Robust estimation in exponential families: from theory to practice

Doctoral thesis (2023)

Скончалась Эмилия Пух

Article for general public (2023)

Biography of Emmy Poukh (1933-2023), the wife of the Russian-Orthodox priest Luxembourgs Serge Poukh (1926-2016)

Non-Hermitian Hamiltonian deformations in quantum mechanics

in Journal of High Energy Physics (2023), 01(60),

The Politics of Collective Principals

Presentation (2023, January 12)

We study a dynamic principal-agent model in which the principal is a group whose members hold heterogeneous and evolving values from an agreement with the agent. The principals collectively choose the ... [more ▼]

We study a dynamic principal-agent model in which the principal is a group whose members hold heterogeneous and evolving values from an agreement with the agent. The principals collectively choose the agent’s offer, which binds all principals if the agent accepts. Learning about the agent’s private information reduces the principals’ conflicts over their joint offer, mitigating a principal’s subsequent losses if she is not decisive. As a consequence, a principal in a group prefers to screen the agent more aggressively than a single principal. We study the dynamics of the principals’ collective choice, and obtain conditions under which decisive members of the group successively trade away their decision-making authority, leading inexorably to the concentration of negotiation power in the hands of a single principal. [less ▲]

Predicting Challenge and Threat Appraisal of Job Demands among Nurses: The Role of Matching Job Resources

in International Journal of Environmental Research and Public Health (2023), 20(2), 1288

(1) Background: Empirical studies have started to examine employees’ subjective appraisals of job demands and their relations to employees’ health. However, knowledge of working conditions, which might ... [more ▼]

(1) Background: Empirical studies have started to examine employees’ subjective appraisals of job demands and their relations to employees’ health. However, knowledge of working conditions, which might contribute to how employees appraise specific job demands, is scarce. The present study aimed to examine predictors of nurses’ appraisals of job demands (i.e., time pressure, emotional demands, physical demands, and role ambiguity) as challenges and/or threats among corresponding job resources (i.e., autonomy, social support, physical resources, participation in decision-making). It also examined moderating effects of these predictors. (2) Methods: Cross-sectional data were collected via an online survey in a sample of 425 nurses working in Luxembourg. (3) Results: Multiple regression analyses indicated that matching job resources predicted nurses’ appraisal of job demands as challenging. Threat appraisal was predicted by three out of four kinds of job resources (i.e., autonomy, physical resources, participation in decision-making). However, the current study did not find any moderating effects between job demands and job resources on challenge/threat appraisals. (4) Conclusions: The present study identified domain-specific job resources that contribute to how employees perceive selected job demands. Accordingly, we encourage scholars and practitioners to align job demands with matching job resources to prevent nurses’ threat appraisal of job demands, and to promote their challenge appraisals. [less ▲]

Analyzing the Unanalyzable: an Application to Android Apps

Doctoral thesis (2023)

In general, software is unreliable. Its behavior can deviate from users’ expectations because of bugs, vulnerabilities, or even malicious code. Manually vetting software is a challenging, tedious, and ... [more ▼]

In general, software is unreliable. Its behavior can deviate from users’ expectations because of bugs, vulnerabilities, or even malicious code. Manually vetting software is a challenging, tedious, and highly-costly task that does not scale. To alleviate excessive costs and analysts’ burdens, automated static analysis techniques have been proposed by both the research and practitioner communities making static analysis a central topic in software engineering. In the meantime, mobile apps have considerably grown in importance. Today, most humans carry software in their pockets, with the Android operating system leading the market. Millions of apps have been proposed to the public so far, targeting a wide range of activities such as games, health, banking, GPS, etc. Hence, Android apps collect and manipulate a considerable amount of sensitive information, which puts users’ security and privacy at risk. Consequently, it is paramount to ensure that apps distributed through public channels (e.g., the Google Play) are free from malicious code. Hence, the research and practitioner communities have put much effort into devising new automated techniques to vet Android apps against malicious activities over the last decade. Analyzing Android apps is, however, challenging. On the one hand, the Android framework proposes constructs that can be used to evade dynamic analysis by triggering the malicious code only under certain circumstances, e.g., if the device is not an emulator and is currently connected to power. Hence, dynamic analyses can -easily- be fooled by malicious developers by making some code fragments difficult to reach. On the other hand, static analyses are challenged by Android-specific constructs that limit the coverage of off-the-shell static analyzers. The research community has already addressed some of these constructs, including inter-component communication or lifecycle methods. However, other constructs, such as implicit calls (i.e., when the Android framework asynchronously triggers a method in the app code), make some app code fragments unreachable to the static analyzers, while these fragments are executed when the app is run. Altogether, many apps’ code parts are unanalyzable: they are either not reachable by dynamic analyses or not covered by static analyzers. In this manuscript, we describe our contributions to the research effort from two angles: ① statically detecting malicious code that is difficult to access to dynamic analyzers because they are triggered under specific circumstances; and ② statically analyzing code not accessible to existing static analyzers to improve the comprehensiveness of app analyses. More precisely, in Part I, we first present a replication study of a state-of-the-art static logic bomb detector to better show its limitations. We then introduce a novel hybrid approach for detecting suspicious hidden sensitive operations towards triaging logic bombs. We finally detail the construction of a dataset of Android apps automatically infected with logic bombs. In Part II, we present our work to improve the comprehensiveness of Android apps’ static analysis. More specifically, we first show how we contributed to account for atypical inter-component communication in Android apps. Then, we present a novel approach to unify both the bytecode and native in Android apps to account for the multi-language trend in app development. Finally, we present our work to resolve conditional implicit calls in Android apps to improve static and dynamic analyzers. [less ▲]

