James Landay

All Publications

• A framework of digital biomarkers for neurodegenerative diseases. Nature reviews bioengineering Nerrise, F., Schütz, N., Zhao, Q., Gould, C., Milstein, A., Schulman, K., Henderson, V. W., Landay, J., Fei-Fei, L., Lin, F. V., Adeli, E. 2026

  Abstract

  Digital biomarkers (DBMs) are a new class of health indicators derived from digital technologies - including smartphones, wearable devices and ambient sensors - that enable continuous, real-time monitoring of signals in everyday settings. By providing richer and more dynamic data than conventional, point-in-time measurements, DBMs offer fresh opportunities for remote patient assessment, personalized care and large-scale biomedical research. Importantly, DBMs function as powerful complementary tools to traditional biomarkers that can screen candidates for more invasive tests and provide contextual data between clinical visits. This Review provides a standardized classification of DBMs focused on neurodegenerative diseases, including Alzheimer disease, Parkinson disease, mild cognitive impairment, Huntington disease, multiple sclerosis, frontotemporal dementia, spinocerebellar ataxia and dementia with Lewy bodies, centred around three questions: what is being measured (the concept of interest), how it is measured (the sensing technologies) and why it is measured (the application areas). By examining these dimensions, we highlight the potential of DBMs to transform clinical monitoring, early detection and therapeutic interventions in these disorders.

  View details for DOI 10.1038/s44222-026-00433-7

  View details for PubMedID 42239941

  View details for PubMedCentralID PMC13229411

• Deep Sketch-Based 3D Modeling: A Survey COMPUTER GRAPHICS FORUM Tono, A., Wu, J., Wetzstein, G., Armeni, I., Subramonyam, H., Landay, J., Fischer, M. 2026

  View details for DOI 10.1111/cgf.70302

  View details for Web of Science ID 001687493600001

• Vascular waveform analysis using Bayesian pulse deconvolution. bioRxiv : the preprint server for biology Ruth, P. S., DeBenedetti, T., O'Brien, L., Landay, J. A., Coleman, T. P., Fox, E. B. 2026

  Abstract

  Vascular waveforms, which measure bulk flow in blood vessels, are widely used to measure vital signs, diagnose conditions, and predict long-term health outcomes. Analyzing vascular waveforms depends on three fundamentally interdependent tasks: signal filtering, pulse timing detection, and pulse shape extraction. We hypothesized that Bayesian pulse deconvolution can achieve improved performance on all three tasks by solving them jointly. This method uses an analytical, generative model of vascular waveforms with priors informed by physical and biological domain knowledge. In simulations, Bayesian pulse deconvolution achieves better performance on all tasks compared with existing algorithms: 90% reduction of median filtering error, 60% reduction in pulse timing error, and 85% reduction in shape extraction error. The advantages in simulations extend to human recordings of photoplethysmography waveforms. Taking real time-synchronized electrocardiogram R-R intervals as a proxy ground truth, Bayesian pulse deconvolution achieves 40% lower pulse interval estimation error (RMSE =5.1 ms) compared with typical algorithms (RMSE = 8.3 ms, p=1e-10). By extracting more accurate and informative insights from vascular waveforms, Bayesian pulse deconvolution could advance a wide array of health technologies that rely on interpreting signals from blood vessels.

  View details for DOI 10.64898/2026.02.09.699383

  View details for PubMedID 41727149

  View details for PubMedCentralID PMC12919062

• Just-In-Time Objectives: A General Approach for Specialized AI Interactions Lam, M. S., Shaikh, O., Xu, H., Guo, A., Yang, D., Heer, J., Landay, J. A., Bernstein, M. S., ACM ASSOC COMPUTING MACHINERY. 2026

  View details for DOI 10.1145/3772318.3790713

  View details for Web of Science ID 001795706500009

• Impact of windows, natural materials, and diverse representations in built environments on psychological and physiological well-being: A between-subjects experiment in immersive virtual environments BUILDING AND ENVIRONMENT Altaf, B., Tavakoli, A., Ruth, P., Green, A., Xu, J., Jain, S., Chiu, E., Bencharit, L., Murnane, E. L., Landay, J. A., Billington, S. L. 2025; 280

  View details for DOI 10.1016/j.buildenv.2025.113147

  View details for Web of Science ID 001495152600001

• Black Older Adults' Perception of Using Voice Assistants to Enact a Medical Recovery Curriculum PROCEEDINGS OF THE ACM ON HUMAN COMPUTER INTERACTION Green, A., Polite, G., Hung, I., Fessele, K. L., Billington, S. L., Landay, J. A., Cuadra, A. 2025; 9 (2)

