10th TMA PhD School
Network Intelligence and Measurements
Following the success of the previous editions and after the interruption due to the COVID pandemic, the 10th TMA PhD School will take place on June 27th and 28th 2022 in Enschede, The Netherlands. Under the theme Network Intelligence and Measurements, the 10th TMA PhD School will include 4 tutorials, by 5 distinct lecturers, over a 2 days program. Lectures are accompanied by related practical lab sessions, where students have the opportunity to put into practice learned notions.
The detailed program of TMA PhD School with bios and abstracts will be available soon.
PhD School Speakers
The list of speakers for the 10th TMA PhD school includes:
Anna Brunström is a Full Professor and Research Manager for the Distributed Systems and Communications Research Group at Karlstad University. She will familiarize the students with experimentation and measurements methodologies for next generation mobile networks, based on her vast experience on applied research projects such as H2020 MONROE, NEAT and 5GENESIS. The students will also get an opportunity for hands-on examination of a mobile network data set.
Emile Aben is a System architect at the RIPE NCC, Netherlands. The lecture will provide an overview of the RIPE RIS Internet data collection system and what it is useful for. The lecturer will demo the interfaces available for the data, and the students will do hands-on experiments that will help with the detection of interesting routing artefacts using this data.
Thymen Wabeke and Thijs van den Hout are research engineers with SIDN Labs (.nl registry). They research how machine learning (ML) applications can increase the security of the internet and the Domain Name System (DNS). The lecture will focus on operationalizing a ML model. There are several challenges involved in this process, such as efficiently collecting ground truth labels, analysts needing to understand model inferences, and monitoring model performance so you know when it fails and needs updating. The lecture will include a hands-on training, so that participants can try out some techniques immediately.
Pedro Casas is a Senior Scientist at the Austrian Institute of Technology, where he acts as Research Lead in AI4NETS (AI/ML for Networking). He will present a broad overview on the application of AI/ML to network data analysis problems, including network security, anomaly detection, and Quality of Experience (QoE) monitoring. The lecture “DEEP in the NET: Deep Learning for Network Monitoring and Analysis” provides an introduction to the basics of AI/ML, going from more traditional applications to newer paradigms, including deep learning, graph-based learning, generative models, explainable AI, and more. The ultimate goal of the lecture is to motivate – for the newcomers, and to strengthen – for those already in the field, the research in AI4NETS.
Poster Sessions and Best Poster Award
The PhD School program will include 4 poster sessions where students can present their own (ongoing) PhD work to other students and to the lecturers, and receive individual feedback from them. Poster sessions will take place during breaks.
The program will also include an informal interactive session between students and the speakers, with the explicit goal of fostering “vertical” interaction between students and the speakers, and “horizontal” interaction between the students themselves. Students will have the opportunity to interview the speakers, asking for their expert opinion on general aspects (non-technical) of the current research dynamics in the field of traffic monitoring and analysis (e.g., how they see the prospective development of a particular research topic in the near future, or what are the key ingredients that drive the success of an experimental measurement platform, etc).
The PhD school program will include social activities on both days, where students, lecturers and attendees of the main TMA conference will have the opportunity to interact informally. A social dinner would be organized on the second day.
The three winners of the PhD School Best Poster and Presentation Award are:
- Katharina Dietz: Towards Synthesizing Communication Network Topologies via GANs
- Aniketh Girish: ImposTer: Towards an Extensible Privacy Analysis framework for Smart home ecosystem
- Joël Ky: Characterization and Troubleshooting of cloud gaming applications on mobile platforms
Registrations are now closed. The maximum number of participants has been met.
As the PhD school is popular, we encourage students to register early. Our goal is to admit as many students as possible but we do note that we have limited room availability. The maximum number of participants will be limited to 40.
Application deadline: April 25th at 23:59 CEST
Tentative decision notification: April 29th
How to apply and Travel Grants
The price for registration for the TMA 2022 PhD school will be fixed soon. This fee will be levied on all attending students, also those receiving travel grants (see below), as the travel grant rules from our sponsors require us to ask for a small own investment. Registration fee would be below 250 Euro.
In order to apply, please submit the following as a single PDF document:
the title and abstract of your poster (in the fields required by the submissions system)
a current CV with contact information and e-mail address
a short personal statement, including: i) a description of the research subject followed by the student, and (ii) information that the applicant feels is relevant to support his/her application, e.g., why the PhD School attendance is important to the applicant’s research and career development;
In case you also want to apply for optional travel support, we ask you to also include:
a letter from your advisor which should: (i) confirm the applicant’s good standing in the institution; (ii) explain why the applicant would benefit from attending the TMA PhD School
the estimated expenses for attending the TMA PhD School (total, and breakdown by travel and lodging), and an indication of which cost items would need to be covered by the grant; if the applicant will be unable to attend the school without a travel grant, they should explain why this is the case (in this case the advisor’s letter should additionally explain the current funding status of the applicant and why the applicant is in need of the travel grant);
The organization will prioritize awarding of travel grants to students who will be unable to attend without a grant, and additionally based on diversity and the region from which the applicant has to travel, to ensure representation from traditionally underrepresented regions. In special cases, where the registration fee is also prohibitive, the organization may decide to waive the fee at its discretion.
Any decision made by the organization regarding attendance and awarding of travel grants is final. We note that reimbursements of travel grants may take up to several months to complete.
Please pay attention to the following details about the student travel grant application and reimbursement process:
The School will admit a limited number of students.
Students enrolled in PhD study programs will receive preference both in the admission to the School and the travel grant awarding.
- Students admitted to the school are encouraged to attend the TMA conference.
We expect a student travel grant will significantly offset air fare and shared hotel accommodation. However, it may not fully cover these expenses, since our desire is to maximize participation by students.
In order to obtain reimbursement, you must provide original receipts for air fare and hotel expenses, along with boarding passes (plane or train) for both outbound and inbound journeys.
All students participating in the School are required to present a poster describing their research and to actively engage with all activities. Failing to do so will lead to admission rejection.
- Please provide complete contact information. You will be notified via email, so make sure your email address is correct on your application.
The PhD School and the Travel Grants are gently supported by: