Doctoral Symposium

Apart from the submission of regular papers above, we solicit submissions to the Doctoral Symposium of the conference, which will be held on Sept. 23rd or 24th 2024. The Doctoral Symposium will offer PhD students a unique opportunity to present their work, to connect to fellow PhD students working on similar topics, and to get feedback both from other PhD students and senior reseachers in AI.

Addressing the needs of doctoral students at different stages of their studies, we invite three different types of submissions:

1. Thesis Proposals (max. 6 pages excl. references)

Thesis Proposal Papers summarize the research question addressed in your PhD project, clarify the identified research gap in the context of related works and outline the approach by which you want to address them. Focussing on the presentation of research questions and methodological approach, for this type of submission it is not necessary to already have experimental results. Hence, Thesis Proposal Papers are a great way for early-stage PhD students to get feedback on their research project during the first phase of planning and orientation.

2. Preliminary Result Communications (max. 6 pages excl. references)

Preliminary Result Communications summarize results of early-stage research projects, independent of whether these results meet the relevance criteria of traditional publication venues. The focus of these submissions is to objectively report which question has been addressed, which methods have been applied, and what were the empirical or experimental results obtained. Papers communicating results of experiments that did not yield the expected results or methods that did not work as planned are particularly welcome.

3. MSc Thesis Papers (max. 4 pages excl. references)

We finally welcome submissions by MSc students who are about to finish or have recently finished their thesis and actively look for potential PhD positions. Such participants may submit a summary of their thesis results as well as a brief research statement summarizing follow-up questions and research interests that could be addressed during a PhD.

For all submission types, the focus of the doctoral symposium will be to provide a safe, friendly and constructive space in which participants can openly exchange experiences and get advice on potential next steps in their research and their career. Submissions should be max. 6 pages excl. references (4 pages for MSc thesis papers) with optional unlimited supplementary information. Accepted submissions will be considered non-archival, i.e. accepted works will not be published in the conference proceedings. Due to the preliminary status of results, members of the program committee will be specially sensitized to respect strict confidentiality.

Submissions shall be made via EasyChair via the following link:

Submit

All Authors of accepted submissions are expected to present their work in a talk that will be held in presence on Sept. 23rd or 24th 2024. Authors can opt-in to have their talk and the Q&A recorded, where the recording will only be made available to the presenters themselves to critically reflect on presentation skills and to identify potential for improvement.

The symposium will include a panel comprised of junior and senior scientists that addresses general issues relevant to PhD students, such as work-life balance, mental health, academic publishing in AI, and career planning.

• Submission Deadline:    July 19th, 2024
• Notification:                     August 2nd, 2024

The Doctoral Symposium will take place on Monday the 23rd in SE I in the computer science building (M2).

Session 1: 14:00 - 15:30

• 14:00 - 14:20 Welcome and Opening Statement
• 14:20 - 14:40 Explainable Artificial Intelligence and Reasoning in the Context of Large Neural Network Models (Thesis Proposal), Stefanie Krause
• 14:40 - 15:00 A Neuro-Symbolic Approach for Deep Anomaly Detection (Thesis Proposal), Konstantin Kirchheim
• 15:00 - 15:20 Explainable Artificial Intelligence Methods for Audio Classification Tasks: Combining Symbolic Rules and Example-based Explanations (Thesis Proposal), Judith Knoblach

Coffee Break: 15:30 - 16:00

Session 2: 16:00 - 17:30

• 16:00 - 16:20: Early Multimodal Data Integration for Medical AI Applications (Thesis Proposal), Julia Gehrmann
• 16:20 - 16:40 Dynamic Difficulty Adjustment in Games through Exhaustive Reinforcement Learning (Thesis Proposal), Johannes Büttner
• 16:40 - 17:00 On Meta-Model Based Uncertainty Estimation in Deep Learning (Thesis Proposal), Venkatesh Thirugnana Sambandham
• 17:00 - 17:20 Guided LLM Reasoning for Knowledge Graph Completion (Thesis Proposal), Jonas Kaiser
• 17:20 - 17:30 Closing Statement