PhD, Human Computer Interaction/SE
Curious about Cognition
Hi! I'm Souti. You can call me Rini! I am an HCI and UX Researcher, investigating human aspects in Software Engineering and Data Science to design human-centered tools that improve User Experience and Productivity. My award-winning research leverages findings from Cognitive Psychology using Empirical Qualitative and Quantitative Methods, and Analysis of User Data using Statistics and ML to drive impactful change to real-world products. Thank you for visiting my research page!
In 2022, I am actively looking for jobs.
Outside of work, I am passionate about music and matcha! Drop and email or DM and I would love to chat with you!
Research Projects and Developed Tools
Cognitive Processes in Computing
Programming is a complex cognitive activity, involving many sub-processes that don't fit under the theoretical frameworks. One such process is the rapid contextual switch programmers encounter. Through field observations, contextual interviews, and confirmatory surveys, I studied how developers preserve the relevant information across tasks resulting in two papers at CHASE'18, ICSE'19. Based on these patterns with which programmers' brains access information, we built a lo-fi prototype of a card-based developer environment (IDE) that provides artifacts in context. We developed the IDE interface and evaluated it using controlled lab study with A/B testing with other IDEs. The results are published in VLHCC'20 and we continued to improve the IDE. The beta version is available here.
However, cognitive processes are not straightforward, and not every information brain uses leads to an optimal approach. One such process is the presence of cognitive biases - deviations from optimal reasoning. Through observational studies and retrospective interviews, I investigate how biases affect developer decisions and productivity ICSE'20. We found around 45% of developers' actions are likely to be associated with a bias, 70% of which were likely to be undone. That takes 25% of developers' work time. This research was recognized with the ACM Distinguished Paper Award(given to top 10 papers every year) and featured as a Research Highlights by Communications of ACM (only ~25 papers per year given this recognition). The research also contributed in bringing 1.2 million USD in NSF Funding in a cross-university collaboration.
Decision Making in Data Science
How do data scientists make the journey from data to insights? Although analysis decisions can be intuitive to an expert, how do they make decisions about verifying hypotheses? Learning this decision-making process can help end-user and novice data scientists to make meaningful inferences from data.
Through field observations with data scientists at Microsoft and semi-structured interviews with data scientists from Microsoft and cross-functional industries like finance and industry, we identified 10 major challenges data scientists face with current tools published at CHI 2020. The research was awarded the Honourable Mention Award by ACM SIGCHI (given to top 5% papers every year).
With a validation survey with 150+ data scientists at Microsoft, we identified 4 high-impact activities that are both important and difficult and discussed design opportunities for tools. The design opportunities we discussed inspired features in mainstream notebooks like Deepnote and the breadth of challenges discussed was featured in Nature Magazine article. The research further inspired a 1.2 million USD NSF funding in a cross-university, cross-continent collaboration (under review).