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Verk
Environmental Sustainability of Hydropower and Its Adaptation to Climate Change
(2026) Patro, Epari Ritesh; Balouchi, Behnam; Gosselin, Marie-Pierre; Aparicio, Maria Ubierna; Finger, David Christian; Department of Engineering
Verk
Vector-Valued Robust Stochastic Control
(2026-07-14) Cialenco, Igor; Kováčová, Gabriela; Department of Engineering
We study a dynamic stochastic control problem subject to Knightian uncertainty with multiobjective (vector-valued) criteria. Assuming the preferences across expected multiloss vectors are represented by a given, yet general, preorder, we address the model uncertainty by adopting a robust or minimax perspective, minimizing expected loss across the worst-case model. For loss functions taking scalar values, there is no ambiguity in interpreting supremum and infimum. In contrast, major challenges for multi-loss control problems include properly defining and interpreting the notions of supremum and infimum, as well as addressing their non-uniqueness. To deal with these, we employ the notion of an ideal point vector-valued supremum for the robust part of the problem, while we view the control part as a multi-objective (or vector) optimization problem. Using a set-valued framework, we derive both a weak and a strong version of the dynamic programming principle (DPP) or Bellman equations for two appropriately chosen value functions: the collection of all worst expected losses across all feasible actions, and for its upper image. The weak version of Bellman's principle is proved under minimal assumptions. To establish a stronger version of DPP, we introduce the rectangularity property with respect to a general preorder. We also show that the weak minimizers obey the time consistency property. Finally, we study the important particular case of component-wise partial order of vectors, and conclude with some illustrative examples motivated by financial problems.
Verk
THz generation in a DC diode with base resistor
(Institute of Electrical and Electronics Engineers Inc., 2026) Alexandersson, Bjarttor Steinn; Torfason, Kristinn; Manolescu, Andrei; Valfells, Agust; Department of Engineering
We have recently discovered a novel mechanism for generating oscillating current at THz frequency in a DC vacuum microdiode with a series resistor. We performed simulations of field emission in a planar microdiode with an appreciable resistor and observed the emergence of regular oscillations in the diode current due to loading of the resistor modulating the surface electric field and subsequently the emission [1]. Here we extend our previous work to examine how field enhancement at the cathode surface affects the operating parameters. It is shown that using field emitter arrays the voltage can be reduced significantly while maintaining a robust diode current oscillating in the THz frequency range. Using molecular dynamics simulations, we show how the configuration of the field emitter array, in the context of other diode parameters, affects the performance of the oscillator.
Verk
HomeGuard : Community-Driven Hierarchical Federated Learning for Robust Smart-Home Intrusion Detection
(Science and Technology Publications, Lda, 2026) Eichhammer, Philipp; Berger, Christian; Reiser, Hans P.; De Capitani Di Vimercati, Sabrina; Samarati, Pierangela; Department of Computer Science
Federated Learning (FL) has emerged as a promising approach to build collaborative Intrusion Detection Systems (IDSs) in the IoT, e.g., in smart homes. FL allows models to be shared without exposing sensitive training data, thus protecting the privacy of IoT users. However, existing FL-based IDSs rely on assumptions that rarely hold in practice, namely homogeneous devices, synchronous participation, and benign contributors. We argue that, in real-world smart homes, IoT devices are highly heterogeneous, resource-constrained, and attractive targets for adversaries, which makes conventional FL less effective or vulnerable to poisoning attacks. We present HOMEGUARD, a collaborative IDS specifically designed for the constraints and threat model of practical smart home IoT infrastructures. In our approach, we rethink FL deployment by (1) offloading model training to gateways to manage computational heterogeneity of IoT devices and (2) organizing anomaly detection models into device-specific communities based on privacy-preserving traffic fingerprints which do not expose sensitive data. Within communities and across smart homes, HOMEGUARD implements an asynchronous, hierarchical FL architecture that tolerates device churn, uneven data availability, and Byzantine participants. Further, HOMEGUARD applies Byzantine-robust aggregation at two levels: within local communities, and globally in the cloud to limit the impact of compromised devices. Experimental evaluation shows that HOMEGUARD achieves an average true positive rate of 97.86% locally and 97.53% globally with a 0% false positive rate, while maintaining robustness against both targeted and untargeted poisoning attacks.
Verk
REIMAGINING CROSS-FUNCTIONAL DESIGN IN THE AGE OF AI: A PRELIMINARY INVESTIGATION : A Preliminary Investigation
(2025) Candi, Marina; Kahn, Kenneth B.; Department of Business and Economics
Being cross-functional in design work can enable effective innovation, though the relevance of ‘being cross-functional’ and the related concept of ‘T-shaped’ individuals could potentially change in the age of artificial intelligence (AI). Reporting results of interviews with design managers, we explore what being cross-functional means for design, the benefits and challenges inherent in cross-functional design work, and AI’s possible impact on the nature of being cross-functional during design activities. Manager responses emphasized the importance of being cross-functional in design work. Noted challenges of cross-functional work include conflicting priorities, differing opinions, unclear roles, loss of design influence, multitasking pressure, and personality differences. Noted benefits include broader viewpoint, creativity versus practicality balance, healthy tension, diverse perspectives, early issue identification, and well-rounded solutions. Regarding the effects of AI, the transformation of cross-functional work by automating routine tasks and enabling deeper data-driven insights is foreseen, but there is disagreement on the degree of change. Some see a shift in the cognitive burden on individuals, allowing them to focus more on creative and integrative tasks, others not so much. All agree that AI tools offer significant opportunities for synthesizing information and managing mundane project management tasks. Managerial and research implications are suggested.