  View details for DOI 10.1145/3710937

  View details for Web of Science ID 001719986200003

• Black immersive virtuality: Racialized experiences of avatar embodiment and customization among Black users in social VR COMPUTERS IN HUMAN BEHAVIOR Deveaux, C., Han, E., Hudson, Z., Egelman, J., Landay, J. A., Bailenson, J. N. 2025; 168

  View details for DOI 10.1016/j.chb.2025.108639

  View details for Web of Science ID 001455538600001

• Oak Story: Improving Learner Outcomes with LLM-Mediated Interactive Narratives Cheng, A. Y., Zou, C. Q., Xie, A., Hsu, M., Yan, F., Huang, F., Zhang, D. K., Sharma, A., Poole, R., Rosli, D., Cuadra, A., Pea, R., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2025

  View details for DOI 10.1145/3746059.3747698

  View details for Web of Science ID 001612640500124

• Ontologies in Design: How Imagining a Tree Reveals Possibilities and Assumptions in Large Language Models Haghighi, N., Yu, S., Landay, J. A., Rosner, D., ACM ASSOC COMPUTING MACHINERY. 2025

  View details for DOI 10.1145/3706598.3713633

  View details for Web of Science ID 001501406100132

• GenieWizard: Multimodal App Feature Discovery with Large Language Models Yang, J., Shi, Y., Gu, C., Zheng, Z., Jain, A., Li, T., Lam, M. S., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2025

  View details for DOI 10.1145/3706598.3714327

  View details for Web of Science ID 001501412600400

• GPTCoach: Towards LLM-Based Physical Activity Coaching Jorke, M., Sapkota, S., Warkenthien, L., Vainio, N., Schmiedmayer, P., Brunskill, E., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2025

  View details for DOI 10.1145/3706598.3713819

  View details for Web of Science ID 001501406100316

• "They Make Us Old Before We're Old": Designing Ethical Health Technology with and for Older Adults PROCEEDINGS OF THE ACM ON HUMAN COMPUTER INTERACTION So, J., Estrada, S., Jorke, M., Bianchi, E., Wang, M., Haghighi, N., Fessele, K. L., Landay, J. A., Cuadra, A. 2024; 8 (CSCW2)

  View details for DOI 10.1145/3687017

  View details for Web of Science ID 001549337000005

• Effects of architectural interventions on psychological, cognitive, social, and pro-environmental aspects of occupant well-being: Results from an immersive online study (vol 253, 111293, 2024) BUILDING AND ENVIRONMENT Bianchi, E., Bencharit, L., Murnane, E. L., Altaf, B., Douglas, I. P., Landay, J. A., Billington, S. L. 2024; 262

  View details for DOI 10.1016/j.buildenv.2024.111789

  View details for Web of Science ID 001263338600001

• workplaces and human well-being: A mixed-methods study to quantify the effects of materials, windows, and representation on biobehavioral outcomes (vol 224, 109516, 2022) BUILDING AND ENVIRONMENT Douglas, I. P., Murnane, E. L., Bencharit, L., Altaf, B., Costa, J., Yang, J., Ackerson, M., Srivastava, C., Cooper, M., Douglas, K., King, J., Paredes, P. E., Camp, N. P., Mauriello, M., Ardoin, N. M., Markus, H., Landay, J. A., Billington, S. L. 2024; 261

  View details for DOI 10.1016/j.buildenv.2024.111717

  View details for Web of Science ID 001252792900001

• Use of crowdsourced online surveys to study the impact of architectural and design choices on wellbeing (vol 4, 780376, 2022) FRONTIERS IN SUSTAINABLE CITIES Altaf, B., Bianchi, E., Douglas, I. P., Douglas, K., Byers, B., Paredes, P. E., Ardoin, N. M., Markus, H. R., Murnane, E. L., Bencharit, L. Z., Landay, J. A., Billington, S. L. 2024; 6

  View details for DOI 10.3389/frsc.2024.1458100

  View details for Web of Science ID 001284821400001

• Digital Forms for All: A Holistic Multimodal Large Language Model Agent for Health Data Entry PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT Cuadra, A., Breuch, J., Estrada, S., Ihim, D., Hung, I., Askaryar, D., Hassanien, M., Fessele, K. L., Landay, J. A. 2024; 8 (2)

  View details for DOI 10.1145/3659624

  View details for Web of Science ID 001229316000031

• Reinforcement learning tutor better supported lower performers in a math task MACHINE LEARNING Ruan, S., Nie, A., Steenbergen, W., He, J., Zhang, J. Q., Guo, M., Liu, Y., Nguyen, K., Wang, C. Y., Ying, R., Landay, J. A., Brunskill, E. 2024

