Postdoctoral Researcher
University of Massachusetts Amherst  

I graduated with a PhD in Information Systems from the School of Information Systems, Singapore Management University. My research area is in Software & Cyber-Physical Systems, with interests in Psychology and Organizational Behavior. I focus primarily on large-scale behavioural research, which explores the use of mobile sensor data to understand human behaviour. My work involves developing smart systems that quantify user routines and social interactions in real-time to derive predictive insights for health and wellbeing purposes. Accordingly, these approaches can be used to develop effective risk-screening and intervention-assessments at scale for everyday users. In the future, I hope to explore the full multi-disciplinary pipeline of integrating such technologies to understand the outcomes on different levels of human services: the individual, group, organization and community.



  1. Zakaria, C., Trivedi, A., Cecchet, E., Chee, M., Shenoy, P., & Balan, R. (2021). Analyzing the Impact of Covid-19 Control Policies on Campus Occupancy and Mobility via Passive WiFi Sensing. arXiv preprint arXiv:2005.12050. - in review

  2. Mammen, P., Zakaria, C., Trivedi, A., Shenoy, P., Balan, R. (2021). WiSleep: Scalable Sleep Monitoring and Analytics Using Passive WiFi Sensing. arXiv preprint arXiv:2102.03690. - in review 

  3. Zakaria, C., Balan, R., Lee, Y. (2021). Detection of Students' Workgroup Identification using Passively Sensed WiFi Infrastructure. Proceedings of the ACM on Human-Computer Interaction, (CSCW).

  4. Trivedi, A., Zakaria, C., Balan, R., & Shenoy, P. (2021). WiFiTrace: Network-based Contact Tracing for Infectious DiseasesUsing Passive WiFi Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, (IMWUT).

  5. Zakaria, C., Balan, R., Lee, Y. (2019). StressMon: Scalable Detection of Perceived Stress and Depression Using Passive Sensing of Changes in Work Routines and Group Interactions. Proceedings of the ACM on Human-Computer Interaction, (CSCW).

  6. Zakaria, C., Goh, K., Lee, Y., & Balan, R. (2019, June). Exploratory Analysis of Individuals' Mobility Patterns and Experienced Conflicts in Workgroups. In Proceedings of the 5th ACM Workshop on Mobile Systems for Computational Social Science (pp. 27-31). ACM.

  7. Roy, Q., Zakaria, C., Perrault, S., Nancel, M., Kim, W., Misra, A., & Cockburn, A. (2019). A Comparative Study of Pointing Techniques for Eyewear Using a Simulated Pedestrian Environment.

  8. Zakaria, C., Davis, R. C., & Walker, Z. (2016, June). Seeking independent management of problem behavior: A proof-of-concept study with children and their teachers. In Proceedings of the The 15th International Conference on Interaction Design and Children (pp. 196-205). ACM.

  9. Jayarajah, K., Radhakrishnan, M., & Zakaria, C. (2016, September). Duplicate issue detection for the Android open source project. In Proceedings of the 5th International Workshop on Software Mining (pp. 24-31). ACM.

  10. Davis, R. C., & Zakaria, C. (2014). K-Sketch: Digital Storytelling with Animation Sketches. In Interactive Storytelling (pp. 242-245). Springer International Publishing.


  1. Zakaria, C., Goh, K., Lee, Y., Balan, R. (2019). DEMO: Passive Detection of Perceived Stress Using Location-driven Sensing Technologies at Scale (MobiSys'19)

  2. Zakaria, C., & Davis, R. C. (2016). DEMO: Wearable Application to Manage Problem Behavior in Children with Neurodevelopmental Disorders (MobiSys'16)



StressMon (previously known as StressAssess@Campus) has undergone validation from two phases of longitudinal study between Spring'18 to Fall'18 since the making of this video. Future development of this work includes extending passive-sensing capabilities to understand measures of social interaction and well-being such as social identification and sleep.

WatchMe is a first PhD work, close to my heart. This work is built on sufficient progress in mobile sensing and HCI to assume that wearable devices can detect the physical movements and sounds in most problem behaviours. For example, I am using the accelerometer for hand gesture recognition and microphone for detecting vocalizations. I hope to continue this work on building an independent behaviour management tool that provides effective intervention to child users only when it is necessary.

I am just beginning with projects centred on healthy and safe living for the older adult population. In my current appointment at SUTD, I work with a team of researchers to develop wearable-sensing applications to assist the users in getting the help they need for day-to-day concerns.