PhD Thesis Defenses

PhD thesis defenses are a public affair and open to anyone who is interested. Attending them is a great way to get to know the work going on by your peers in the various research groups. On this page you will find a list of upcoming and past defense talks.

Please go here for electronic access to most of the doctoral dissertations from Saarbrücken Computer Science going back to about 1990.

February

Till Schlüter
Systematic Characterization, Exploitation, and Protection of Microarchitectural Features
(Advisor: Dr. Nils Ole Tippenhauer)
Tuesday, 10.02.26, 10:00, building E9 1, room 0.01

Modern digital infrastructure relies on fast, efficient processors. To achieve high performance, CPUs incorporate proprietary microarchitectural optimization features. These features, however, can inadvertently introduce security vulnerabilities that compromise fundamental platform guarantees. We examine microarchitectural features from three perspectives: characterization, exploitation, and protection. We develop novel methods to characterize security-critical microarchitectural properties, including the Leakage Template, an abstract representation of a side channel. We propose how Leakage Templates can be created and utilized to find instances of the channel they describe in real programs.We also design FetchBench, a framework for characterizing hardware prefetching mechanisms. Using FetchBench, we uncover an unknown Spatial Memory Streaming (SMS) prefetch-er implementation in a commercial processor and show how it can be exploited to leak secrets across privilege domains. On the defensive side, we design and implement PreFence, an efficient mitigation against prefetching-based attacks that selectively disables prefetchers during security-critical code execution. Finally, we systematize defenses against attacks on microarchitectural features by analyzing academic and non-academic literature. We point out a bias towards the x86_64 architecture and identify gaps where no defenses are proposed against the attacks we consider.

Pascal Hennen
An Empirical Evaluation of Messy BGP Data Sources
(Advisor: Prof. Anja Feldmann)
Monday, 09.02.26, 15:00, building E1 4, room 0.24

The Internet is the world’s largest human-build system and as such evolved to be rather complex. Operators use the Border Gateway Protocol (BGP)—the Internet’s de-facto inter-AS routing protocol—to enable global connectivity. However, routing on the Internet is evolving. Although the specification of BGP has not changed since decades, its additions and usage patterns have. Thus, BGP has become an important topic to study for researchers. They use BGP data to, e.g., understand routing decisions, map the Internet’s topology, and improve security. Each AS uses BGP to realize its routing policies based on the business agreements that they have with its neighboring ASes. ASes typically do not share their business agreements publicly. Yet, ASes need to see the effects of a change in their BGP configuration. Route collector projects such as RouteViews and RIPE’s Routing Information Service (RIS) collect BGP data from as many ASes as possible and make that data publicly available in BGP archives. In addition, data broker services provide interfaces to these BGP archives. Whereas operators use this data to optimize their networks, researchers frequently use this data to study and understand the routing ecosystem. Until now the consistency and reliability of these data sources was usually assumed to be a given. However, it is not. In this dissertation, we fill this gap by investigating the temporal consistency (are routes recorded when they should be) and internal consistency (are routes recorded correctly). Furthermore, we evaluate whether a popular BGP route collector data broker (BGPStream’s broker) reliably returns all data files according to supplied search terms.
As a policy-based protocol, BGP is implemented on the border routers of ASes. A border router maintains multiple BGP sessions and selects the best route for a prefix by evaluating all learned routes. This is done via BGP attributes. Adjusting these BGP attributes and/or filtering routes allows an AS to implement its routing policies and manage its relationships with other networks. It is commonly assumed that ASes use the same BGP policies for all sessions with the same neighbor AS, preferring the same next-hop AS for the same prefix. In this dissertation, we show that this is often not the case—we refer to such ASes as being heterogeneous. We propose two inference methods to (i) quantify the number of heterogeneous ASes as observed by the route collectors, and (ii) identify ASes which explicitly diverge from the conventional BGP behavior. Route collectors yield a public view of the Internet—they do not show privately assigned BGP attributes. Thus, ASes collaborate with each other and operate publicly accessible Looking Glasses (LGs).
LGs are websites that allow other operators to perform queries on a subset of routers within the ASes to gather routing information. In this dissertation, we collect a LG dataset that focuses on collecting BGP attributes from more than 149 LGs in 154 ASes from 931 routers via scraping LGs. Hereby, the difficulties relate to the non-uniformity of the LGs—most interfaces differ, the fluctuating accessibility of the LGs, as well as the different output formats. To overcome this we combined manual configuration with an automated scraping process followed by careful post-processing and manual checks.