  View details for DOI 10.1007/s10994-023-06423-9

  View details for Web of Science ID 001159435300001

• Leveraging Immersive Virtual Environments for Occupant Well-Being Analysis Altaf, B., Tavakoli, A., Bianchi, E., Landay, J., Billington, S. L. edited by Turkan, Y., Louis, J., Leite, F., Ergan, S. AMER SOC CIVIL ENGINEERS. 2024: 85-92

  View details for Web of Science ID 001175759800011

• AMMA: Adaptive Multimodal Assistants Through Automated State Tracking and User Model-Directed Guidance Planning Yang, J., Qiu, L., Corona-Moreno, E., Shi, L., Bui, H., Lam, M. S., Landay, J. A., IEEE Comp Soc IEEE COMPUTER SOC. 2024: 892-902

  View details for DOI 10.1109/VR58804.2024.00108

  View details for Web of Science ID 001212781000083

• The Illusion of Empathy? Notes on Displays of Emotion in Human-Computer Interaction Cuadra, A., Wang, M., Stein, L., Jung, M. F., Dell, N., Estrin, D., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2024

  View details for DOI 10.1145/3613904.3642336

  View details for Web of Science ID 001255317908005

• ReactGenie: A Development Framework for Complex Multimodal Interactions Using Large Language Models Yang, J., Shi, Y., Zhang, Y., Li, K., Rosli, D., Jain, A., Zhang, S., Li, T., Landay, J. A., Lam, M. S., ACM ASSOC COMPUTING MACHINERY. 2024

  View details for DOI 10.1145/3613904.3642517

  View details for Web of Science ID 001259864902016

• Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooM Lam, M. S., Teoh, J., Landay, J. A., Heer, J., Bernstein, M. S., ACM ASSOC COMPUTING MACHINERY. 2024

  View details for DOI 10.1145/3613904.3642830

  View details for Web of Science ID 001266059702028

• On Stress: Combining Human Factors and Biosignals to Inform the Placement and Design of a Skin-like Stress Sensor Khan, Y., Mauriello, M., Nowruzi, P., Motani, A., Hon, G., Vitale, N., Li, J., Kim, J., Foudeh, A., Duvio, D., Shols, E., Chesnut, M., Landay, J., Liphardt, J., Williams, L., Sudheimer, K. D., Murmann, B., Bao, Z., Paredes, P. E., ACM ASSOC COMPUTING MACHINERY. 2024

  View details for DOI 10.1145/3613904.3643473

  View details for Web of Science ID 001266059704048

• Scientific and Fantastical: Creating Immersive, Culturally-Relevant Learning Experiences with Augmented Reality and Large Language Models Cheng, A. Y., Guo, M., Ran, M., Ranasaria, A., Sharma, A., Xie, A., Le, K. N., Vinaithirthan, B., Luan, S., Wright, D., Cuadra, A., Pea, R., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2024

  View details for DOI 10.1145/3613904.3642041

  View details for Web of Science ID 001255317902051

• A study of the role of indoor nature on solidarity and group identity during remote work BUILDING AND ENVIRONMENT Bianchi, E., Bloomfield, L. S. P., Bencharit, L. Z., Altaf, B., Sawe, N. A., Murnane, E. L., Landay, J. A., Billington, S. L. 2023; 245

  View details for DOI 10.1016/j.buildenv.2023.110909

  View details for Web of Science ID 001094399400001

• Exploring the Relationship Between Attribute Discrepancy and Avatar Embodiment in Immersive Social Virtual Reality. Cyberpsychology, behavior and social networking DeVeaux, C., Han, E., Landay, J. A., Bailenson, J. N. 2023

  Abstract

  Social virtual reality (VR) is an emerging set of platforms where users interact while embodying avatars. Given that VR headsets track real physical movements and map them onto one's avatar body, the nature of one's digital representation is an important aspect of social VR. However, little is known about how the visual proximity of an avatar to the self shapes user experience in naturalistic, social VR environments. In this article, we use this context to explore how embodiment is influenced by the perceived differences between the physical attributes of a user and the virtual attributes of their avatar. We selected a number of attributes for this measure that have been shown to be important for customization and representation in VR. Participants created an avatar, spent time in social VR, and reported on their experience in a questionnaire. Our results demonstrate a significant negative association between attribute discrepancy and avatar embodiment, the psychological experience of one's virtual body as their own body. We discuss implications for theories of self-representation and suggest urgency on the part of games and VR designers to improve the methods of creating avatars.

