Papers or posters from seminars, congresses, etc.
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Publication Facilitating a Sustainable Electric Vehicle Transition through Consumer Utility Driven Pricing(International Conference on Information Systems (ICIS), 2018-12) Valogianni, Konstantina; Ketter, Wolfgang; Zhdanov, Dmitry; Collins, John; https://ror.org/02jjdwm75A transition to an electrified transportation system is widely assumed to be an important step along the road to environmental sustainability. However, large penetrations of electric vehicles (EVs) may put electricity grids under critical strain, since peaks in electricity demand are likely to increase radically. Efforts to manage demand peaks through pricing schemes may create new peaks at low-price periods, if large numbers of EV owners try to benefit from low prices. We propose a pricing method, called consumer utility driven pricing, which learns from EV owners’ reactions to sub-optimal prices and adjusts announced prices accordingly. We evaluate our results in simulations, where we find that consumer utility driven pricing outperforms current electricity pricing schemes. We test our method in matching both flat and extremely volatile demand profiles and we see that in both cases it performs closely to what it is theoretically possible under perfect information.Publication Heterogeneous Electric Vehicle Charging Coordination: A Variable Charging Speed Approach(2019-01-08) Valogianni, Konstantina; Ketter, Wolfgang ; Collins, John; Adomavicius, Gediminas; https://ror.org/02jjdwm75We present a coordination mechanism that reduces peak demand coming from EV charging, supports grid stability and environmental sustainability. The proposed mechanism accounts for individual commuting preferences, as well as desired states of charge by certain deadlines, which can serve as a proxy for range anxiety. It can shape EV charging toward a desired profile, without violating individual preferences. Our mechanism mitigates herding, which is typical in populations where all agents receive the same price signals and make similar charging decisions. Furthermore, it assumes no prior knowledge about EV customers and therefore learns preferences and reactions to prices dynamically. We show through simulations that our mechanism induces a less volatile demand and lower peaks compared to currently used benchmarks.Publication Multiple Vickrey Auctions for Sustainable Electric Vehicle Charging(International Conference on Information Systems (ICIS), 2019-12) Valogianni, Konstantina; Gupta, Alok; Ketter, Wolfgang; Sen, Soumya; Heck, Eric van; https://ror.org/02jjdwm75Electric vehicles (EVs) are important contributors to a sustainable future. However, uncontrolled EV charging in the smart grid is expected to stress its infrastructure, as it needs to accommodate extra electricity demand coming from EV charging. We propose an auction mechanism to optimally schedule EV charging in a sustainable manner so that the grid is not overloaded. Our solution has lower computational complexity, compared to state-of-the-art mechanisms, making it easily applicable to practice. Our mechanism creates electricity peak demand reduction, which is important for improving sustainability in the grid, and provides optimized charging speed design recommendations so that raw materials are not excessively used. We prove the optimal conditions that must hold, so that different stakeholder objectives are satisfied. We validate our mechanism on real-world data and examine how different trade-offs affect social welfare and revenues, providing a holistic view to grid stakeholders that need to satisfy potentially conflicting objectives.Publication Is Fast Feminine?: The Effect of Speed of Observed Hand-Motor Actions on Consumer Judgment and Behaviors(Association of Consumer Research, 2020-05-26) Sayin, Eda; Malik, Sumit; https://ror.org/02jjdwm75This paper shows that observing a slow (vs. fast) hand-motor action with an advertised product (eg, fabric, shaving foam, etc.) can evince stereotypic feminine (vs. masculine) schematic associations and, subsequently, alter consumer judgment. In three studies, we provide evidence on the effect of dynamic-observed experiences across advertising contexts.Publication Tensor Approximation for Multidimensional and Multivariate Data(Springer Science and Business Media Deutschland GmbH, 2021) Pajarola, Renato; Suter, Susanne; Yang, Haiyang; Ballester, Rafael; Seventh Framework Programme; Swiss National Science Foundation; https://ror.org/02jjdwm75Tensor decomposition methods and multilinear algebra are powerful tools to cope with challenges around multidimensional and multivariate data in computer graphics,image processing and data visualization,in particular with respect to compact representation and processing of increasingly large-scale data sets. Initially proposed as an extension of the concept of matrix rank for 3 and more dimensions,tensor decomposition methods have found applications in a remarkably wide range of disciplines. We briefly review the main concepts of tensor decompositions and their application to multidimensional visual data. Furthermore,we will include a first outlook on porting these techniques to multivariate data such as vector and tensor fields.Publication Open Science Policies in the Universidad Carlos III de Madrid(2024-10-30) Bermejo Castrillo, Manuel Ángel; https://ror.org/02jjdwm75-Publication Protecting knowledge through openness Open Science and intellectual property(IE University, 2024-10-30) Cueva, Javier de la; https://ror.org/02jjdwm75-Publication Open Access: what do Spanish academics think and do?