Sebastian Schirmer
Specifying Monitors for Autonomous Cyber-Physical Systems
(Advisor: Prof. Bernd Finkbeiner, now Munich)
Friday, 06.02.26, 16:00, building E1 1, room 407

In this thesis, we investigate and apply specification-based monitoring for autonomous cyber-physical systems, such as unmanned aerial vehicles (UAV). The aim is to support development and ensure safe and correct operation.
First, we show how aviation safety documents map to monitoring and how system behaviors are formalized. In particular, we propose temporal behavior trees (TBT), which build upon the widely used Behavior Tree (BT) framework for robotic task execution by combining it with temporal languages. TBTs provide a modular structure for decomposing complex tasks and enable retrofitting monitoring into applications that use BT.
Second, we present offline monitoring algorithms that analyze system log files post-execution. We introduce trace segmentation that splits the trace into segments and assigns them portions of the specification. This helps to understand which parts of the specification are violated and require further development. We then propose trace repair that minimally modifies a trace that violates its specification so that it satisfies it. Our experiments include an autonomous landing of a UAV on a ship and demonstrate their practical use.
Last, we present tools for online monitoring that ease the integration of specified monitors and validate these monitors in real-world flight tests. The results confirm the effectiveness of our specified monitors in safeguarding both machine learning components and UAV operations.

Philipp Christmann
Question Answering over Heterogeneous Sources
(Advisors: Prof. Gerhard Weikum  & Dr. Rishiraj Saha Roy)
Friday, 06.02.26, 10:00, building E1 4, room 0.24

Question answering (QA) systems provide crisp answers to questions posed by end users. Most existing QA systems rely on a single type of information source for answering: either a curated knowledge base (KB), or a text corpus, or a set of web tables, which limits their answer coverage.
This dissertation makes the following salient contributions:
(i) Proposing a general 3-stage architecture for answering questions over heterogeneous sources to improve answer coverage.
(ii) Developing end-to-end QA systems for conversational questions with incomplete intent, temporal questions with implicit or explicit time constraints, and complex questions that involve aggregation, grouping and joining of information from different sources.
(iii) Constructing large-scale benchmarks for conversational, temporal, and complex QA, as well as QA over personal data, which require the integration of heterogeneous sources.
By design, answers obtained by our QA systems can be traced back to the underlying evidence, and the approaches build upon small-scale language models for computational efficiency.

Magdalena Theresa Kaiser
Reinforcement Learning from Implicit Feedback for Conversational Question Answering
(Advisors: Prof. Gerhard Weikum  & Dr. Rishiraj Saha Roy)
Wednesday, 04.02.26, 10:00, building E1 4, room 0.24

Conversational systems that enable interactions with users in natural language to satisfy their information needs and assist them in completing their tasks have been a long-standing goal. Recent advancements in Machine Learning and Natural Language Processing have enabled the development of such systems. Feedback is essential to continuously improve and adapt these systems to users’ needs. This thesis focuses on Conversational Question Answering (ConvQA), where the task is to provide crisp answers to fact-centric questions, formulated in natural language. ConvQA models are usually trained and evaluated on benchmarks of gold-standard question-answer pairs. Manually judging answer correctness is costly and therefore often not available in real-world scenarios. If available, these judgments are often limited in scope and quality. This thesis studies forms of implicit feedback to effectively train and improve conversational systems from limited amounts of data.

January

Linjie Lyu
Global Illumination in Inverse Rendering: From Probabilistic Reconstruction to Generative Editing
(Advisor: Prof. Christian Theobalt)
Friday, 16.01.26, 16:00, building E1 4, room 0.24

Reconstructing geometry, materials, and lighting from images – known as inverse rendering – is a central problem in computer graphics and vision. A key difficulty lies in accurately modeling global illumination effects such as shadows, reflections, and color bleeding, which are essential for realistic scene understanding but challenging to infer from limited visual observations.
This thesis advances inverse rendering by explicitly accounting for global illumination while addressing two fundamental challenges: ambiguity in reconstructing 3D scenes from images, and the high computational cost of simulating light transport. To handle ambiguity, we introduce probabilistic inverse rendering frameworks that represent multiple plausible scene interpretations, enabling uncertainty-aware reconstruction and principled strategies for image acquisition. To improve efficiency, we develop differentiable rendering techniques that approximate complex light transport, including fast soft shadow computation and neural representations that enable efficient relighting under unknown illumination.
In addition, we explore diffusion-based generative models as complementary priors for global-illumination-aware image decomposition and editing, enabling semantic manipulation of lighting and materials without full 3D reconstruction.
Together, these contributions form a unified framework for scalable and robust inverse rendering in complex environments. By combining physical mo-deling, uncertainty reasoning, and generative priors, this work enables more reliable scene reconstruction and editing, with applications in 3D content creation, visual effects, and augmented reality.