  View details for DOI 10.1089/cyber.2023.0210

  View details for PubMedID 37851990

• Time perception during the pandemic: A longitudinal study examining the role of indoor and outdoor nature exposure for remote workers BUILDING AND ENVIRONMENT Altaf, B., Bloomfield, L. S. P., Karzai, D. N., Sawe, N. A., Murnane, E. L., Bencharit, L., Landay, J. A., Billington, S. L. 2023; 243

  View details for DOI 10.1016/j.buildenv.2023.110644

  View details for Web of Science ID 001050526300001

• Narrative-Based Visual Feedback to Encourage Sustained Physical Activity: A Field Trial of the WhoIsZuki Mobile Health Platform PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT Murnane, E. L., Glazko, Y. S., Costa, J., Yao, R., Zhao, G., Moya, P. M. L., Landay, J. A. 2023; 7 (1)

  View details for DOI 10.1145/3580786

  View details for Web of Science ID 000957429700023

• Effects of Wearable Fitness Trackers and Activity Adequacy Mindsets on Affect, Behavior, and Health: Longitudinal Randomized Controlled Trial. Journal of medical Internet research Zahrt, O. H., Evans, K., Murnane, E., Santoro, E., Baiocchi, M., Landay, J., Delp, S., Crum, A. 2023; 25: e40529

  Abstract

  There is some initial evidence suggesting that mindsets about the adequacy and health consequences of one's physical activity (activity adequacy mindsets [AAMs]) can shape physical activity behavior, health, and well-being. However, it is unknown how to leverage these mindsets using wearable technology and other interventions.This research examined how wearable fitness trackers and meta-mindset interventions influence AAMs, affect, behavior, and health.A total of 162 community-dwelling adults were recruited via flyers and web-based platforms (ie, Craigslist and Nextdoor; final sample size after attrition or exclusion of 45 participants). Participants received an Apple Watch (Apple Inc) to wear for 5 weeks, which was equipped with an app that recorded step count and could display a (potentially manipulated) step count on the watch face. After a baseline week of receiving no feedback about step count, participants were randomly assigned to 1 of 4 experimental groups: they received either accurate step count (reference group; 41/162, 25.3%), 40% deflated step count (40/162, 24.7%), 40% inflated step count (40/162, 24.7%), or accurate step count+a web-based meta-mindset intervention teaching participants the value of adopting more positive AAMs (41/162, 25.3%). Participants were blinded to the condition. Outcome measures were taken in the laboratory by an experimenter at the beginning and end of participation and via web-based surveys in between. Longitudinal analysis examined changes within the accurate step count condition from baseline to treatment and compared them with changes in the deflated step count, inflated step count, and meta-mindset conditions.Participants receiving accurate step counts perceived their activity as more adequate and healthier, adopted a healthier diet, and experienced improved mental health (Patient-Reported Outcomes Measurement Information System [PROMIS]-29) and aerobic capacity but also reduced functional health (PROMIS-29; compared with their no-step-count baseline). Participants exposed to deflated step counts perceived their activity as more inadequate; ate more unhealthily; and experienced more negative affect, reduced self-esteem and mental health, and increased blood pressure and heart rate (compared with participants receiving accurate step counts). Inflated step counts did not change AAM or most other outcomes (compared with accurate step counts). Participants receiving the meta-mindset intervention experienced improved AAM, affect, functional health, and self-reported physical activity (compared with participants receiving accurate step counts only). Actual step count did not change in either condition.AAMs--induced by trackers or adopted deliberately--can influence affect, behavior, and health independently of actual physical activity.ClinicalTrials.gov NCT03939572; https://www.clinicaltrials.gov/ct2/show/NCT03939572.

  View details for DOI 10.2196/40529

  View details for PubMedID 36696172

• GPTeach: Interactive TA Training with GPT-based Students Markel, J. M., Opferman, S. G., Landay, J. A., Piech, C. edited by ACM ASSOC COMPUTING MACHINERY. 2023: 226-236

  View details for DOI 10.1145/3573051.3593393

  View details for Web of Science ID 001125787500024

• A Workshop-Based Method for Navigating Value Tensions in Collectively Speculated Worlds Haghighi, N., Jorke, M., Mohsen, Y., Cuadra, A., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2023: 1676-1692

  View details for DOI 10.1145/3563657.3595992

  View details for Web of Science ID 001090855700111

• Visual StoryCoder: A Multimodal Programming Environment for Children's Creation of Stories Dietz, G., Tamer, N., Ly, C., Le, J. K., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2023

  View details for DOI 10.1145/3544548.3580981

  View details for Web of Science ID 001037809505018

• Model Sketching: Centering Concepts in Early-Stage Machine Learning Model Design Lam, M. S., Ma, Z., Li, A., Freitas, I., Wang, D., Landay, J. A., Bernstein, M. S., ACM ASSOC COMPUTING MACHINERY. 2023

