Bio

James Landay is a Professor of Computer Science at Stanford University, specializing in human-computer interaction (HCI). Previously, Dr. Landay was a Professor of Information Science at Cornell Tech in New York City and prior to that a Professor of Computer Science & Engineering at the University of Washington. His current research interests include Technology to Support Behavior Change, Demonstrational Interfaces, Mobile & Ubiquitous Computing, and User Interface Design Tools. He is the founder and co-director of the World Lab, a joint research and educational effort with Tsinghua University in Beijing.

Dr. Landay received his BS in EECS from UC Berkeley in 1990 and MS and PhD in Computer Science from Carnegie Mellon University in 1993 and 1996, respectively. His PhD dissertation was the first to demonstrate the use of sketching in user interface design tools. He was previously the Laboratory Director of Intel Labs Seattle, a university affiliated research lab that explored the new usage models, applications, and technology for ubiquitous computing. He was also the chief scientist and co-founder of NetRaker, which was acquired by KeyNote Systems in 2004. From 1997 through 2003 he was a professor in EECS at UC Berkeley.

Academic Appointments

Administrative Appointments

  • Associate Director, Stanford Institute for Human-Centered AI (2018 - Present)

Honors & Awards

  • Fellow, ACM (2016)
  • SIGCHI Academy Member, ACM SIGCHI (2011)

Boards, Advisory Committees, Professional Organizations

  • CISE Advisory Committee Member, National Science Foundation (2010 - 2016)

Program Affiliations

  • Symbolic Systems Program

Professional Education

  • BS, UC Berkeley, Electrical Engineering & Computer Science (1990)
  • MS, Carnegie Mellon University, Computer Science (1993)
  • PhD, Carnegie Mellon University, Computer Science (1996)

Contact

  • Academic
    University - Faculty Department: Computer Science Position: Professor

Additional Info

Current Research and Scholarly Interests

Landay's current research interests include Technology to Support Behavior Change (especially for health and sustainability), Demonstrational User Interfaces, Mobile & Ubiquitous Computing, Cross-Cultural Interface Design, Human-Centered AI, and User Interface Design Tools. He has developed tools, techniques, and a top professional book on Web Interface Design.

2022-23 Courses

Stanford Advisees

All Publications

  • 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

  • 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

  • On-road Guided Slow Breathing Interventions for Car Commuters Balters, S., Landay, J. A., Paredes, P. E., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

    View details for DOI 10.1145/3290607.3312785

    View details for Web of Science ID 000482042102073

  • 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., 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

https://orcid.org/0000-0003-1520-8894