Hello!
I am a mixed-method researcher. I have a background in psychology, cognitive science, and informatics, I enjoy combining the quantitative methods of psychology and informatics with qualitative methods of HCI and design. My research aims to:
1) understand human cognition and behavior better,
2) guide designers and design decisions in developing technologies.
I care a lot about the well-being of individuals and how people remember their memories :) My main research topics include human memory, technology, and well-being.
I have conducted various studies on how people remember their memories by conducting surveys, experiments, interviews, and I assessed their theory of mind skills using dynamical stimulus.
I also conducted social media analysis to determine loneliness of users, where I benefit from using NLP and web-scrapping techniques. I presented my work in Cognitive Science Conference, Midwest Cognitive Science Conference.
Besides them, during my PhD, I interviewed various peoples on their social media use, memory-aiding habits, their multimodality preferences. Benefitting from grounded theory, I developed insights and presented them as a coherent story in prestigious venues such as CHI'2024, CRA-WP Women Summit.
Awards & Fellowships
I was honored to receive the 3rd place award as the Student Research Winner at CHI'24, acknowledging the impact and quality of my work in Human-Computer Interaction. Additionally, I was awarded the $2,000 Kishor & Bhatt Fellowship at Indiana University, $930 College of Arts and Sciences Graduate student travel award, $1000 travel award from Luddy School of Informatics. I was also very lucky to receive Cognitive Science Conference Diversity and Inclusion Award ($1000) at CogSci 2023 conference. I was also selected as one of only three Summer Visiting Student Researchers at Princeton University, where I conducted a study on spontaneous human thoughts, supported by a total funding of $8,000.
Field of Study:
💻 Human - Computer Interaction
🧠 Cognitive Science
⭐Topics:
Cognition
Emotion
Human-AI
Memory
Narrative
Social Media
Senses/Modalities
Technology
Theory of Mind (ToM)
Well-being
Progress:
✅ Completed
⏯️ Ongoing
📝Methods:
Quantitative
Data Visualization
Modeling
Natural Language Processing (NLP)
Web Scraping
Network Science
Survey Design and Analysis
Qualitative
Observational Research
Interview
Thematic Analysis
Usability Testing
Systematic Review
Wizard of Oz
Talk Aloud
Prototyping
Workshop
🌀Design Thinking Stages:
Empathize
Define
Ideate
Prototype
Test
Research Methods: We conducted an online survey with qualitative and quantitative components to examine how users capture, express, and reflect on their negative memories.
Participants: The study involved 34 participants, including 8 ruminators and 8 reflectors, recruited via university research pools and online communities.
Tools & Technologies:
Python, Jamovi, (Survey analysis), Qualtrics, Thematic Coding
Challenges & Learnings:
Recruiting participants who openly discuss negative memories and collecting data in person were challenging, so we adjusted recruitment style and content of our questions.
💻 Human - Computer Interaction
⭐ Emotion Memory Technology Well-being
📝 Survey Design and Analysis Thematic Analysis
🌀 Empathize Define
⏯️ Ongoing
Overview: This study explores how people process their negative memories using technology (capture, express, share, reflect on), aiming to identify needs and design opportunities.
Research Goals:
How do people process their unpleasant memories?
How do different cognitive styles (rumination vs. reflection) impact the way people engage with technology to process their memories?
My Role: Lead researcher
Key Findings:
Different people (reflectors and ruminators) have different attitudes towards technology, and their needs differ.
They engage with memory technologies differently—reflectors do not trust the effect of technology, and they have a separate processing phase, while ruminators prefer expressive outlets and they need to communicate with others, in addition to trusting the influence of technology
Participants displayed individual and social acceptance plays a role in the processing of unpleasant memories.
Design Recommendations / Impact:
Display the need for personalized reflection tools
Display potential for various steps in processing
Deliverables:
A research report with key findings, submitted to a conference.
Research Methods: I conducted interviews with participants about their memories and asked them to describe their memories with different modalities (by providing tools such as crayons, papers, music player), and assessed their phenomenology for memories, and individual differences.
Participants:
12 participants interviewed about their autobiographical memories, using different sensory modalities for recall and expression.
Tools & Technologies:
Qualitative coding (Taguette), audio transcription, and thematic analysis for interview data.
Challenges & Learnings:
Understanding individual differences in sensory memory recall matters.
Ensuring a natural recall process while introducing different modalities is essential, especially not biasing individuals for picking some items.
Asking for before, after phenomenology ratings would be more useful and controlled to see isolated effect of the system.