  View details for DOI 10.1145/3544548.3581290

  View details for Web of Science ID 001048393802055

• Designing Immersive, Narrative-Based Interfaces to Guide Outdoor Learning Cheng, A. Y., Ritchie, J., Agrawal, N., Childs, E., DeVeaux, C., Jee, Y., Leon, T., Maples, B., Cuadra, A., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2023

  View details for DOI 10.1145/3544548.3581365

  View details for Web of Science ID 001048393804013

• Leveraging Mobile Technology for Public Health Promotion: A Multidisciplinary Perspective. Annual review of public health Hicks, J. L., Boswell, M. A., Althoff, T., Crum, A. J., Ku, J. P., Landay, J. A., Moya, P. M., Murnane, E. L., Snyder, M. P., King, A. C., Delp, S. L. 2022

  Abstract

  Health behaviors are inextricably linked to health and well-being, yet issues such as physical inactivity and insufficient sleep remain significant global public health problems. Mobile technology-and the unprecedented scope and quantity of data it generates-has a promising but largely untapped potential to promote health behaviors at the individual and population levels. This perspective article provides multidisciplinary recommendations on the design and use of mobile technology, and the concomitant wealth of data, to promote behaviors that support overall health. Using physical activity as an exemplar health behavior, we review emerging strategies for health behavior change interventions. We describe progress on personalizing interventions to an individual and their social, cultural, and built environments, as well as on evaluating relationships between mobile technology data and health to establish evidence-based guidelines. In reviewing these strategies and highlighting directions for future research, we advance the use of theory-based, personalized, and human-centered approaches in promoting health behaviors. Expected final online publication date for the Annual Review of Public Health, Volume 44 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  View details for DOI 10.1146/annurev-publhealth-060220-041643

  View details for PubMedID 36542772

• Physical workplaces and human well-being: A mixed-methods study to quantify the effects of materials, windows, and representation on biobehavioral outcomes BUILDING AND ENVIRONMENT Douglas, I. P., Murnane, E. L., Bencharit, L., Altaf, B., Costa, J., Yang, J., Ackerson, M., Srivastava, C., Cooper, M., Douglas, K., King, J., Paredes, P. E., Camp, N. P., Mauriello, M., Ardoin, N. M., Markus, H., Landay, J. A., Billington, S. L. 2022; 224

  View details for DOI 10.1016/j.buildenv.2022.109516

  View details for Web of Science ID 000862289200005

• Beyond Being Real: A Sensorimotor Control Perspective on Interactions in Virtual Reality Abtahi, P., Hough, S. Q., Landay, J. A., Follmer, S., ACM ASSOC COMPUTING MACHINERY. 2022

  View details for DOI 10.1145/3491102.3517706

  View details for Web of Science ID 000922929504051

• HomeView: Automatically Building Smart Home Digital Twins With Augmented Reality Headsets Lyu, Z., Yang, J., Lam, M. S., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2022

  View details for DOI 10.1145/3526114.3558709

  View details for Web of Science ID 001042429100023

• HybridTrak: Adding Full-Body Tracking to VR Using an Off-the-Shelf Webcam Yang, J., Chen, T., Qin, F., Lam, M. S., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2022

  View details for DOI 10.1145/3491102.3502045

  View details for Web of Science ID 000890212503050

• Use of Crowdsourced Online Surveys to Study the Impact of Architectural and Design Choices on Wellbeing Frontiers in Sustainable Cities Altaf, B., Bianchi, E., Douglas, I. P., Douglas, K., Byers, B., Paredes, P. E., Ardoin, N. M., Markus, H. R., Murnane, E. L., Bencharit, L. Z., Landay, J. A., Billington, S. L. 2022: 19

  View details for DOI 10.3389/frsc.2022.780376

• EnglishRot: An Al-Powered Conversational System for Second Language Learning Ruan, S., Jiang, L., Xu, Q., Davis, G. M., Liu, Z., Brunskill, E., Landay, J. A., ASSOC COMP MACHINERY ASSOC COMPUTING MACHINERY. 2021: 434-444

  View details for DOI 10.1145/3397481.3450648

  View details for Web of Science ID 000747690200052

• StoryCoder: Teaching Computational Thinking Concepts Through Storytelling in a Voice-Guided App for Children Dietz, G., Le, J. K., Tamer, N., Han, J., Gweon, H., Murnane, E. L., Landay, J. A., ASSOC COMP MACHINERY ASSOC COMPUTING MACHINERY. 2021

  View details for DOI 10.1145/3411764.3445039

  View details for Web of Science ID 000758168000002

• Variational Deep Knowledge Tracing for Language Learning Ruan, S., Wei, W., Landay, J., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2021: 323-332