The Politics of Collective Principals

Presentation (2023, January 08)

We study a dynamic principal-agent model in which the principal is a group whose members hold heterogeneous and evolving values from an agreement with the agent. The principals collectively choose the ... [more ▼]

We study a dynamic principal-agent model in which the principal is a group whose members hold heterogeneous and evolving values from an agreement with the agent. The principals collectively choose the agent’s offer, which binds all principals if the agent accepts. Learning about the agent’s private information reduces the principals’ conflicts over their joint offer, mitigating a principal’s subsequent losses if she is not decisive. As a consequence, a principal in a group prefers to screen the agent more aggressively than a single principal. We study the dynamics of the principals’ collective choice, and obtain conditions under which decisive members of the group successively trade away their decision-making authority, leading inexorably to the concentration of negotiation power in the hands of a single principal. [less ▲]

Interview with Dr. Inna Ganschow (C2DH, Uni of Lux)

Speeches/Talks (2023)

Throughout her academic projects, Dr Ganschow is working on the presence of the so-called Russian diaspora in Luxembourg, i.e. the emigrant population from former Soviet Republics. Her current project ... [more ▼]

Throughout her academic projects, Dr Ganschow is working on the presence of the so-called Russian diaspora in Luxembourg, i.e. the emigrant population from former Soviet Republics. Her current project deals with Soviet forced labourers during the Second World War and is commissioned by the Luxembourg government. In her work, she decided to compare the situation of these forced labourers, mainly young women coming from Ukraine, with the local population, in the Belval region in the south of Luxembourg. Another interview topic is LURN network (Luxembourg Ukrainian Researcher Network) which aims to connect Ukrainian researchers displaced by the war and who are temporarily working in Luxembourg for research institutions. It also aims to provide additional points of contact with the Luxembourg research community. The LURN already organised three different meetings and workshops since its creation in August 2022, facilitating Ukrainian scholars contacts in Luxembourg new environment, and stimulating new research projects. [less ▲]

Federated Learning as a Solution for Problems Related to Intergovernmental Data Sharing

in Proceedings of the 56th Hawaii International Conference on System Sciences (2023, January 03)

To address global problems, intergovernmental collaboration is needed. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts ... [more ▼]

To address global problems, intergovernmental collaboration is needed. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts of data to perform well. However, data sharing between governments is limited. A possible solution is federated learning (FL), a decentralised AI method created to utilise personal information on edge devices. Instead of sharing data, governments can build their own models and just share the model parameters with a centralised server aggregating all parameters, resulting in a superior overall model. By conducting a structured literature review, we show how major intergovernmental data sharing challenges like disincentives, legal and ethical issues as well as technical constraints can be solved through FL. Enhanced AI while maintaining privacy through FL thus allows governments to collaboratively address global problems, which will positively impact governments and citizens. [less ▲]

Subjektives Wohlbefinden in Einrichtungen der stationären luxemburgischen Kinder- und Jugendhilfe. Eine qualitative Studie mit betroffenen Jugendlichen.

Doctoral thesis (2023)

Life in residential child and youth welfare facilities is a great challenge for the concerned children. This paper explains factors that contribute to an increase or decrease in the subjectively perceived ... [more ▼]

Life in residential child and youth welfare facilities is a great challenge for the concerned children. This paper explains factors that contribute to an increase or decrease in the subjectively perceived well-being of children and adolescents in residential institutions. Qualitative content analysis was chosen to analyze the data collected in Luxembourg. The study shows that children's well-being is particularly influenced by structural conditions and concepts, by fellow residents, and by (pedagogical) professionals. Another result points to the presence of different forms of violence and to the danger of (re-) traumatization of the children and young people within the institutions of inpatient child and youth welfare in Luxembourg. [less ▲]