Mallikarjun BR
Monocular face reconstruction and editing using priors learned from 2D data
(Advisor: Prof. Christian Theobalt)
Tuesday, 13.01.26, 09:00, building E1 5, room 0.02

Digital facial models equipped with semantic editing capabilities play a pivotal role across various domains such as film, gaming, telepresence, and social media. Conventionally, digital modeling involved representing both geometric and appearance properties, with the ability to semantically edit expressions and appearances in response to scene illumination changes and facial part alterations. Traditionally, achieving this level of fidelity necessitated costly setups like multi-view and light-stage rigs, limiting accessibility due to physical and financial constraints. Consequently, methods that require just a single monocular image offer substantial practical advantages, albeit facing the challenge of being under-constrained. To address this challenge, methods often rely on prior models, such as 3D Morphable Models (3DMM), constructed from a collection of 3D scans. However, acquiring large-scale 3D scans poses its own set of challenges, thereby limiting the quality of the prior model based on available data. In this thesis, a novel approach is proposed to learn a 3DMM model directly from extensive unstructured video and image datasets. Furthermore, existing methods typically approximate skin as a diffuse surface, failing to accurately capture photo-realistic appearance, particularly under complex illumination conditions involving diffuse, specular, subsurface scattering, self-shadows, and inter-reflections. To address this limitation, a new neural representation is proposed to estimate intricate illumination effects. Additionally, while modeling facial appearance, it’s crucial to account for non-facial regions like hair and neck. This thesis introduces a method leveraging a pre-trained 2D Generative Adversarial Network (GAN) to synthesize novel views and illumination, ensuring comprehensive modeling of these regions. Facial structures encompass various semantic parts like hair, eyes, and eyebrows. Existing methods often overlook certain parts or use a unified representation, hindering specific part-editing tasks. To overcome this, a compositional generative model is proposed, treating each part as a distinct entity. Efficient and photorealistic models are essential for wide-spread adoption. Thus, this thesis proposes an efficient 3D generative model capable of real-time sampling and rendering. Moreover, this model offers dense 3D correspondenc-es between samples, enhancing its utility for downstream applications. Lastly, the thesis provides an outlook on future research directions for each sub-problem addressed herein.

Vagrant Gautam
Fair and Faithful Processing of Referring Expressions in English
(Advisor: Prof. Dietrich Klakow)
Friday, 09.01.26, 15:00, building C7 4, room 1.17

Names (“Vagrant”), pronouns (“they”) and definite descriptions (“the birder”) are examples of referring expressions, linguistic forms that point to referents. The many-to-many relation-ship between these forms and the referents they denote make referential reasoning a significant challenge for natural language processing systems that deal exclusively with linguistic form. Beyond denotational meanings, referring expressions can also have gendered and racial connotations, leading to their use in measuring sociodemographic biases in society and NLP systems. In this talk, I will introduce theoretical arguments and empirical evidence that refer-ring expressions are problematic proxies for sociodemographic factors. Then, I will present my work on disentangling meaningful reasoning about pronominal reference from shallow repetition. After this overview of my dissertation, I will conclude with a broader perspective on fair and faithful natural language processing, beyond referring expressions and English.

Hoang Thu Trang Do
Transcriptomic and Proteomic Rewiring in Tissue-specific Regulation
(Advisor: Prof. Volkhard Helms)
Friday, 09.01.26, 13:00, building E2 1, room E007

The identity of a cell is characterized by its distinct physiology and behaviours, which develop from a single embryonic cell during the course of development. The differences between cell types or tissues within an organism are reflected at multiple levels, from its genetic components in DNA and RNA, to protein interactions and characteristic signalling pathways. In this doctoral thesis, the rewiring events at different omics levels that are linked by various cell-dependent regulatory factors were investigated, ultimately to deepen the understanding of cells fate and identity. The first study „Association between Differential Exon Usage and De-regulated Epigenetic Marks in Development“ focuses on the interplay between alternative splicing (AS) and epigenetic deregulation, while two later studies, namely „A better brain? Alternative spliced STIM2 in hominoids arises with synapse formation and creates a gain-of-function variant“ and „HyperTRIBE identifies IGF2BP2/IMP2 targets in vivo and links IMP2 to autophagy“, explore the functional roles of specific transcript variant and RBPs in specific cell types and experiment contexts. In the second chapter, three projects including „Detecting Re-wiring Events in Protein-Protein Interaction Networks Based on Transcriptomic Data“, „PPIX-press and PPICompare Webservers infer condition-specific and differential PPI networks“ and „Tissue-specific RNA binding protein networks provide insights on splicing processes“, assessed and developed a new workflow consisting of two webservices for analyzing protein-protein interaction networks with the ultimate aim to study the differential interactions of RBPs across various cell types and tissues that may associate with AS.