  View details for DOI 10.1145/3448139.3448170

  View details for Web of Science ID 000883342500031

• Personal identifiability of user tracking data during observation of 360-degree VR video. Scientific reports Miller, M. R., Herrera, F., Jun, H., Landay, J. A., Bailenson, J. N. 2020; 10 (1): 17404

  Abstract

  Virtual reality (VR) is a technology that is gaining traction in the consumer market. With it comes an unprecedented ability to track body motions. These body motions are diagnostic of personal identity, medical conditions, and mental states. Previous work has focused on the identifiability of body motions in idealized situations in which some action is chosen by the study designer. In contrast, our work tests the identifiability of users under typical VR viewing circumstances, with no specially designed identifying task. Out of a pool of 511 participants, the system identifies 95% of users correctly when trained on less than 5min of tracking data per person. We argue these results show nonverbal data should be understood by the public and by researchers as personally identifying data.

  View details for DOI 10.1038/s41598-020-74486-y

  View details for PubMedID 33060713

• Designing Ambient Narrative-Based Interfaces to Reflect and Motivate Physical Activity. Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference Murnane, E. L., Jiang, X. n., Kong, A. n., Park, M. n., Shi, W. n., Soohoo, C. n., Vink, L. n., Xia, I. n., Xin, Y. n., Yang-Sammataro, J. n., Young, G. n., Zhi, J. n., Moya, P. n., Landay, J. A. 2020; 2020

  Abstract

  Numerous technologies now exist for promoting more active lifestyles. However, while quantitative data representations (e.g., charts, graphs, and statistical reports) typify most health tools, growing evidence suggests such feedback can not only fail to motivate behavior but may also harm self-integrity and fuel negative mindsets about exercise. Our research seeks to devise alternative, more qualitative schemes for encoding personal information. In particular, this paper explores the design of data-driven narratives, given the intuitive and persuasive power of stories. We present WhoIsZuki, a smartphone application that visualizes physical activities and goals as components of a multi-chapter quest, where the main character's progress is tied to the user's. We report on our design process involving online surveys, in-lab studies, and in-the-wild deployments, aimed at refining the interface and the narrative and gaining a deep understanding of people's experiences with this type of feedback. From these insights, we contribute recommendations to guide future development of narrative-based applications for motivating healthy behavior.

  View details for DOI 10.1145/3313831.3376478

  View details for PubMedID 33880463

  View details for PubMedCentralID PMC8055101

• Adaptive Photographic Composition Guidance Jane, L. E., Fried, O., Lu, J., Zhang, J., Mech, R., Echevarria, J., Hanrahan, P., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2020

  View details for DOI 10.1145/3313831.3376635

  View details for Web of Science ID 000696109100104

• Supporting Children's Math Learning with Feedback-Augmented Narrative Technology Ruan, S., He, J., Ying, R., Burkle, J., Hakim, D., Wang, A., Yin, Y., Zhou, L., Xu, Q., AbuHashem, A., Dietz, G., Murnane, E. L., Brunskill, E., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2020: 567-580

  View details for DOI 10.1145/3392063.3394400

  View details for Web of Science ID 000675620600050

• Soundr: Head Position and Orientation Prediction Using a Microphone Array Yang, J., Banerjee, G., Gupta, V., Lam, M. S., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2020: 529-537

  Abstract

  As a lincosamide antibiotic, lincomycin is still important for treating diseases caused by Gram-positive bacteria. Manufacturing of lincomycin needs efforts to, e.g. maximize desirable species and minimizing unwanted fermentation byproducts. Analysis of the lincomycin biosynthetic gene cluster of Streptomyces lincolnensis, lmbB1, was shown to catalyze the conversion of L-dopa but not of L-tyrosine and then further generated the precursor of lincomycin A. Based on the principle of directed breeding, a strain termed as S. lincolnensis 24-2, was obtained in this work. By overexpressing the lmbB1 gene, this strain produces efficacious lincomycin A and suppresses melanin generation, whereas contains unwanted lincomycin B. The good fermentation performance of the mutant-lmbB1 (M-lmbB1) was also confirmed in a 15 L-scale bioreactor, which increased the lincomycin A production by 37.6% compared with control of 6435 u/mL and reduced the accumulation of melanin by 29.9% and lincomycin B by 73.4%. This work demonstrated that the amplification of lmbB1 gene mutation and metabolic engineering could promote lincomycin biosynthesis and might be helpful for reducing the production of other industrially unnecessary byproduct.

