Hi! I’m Sayali Phatak.
I am a UX Researcher based in Vienna, Austria.
I’m interested in designing solutions to support individuals and communities in managing their health and well-being. I care deeply about appreciating users’ lived expertise and individual differences, and empowering people through experiences that lead to self-awareness and self-learning.
Some Past Projects
Hack Your Health: A Self-experimentation Tool for Behavioral Interventions
Hack Your Health is a self-experimentation tool that lets users try popular health-promoting activities (e.g., physical activity, meditation) to test whether the activity improves their psychological well-being. Learn more about the research process we used to design the tool.
Opening Pathways For Discovery, Research, and Innovation in Health (and Healthcare)
I was part of a RWJF-funded project that aims to explore pathways for patient-led research, discovery and innovation in the healthcare space.
I was primarily part of the on-call data science team where we provided support to a DIY Type 1 diabetes community called OpenAPS (Open Source Artificial Pancreas System) by helping members formulate their research questions, and select appropriate research methods and analyses to answer those questions.
We worked on some interesting projects with partners from the community, from exploring changes in insulin sensitivity over time to looking at changes in total daily dosage of insulin during the menstrual cycle. Learn more.
Just Walk Study: Using Control Systems Engineering Methods to Inform Adaptive Behavioral Interventions
This work uses control systems engineering methods to inform a personalized and intensively adaptive physical activity intervention. In our pilot work, we designed and deployed a smartphone app called Just Walk, and conducted a system identification experiment to develop individualized (N=1) models of physical activity measured using a Fitbit.
Through this work, we identified important time-varying variables, such as weekday/weekend, predicted busyness, etc. that seemed to influence each user’s activity levels. The long-term goal is to use such models in a model-predictive controller to then inform an app that assigns appropriate daily step goals for the user based on what the system knows about them. Learn more.
Using Proximity Sensors to Inform a Just-in-Time Intervention to Reduce Sitting Behavior at the Workplace
Mobile technologies have the capacity to track factors that are important to health like being physically active and provide customized interventions exactly when and where it would be most beneficial for each person. While this possibility exists in theory, in practice it is very hard to know when the “right” time is for delivering these sorts of messages.
Technologies such as smartwatches and indoor location sensors that can track where a person is inside buildings provide better opportunities to identity those exact moments when a person might both benefit from and be receptive to messages to help them achieve their personal goals. In this project, we used proximity sensors (iBeacon) to trigger walking prompts at the workplace. Learn more.