(IE University, 2024-10-30) Torre, Eva María de la; https://ror.org/02jjdwm75-Publication Embracing Open Science: Meeting requirements and unlocking benefits(IE University, 2024-10-30) Gómez, Alicia Fátima; https://ror.org/02jjdwm75-Publication AI Policies in Academic Publishing: New Approaches to Transparency, Ethics, and Accountability(2025-01-21) Gómez, Alicia Fátima; Güneş, Güssün; https://ror.org/02jjdwm75As Artificial Intelligence (AI) continues to influence academic publishing, its integration has introduced both innovative advancements and complex ethical challenges. This paper explores AI policies implemented by major academic publishers, including Elsevier, Springer Nature, Wiley, Taylor & Francis, and others, aiming to understand how these policies guide ethical AI use and maintain research integrity. The central research question driving this analysis is: In what ways do AI policies shape transparency, ethical responsibility, and accountability in the context of academic publishing? Methodology: To answer this question, we conducted a comparative policy analysis, examining documents and guidelines provided by key academic publishers. Policies were analyzed to assess criteria such as transparency, author accountability, ethical standards, confidentiality, and intellectual property considerations. Each policy was evaluated for directives on AI use across three primary areas: authorship, manuscript preparation, and peer review processes. By mapping out common principles and unique variations, this analysis identifies emerging trends in how publishers navigate AI's evolving role within academic publishing. Results: Our findings reveal a shared emphasis on transparency and author responsibility. Across all policies, publishers mandate that authors disclose any AI usage in their manuscript preparation, typically within the Methods or Acknowledgments sections. This requirement supports transparency and allows reviewers to better understand the scope of AI assistance. Furthermore, policies consistently prohibit AI from being listed as an author, underscoring the idea that AI lacks the original thought and accountability that human authors provide. Confidentiality emerges as another core tenet, with most publishers discouraging the use of AI in peer review, as uploading manuscripts to AI platforms could compromise privacy and data security. Ethical considerations further extend to AI-generated visuals and data manipulation, with restrictions placed on using AI to fabricate, alter, or misrepresent images or datasets. Significance: The implications of these findings are significant in promoting ethical standards and preventing potential misuse of AI in academic research. As the AI landscape evolves, these policies represent essential guidelines, positioning publishers as gatekeepers of research integrity. They advocate for transparency in AI disclosures and underscore the need for human accountability, both crucial for maintaining trust in the scholarly record. In establishing clear boundaries for AI's role, these policies also anticipate future technological advancements, promoting adaptability and vigilance among authors, reviewers, and editors. This study contributes to the broader discourse on AI governance by illustrating how academic publishers are actively shaping the ethical framework around AI in research. It serves as a valuable resource for researchers, institutions, and policymakers interested in fostering an ethical integration of AI in academia. In sum, by enforcing transparency, prioritizing accountability, and addressing ethical risks, these policies not only protect the credibility of academic research but also support a responsible transition to AI-enhanced scholarly communication.Publication FAIR in Practice: evaluación de los principios FAIR para datasets de Investigación(2025-02-26) Gómez, Alicia Fátima; https://ror.org/02jjdwm75This content explores the practical implementation of FAIR principles—ensuring research data is findable, accessible, interoperable, and reusable. It outlines different levels of FAIR maturity and highlights the importance of metadata quality, licensing, and repository standards. A range of tools and platforms are presented to help researchers assess and improve the FAIRness of their datasets, including automated evaluation services and self-assessment resources. It also includes templates and guidelines for describing research data to facilitate better sharing and reuse across scientific communities.Publication Meet & Greet: (Open) Science and Research Data Management(IE University, 2025-03-25) Gómez, Alicia Fátima; Aguilera Ortega, Raúl; https://ror.org/02jjdwm75This presentation introduces key concepts, policies, and actors involved in Open Science and Research Data Management across Europe and Spain. It explores how international recommendations, national strategies, and EU frameworks like Horizon Europe and ResearchComp are shaping a more open, transparent, and responsible research ecosystem. The content also addresses FAIR data principles, privacy and intellectual property rights, and the evolving role of libraries in supporting infrastructures and services. Emphasis is placed on skills development, research assessment reform, and enabling practices such as open access, data sharing, and responsible data governance.