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@Inproceedings { BumpyRideCHI25,
    author = {Sasalovici, Markus and Zeqiri, Albin and Schramm, Robin Connor and Ariza Nu\~{n}ez, Oscar Javier and Jansen, Pascal and Freiwald, Jann Philipp and Colley, Mark and Winkler, Christian and Rukzio, Enrico},
    title = {Bumpy Ride? Understanding the Effects of External Forces on Spatial Interactions in Moving Vehicles},
    abstract = {As the use of Head-Mounted Displays in moving vehicles increases, passengers can immerse themselves in visual experiences independent of their physical environment. However, interaction methods are susceptible to physical motion, leading to input errors and reduced task performance. This work investigates the impact of G-forces, vibrations, and unpredictable maneuvers on 3D interaction methods. We conducted a field study with 24 participants in both stationary and moving vehicles to examine the effects of vehicle motion on four interaction methods: (1) Gaze\\&Pinch, (2) DirectTouch, (3) Handray, and (4) HeadGaze. Participants performed selections in a Fitts' Law task. Our findings reveal a significant effect of vehicle motion on interaction accuracy and duration across the tested combinations of Interaction Method x Road Type x Curve Type. We found a significant impact of movement on throughput, error rate, and perceived workload. Finally, we propose future research considerations and recommendations on interaction methods during vehicle movement.},
    status = {1},
    year = {2025},
    month = {4},
    DOI = {10.1145/3706598.3714077},
    booktitle = {Proceedings of the CHI 2025 (SIGCHI Conference on Human Factors in Computing Systems)},
    publisher = {ACM},
    series = {CHI '25},
    file_url = {t3://file?uid=525741}
}

@Inproceedings { PlantPalCHI25,
    author = {Zeqiri, Albin and Britten, Julian and Schramm, Clara and Jansen, Pascal and Rietzler, Michael and Rukzio, Enrico},
    title = {PlantPal: Leveraging Precision Agriculture Robots to Facilitate Remote Engagement in Urban Gardening},
    abstract = {Technological progress has often been measured by the extent to which it shields and protects us from the harshness of nature. At the same time, it has long been recognised that our resulting disengagement from nature negatively affects our wellbeing and impedes awareness of our vital dependence on natural environments. To understand how HCI has considered the possibilities that digital technology offers for engaging with nature, we conducted a scoping review encompassing more than 20 years of HCI research on nature engagement. We compare the orientations, motivations, and methodologies of different threads within this growing body of work. We show how HCI research has enabled varied forms of direct and indirect engagement with nature, and we develop a typology of the roles proposed for technology in this work. We highlight promising and under-utilised approaches to designing for nature engagement and discuss directions for future research.},
    status = {1},
    year = {2025},
    month = {1},
    booktitle = {Proceedings of the CHI 2025 (SIGCHI Conference on Human Factors in Computing Systems)},
    publisher = {ACM},
    series = {CHI '25},
    file_url = {t3://file?uid=525683}
}

@Article { 10.1145/3643558,
    author = {Zeqiri, Albin and Jansen, Pascal and Rixen, Jan Ole and Rietzler, Michael and Rukzio, Enrico},
    title = {'Eco Is Just Marketing': Unraveling Everyday Barriers to the Adoption of Energy-Saving Features in Major Home Appliances},
    abstract = {Energy-saving features (ESFs) represent a simple way to reduce the resource consumption of home appliances (HAs), yet they remain under-utilized. While prior research focused on increasing the use of ESFs through behavior change interventions, there is currently no clarity on the barriers that restrict their utilization in the first place. To bridge this gap, we conducted a qualitative analysis of 349 Amazon product reviews and 98 Reddit discussions, yielding three qualitative themes that showcase how users perceive, interact with, and evaluate ESFs in HAs. Based on these themes, we derived frequent barriers to ESF adoption, which guided a subsequent expert focus group (N=5) to assess the suitability of behavior change interventions and potential alternative strategies for ESF adoption. Our findings deepen the understanding of everyday barriers surrounding ESFs and enable the targeted design and assessment of interventions for future HAs.},
    year = {2024},
    month = {3},
    DOI = {10.1145/3643558},
    journal = {Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (IMWUT)},
    volume = {8},
    publisher = {ACM},
    pages = {27},
    number = {1},
    keywords = {energy-saving mechanisms, home appliances, sustainability},
    file_url = {t3://file?uid=486903}
}

@Article { 950798920855_2024,
    author = {Colley, Mark and Hartwig, Sebastian and Zeqiri, Albin and Ropinski, Timo and Rukzio, Enrico},
    title = {AutoTherm: A Dataset and Benchmark for Thermal Comfort Estimation Indoors and in Vehicles},
    year = {2024},
    DOI = {10.1145/3678503},
    journal = {Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (IMWUT); Joint First Authors},
    publisher = {ACM},
    address = {New York, NY, USA},
    file_url = {t3://file?uid=491825}
}

@Conference { 10.1145/3675094.3678487,
    author = {Zeqiri, Albin and Rietzler, Michael and Rukzio, Enrico},
    title = {Exploring Contextual Feature Combinations for Prediction of Subjective Thermal Perceptions},
    abstract = {Thermal attributes in the environment impact well-being, but their inclusion in standard well-being monitoring is challenging due to complex measurement requirements. Industry standards like the Predicted Mean Vote (PMV) index need numerous measures and specialized setups, making large-scale applications impractical. This study investigates predicting thermal perception ratings using only contextual factors. We conducted an ablation study using the Chinese Thermal Comfort Dataset (CTCD) and a Random Forest (RF) classifier to evaluate prediction performance with different contextual feature combinations on five labeling scales. Results showed that omitting measures required for PMV index calculation and relying on contextual features exclusively achieved F1 scores similar to those when including PMV measures. Key predictive factors included daily outdoor temperature and a person's clothing, weight, and age. These findings suggest that leveraging more accessible contextual data to estimate thermal perception ratings is promising, and further research should explore more contextual factors to enhance prediction accuracy and support well-being assessments.},
    year = {2024},
    isbn = {9798400710582},
    DOI = {10.1145/3675094.3678487},
    booktitle = {Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    series = {UbiComp '24},
    pages = {371–376},
    keywords = {context-based estimation, thermal perception, ubiquitous computing},
    file_url = {t3://file?uid=521915}
}