  View details for DOI 10.1145/3313831.3376427

  View details for Web of Science ID 000695438100099

  View details for PubMedID 31916478

• Beyond The Force: Using Quadcopters to Appropriate Objects and the Environment for Haptics in Virtual Reality Abtahi, P., Landry, B., Yang, J., Pavone, M., Follmer, S., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3290605.3300589

  View details for Web of Science ID 000474467904051

• QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge Ruan, S., Jiang, L., Xu, J., Tham, B., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3290605.3300587

  View details for Web of Science ID 000474467904049

• InfoLED: Augmenting LED Indicator Lights for Device Positioning and Communication Yang, J., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2019: 175–87

  View details for DOI 10.1145/3332165.3347954

  View details for Web of Science ID 000518189200016

• drone.io: A Gestural and Visual Interface for Human-Drone Interaction Cauchard, J. R., Tamkin, A., Wang, C., Vink, L., Park, M., Fang, T., Landay, J. A., IEEE IEEE. 2019: 153–62

  View details for Web of Science ID 000467295400022

• BookBuddy: Turning Digital Materials Into Interactive Foreign Language Lessons Through a Voice Chatbot Ruan, S., Willis, A., Xu, Q., Davis, G. M., Jiang, L., Brunskill, E., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3330430.3333643

  View details for Web of Science ID 000507611000030

• Key Phrase Extraction for Generating Educational Question-Answer Pairs Willis, A., Davis, G., Ruan, S., Manoharan, L., Landay, J., Brunskill, E., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3330430.3333636

  View details for Web of Science ID 000507611000020

• QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge Ruan, S., Jiang, L., Xu, J., Tham, B., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3290605.3300587

  View details for Web of Science ID 000474467904049

• Poirot: A Web Inspector for Designers Tanner, K., Johnson, N., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3290605.3300758

  View details for Web of Science ID 000474467906064

• Evaluating Speech-Based Smart Devices Using New Usability Heuristics IEEE PERVASIVE COMPUTING Wei, Z., Landay, J. A. 2018; 17 (2): 84–96

  View details for DOI 10.1109/MPRV.2018.022511249

  View details for Web of Science ID 000435355100012

• From on Body to Out of Body User Experience Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 1–2

  View details for DOI 10.1145/3172944.3176183

  View details for Web of Science ID 000458192600001

• Breath Booster! Exploring In-Car, Fast-Paced Breathing Interventions to Enhance Driver Arousal State Balters, S., Murnane, E. L., Landay, J. A., Paredes, P. E., ACM ASSOC COMPUTING MACHINERY. 2018: 128-137

  View details for DOI 10.1145/3240925.3240939

  View details for Web of Science ID 000614057600015

• Fast & Furious: Detecting Stress with a Car Steering Wheel Paredes, P. E., Ordonez, F., Ju, W., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2018

  View details for DOI 10.1145/3173574.3174239

  View details for Web of Science ID 000509673108018

• Gender-Inclusive Design: Sense of Belonging and Bias in Web Interfaces Metaxa-Kakavouli, D., Wang, K., Landay, J. A., Hancock, J., ACM ASSOC COMPUTING MACHINERY. 2018

  View details for DOI 10.1145/3173574.3174188

  View details for Web of Science ID 000509673107049

• FlyMap: Interacting with Maps Projected from a Drone Brock, A. M., Chatain, J., Park, M., Fang, T., Hachet, M., Landay, J. A., Cauchard, J. R. edited by Schmidt, A., Williamson, Elhart, Baldauf, M., Mikusz, M., Sorce, S., Kurdyukova, K., ElAgroudy, P., Gentile ASSOC COMPUTING MACHINERY. 2018

  View details for DOI 10.1145/3205873.3205877

  View details for Web of Science ID 000482943500013

• Aeroquake: Drone Augmented Dance Kim, H., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 691–95

  View details for DOI 10.1145/3196709.3196798

  View details for Web of Science ID 000478673400060

• Evaluating In-Car Movements in the Design of Mindful Commute Interventions: Exploratory Study. Journal of medical Internet research Paredes, P. E., Hamdan, N. A., Clark, D., Cai, C., Ju, W., Landay, J. A. 2017; 19 (12): e372

  Abstract

  The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges.This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights.We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete movements (configural or breath-based) while engaged in either simple (highway) or complex (city) simulated urban driving tasks using autonomous and manual driving modes. Then, we performed a matching exercise where participants could experience vibrotactile patterns from the back of the car seat and map them to the prior movements.We report a summary of individual perceptions concerning different movements and vibrotactile patterns. Beside describing situations within a drive when it may be more likely to perform movement-based interventions, we also describe movements that may interfere with driving and those that may complement it well. Furthermore, we identify movements that could be conducive to a more relaxing commute and describe vibrotactile patterns that could guide such movements and exercises. We discuss implications for design such as the influence of driving modality on the adoption of movement, need for personal customization, the influence that social perception has on participants, and the potential role of prior awareness of mindful techniques in the adoption of new movement-based interventions.This exploratory study provides insights into which types of movements could be better suited to design mindful interventions to reduce stress for commuters, when to encourage such movements, and how best to guide them using noninvasive haptic stimuli embedded in the car seat.

