sessions. Laboratory sessions will be structured as hands-on activities where PhD students have the opportunity of setting up their own wireless solutions for a real Industry 4.0 use case, verify their effects on the production, and identify the new open challenges.
The evaluation will be based on mini-projects to be carried out in groups. Such mini-projects may involve the usage of laboratory facilities.Organizer: Gilberto Berardinelli
Lecturers: Associate Professor Gilberto Berardinelli, Professor Ole Madsen, Postdoc Melisa Maria Lopez Lechuga
ECTS: 2
Time: Fall 2023, e.g. October 2023
Place:
Zip code:
City:
Number of seats: 10-30
Deadline:
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 3.000 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: Gilberto Berardinelli
- Teacher: Melisa Maria Lopez Lechuga
- Teacher: Ole Madsen