  View details for DOI 10.2196/jmir.6983

  View details for PubMedID 29203458

  View details for PubMedCentralID PMC5735252

• BrushTouch: Exploring an Alternative Tactile Method for Wearable Haptics Strasnick, E., Cauchard, J. R., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2017: 3120–25

  View details for DOI 10.1145/3025453.3025759

  View details for Web of Science ID 000426970503007

• INQUIRE Tool: Early Insight Discovery for Qualitative Research Paredes, P., Landay, J., Oikonomou, V., Guerrero, R., Yang, T., Karashchuk, P., Jiang, B., Cheshire, C., Canny, J., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2017: 29-32

  View details for DOI 10.1145/3022198.3023272

  View details for Web of Science ID 000455085000008

• Evaluating In-Car Movements in the Design of Mindful Commute Interventions Journal of Medical Internet Research (JMIR) Paredes, P. E., Hamdan, N. A., Cai, C., Clark, D., Ju, W., Landay, J. 2017: e372

  Abstract

  The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges.This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights.We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete movements (configural or breath-based) while engaged in either simple (highway) or complex (city) simulated urban driving tasks using autonomous and manual driving modes. Then, we performed a matching exercise where participants could experience vibrotactile patterns from the back of the car seat and map them to the prior movements.We report a summary of individual perceptions concerning different movements and vibrotactile patterns. Beside describing situations within a drive when it may be more likely to perform movement-based interventions, we also describe movements that may interfere with driving and those that may complement it well. Furthermore, we identify movements that could be conducive to a more relaxing commute and describe vibrotactile patterns that could guide such movements and exercises. We discuss implications for design such as the influence of driving modality on the adoption of movement, need for personal customization, the influence that social perception has on participants, and the potential role of prior awareness of mindful techniques in the adoption of new movement-based interventions.This exploratory study provides insights into which types of movements could be better suited to design mindful interventions to reduce stress for commuters, when to encourage such movements, and how best to guide them using noninvasive haptic stimuli embedded in the car seat.

  View details for DOI 10.2196/jmir.6983

  View details for PubMedCentralID PMC5735252

• ActiVibe: Design and Evaluation of Vibrations for Progress Monitoring Cauchard, J. R., Cheng, J. L., Pietrzak, T., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2016: 3261–71

  View details for DOI 10.1145/2858036.2858046

  View details for Web of Science ID 000380532903026

• Emotion Encoding in Human-Drone Interaction Cauchard, J. R., Zhai, K. Y., Spadafora, M., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2016: 263–70

  View details for Web of Science ID 000389809100036

• Drone & Me: An Exploration Into Natural Human-Drone Interaction Cauchard, J. R., Jane, L. E., Zhai, K. Y., Landay, J. A., ACM ASSOC COMPUTING MACHINERY. 2015: 361–65

  View details for DOI 10.1145/2750858.2805823

  View details for Web of Science ID 000383742200032

• Toolkit Support for Integrating Physical and Digital Interactions HUMAN-COMPUTER INTERACTION Klemmer, S. R., Landay, J. A. 2009; 24 (3): 315-366

  View details for DOI 10.1080/07370020902990428

  View details for Web of Science ID 000266871300002

• Integrating physical and digital interactions on walls for fluid design collaboration HUMAN-COMPUTER INTERACTION Klemmer, S. R., Everitt, K. M., Landay, J. A. 2008; 23 (2): 138-213

  View details for DOI 10.1080/07370020802016399

  View details for Web of Science ID 000257541400002

• The mobile sensing platform: An embedded activity recognition system IEEE PERVASIVE COMPUTING Choudhury, T., Consolvo, S., Harrison, B., LaMarca, A., LeGrand, L., Rahimi, A., Rea, A., Borriello, G., Hemingway, B., Klasnja, P. P., Koscher, K., Landay, J. A., Lester, J., Wyatt, D., Haehnel, D., Hightower, J. 2008; 7 (2): 32-41

  View details for Web of Science ID 000255249500007

• Siren: Context-aware computing for firefighting 2nd International Conference on Pervasive Computing Jiang, X. D., Chen, N. Y., Hong, J. I., Wang, K., Takayama, L., Landay, J. A. SPRINGER-VERLAG BERLIN. 2004: 87–105

  View details for Web of Science ID 000189502500006