Study highlights the importance of sensory-rich experiences in designing memory-supporting technologies.
💻 Human - Computer Interaction
⭐ Memory Technology Senses/Modalities Well-being
📝 Survey Design and Analysis Interview
🌀 Empathize Define
✅ Completed
Overview: This study explores which modalities (senses) people need to express their memories and how remembering with different modalities (mediums for our senses) influence our personal memories and feelings. I also investigate the role of individual differences.
Research Goals: To understand how sensory modalities shape memory recall and expression and to provide design insights for future memory technologies.
My Role: Lead researcher
Key Findings:
Participants recalled memories through multi-modalities, highlighting the influence of tangible interactions.
Expression preferences varied, with some preferring verbal storytelling while others relied on images or physical objects.
Emotion of the memory changes its needs, negative memories are not expressed with modalities.
Design Recommendations / Impact:
Develop memory technologies that incorporate multiple modalities for richer recall.
Design tools that allow users to express memories through images, sound, and tactile interactions.
Personalize memory recall systems based on users’ sensory preferences.
Deliverables:
A research framework outlining multimodal memory recall and expression.
User insights to inform future development of memory-supporting technologies.
Award: 3rd Place Winner- Student Research Competition (CHI'24)
💻 Human - Computer Interaction
⭐ Human-AI Technology Theory of Mind (ToM)
📝 Observational Research Interview Talk Aloud
🌀 Empathize Define
✅ Completed
Overview: I am working on how human and LLM interaction is influenced by their theory of mind towards each other. My insights are presented in this paper, I presented at ToM-AI Workshop at CHI'24.
Deliverables:
💻 Human - Computer Interaction
⭐ Human-AI Memory Narrative Social Media Technology
📝 Systematic Review
🌀 Empathize Define
⏯️ Ongoing
Overview: This paper explores how different technologies are designed for aiding human memory, and how technology found to be impacting human memory abilities.
Research Goals: How do computing technologies influence autobiographical memory?
My Role: Lead researcher
Key Findings:
Design Recommendations / Impact:
Deliverables:
💻 Human - Computer Interaction
⭐ Human-AI Memory Technology
📝 Systematic Review
🌀 Empathize Define
✅ Completed/Submitted
Overview: This paper explores the scope of existing memory technologies in the HCI field.
Research Goals: What is the focus of existing memory technologies?
My Role: Lead researcher
Key Findings:
Design Recommendations / Impact:
Deliverables:
Usability Testing: Conducted 15 sessions with real-world users.
Tasks: search for article, search for an event, and search for a research to participate.
Cognitive Walkthrough Protocol: Collected qualitative insights on user experiences.
Post-Test Surveys & Interviews: Gathered feedback on the app.
15 participants (African American, elderly) who are caretakers of Alzheimer's disease patients, recruited through community outreach.
Otter.ai (transcription)
Taguette (qualitative coding)
Recruiting diverse participants required targeted outreach and community partnerships.
Users needed breaks in between sessions to not induce fatigue.
💻 Human - Computer Interaction
⭐ Human-AI Memory Technology
📝 Usability Testing Wizard of Oz Prototyping
🌀 Prototype Test
✅ Completed/Submitted
Overview: This is a bigger project (consisting of prototyping, designing, and testing). Conducted usability testing to assess the accessibility and cultural fit of a multimodal AI-powered health app designed for medical information-seeking among diverse users. Findings were published in JMIR mHealth and uHealth.
Research Goals:
How usable/accessible/culturally relevant/easily adoptable is this multimodal AI-powered health app for elderly and African American participants?
What barriers exist in AI-driven health information-seeking?
My Role: Collaborator
Key Findings:
Elderly participants faced challenges with voice interaction due to unclear prompts and complex phrasing.
Users preferred a mix of voice and text input for better accessibility.
African American participants highlighted concerns about AI bias and trust in medical recommendations.
Design Recommendations / Impact:
Simplify voice interactions with clear, step-by-step guidance.
Implement transparency features (e.g., source citations) to build trust.
Develop culturally responsive AI assistants by integrating diverse datasets and inclusive language.
Deliverables:
NLP, data analysis, data visualization
203 Reddit posts from October 2022 to October 2023, focusing on self-managed abortion in the U.S.
12 workshop participants for design iterations
Python (web scraping, text analysis), R (statistical analysis), Miro, Canva, Zoom.
Challenges & Learnings:
Navigating ethical considerations in analyzing sensitive online discussions.
Filtering relevant posts while maintaining user anonymity.
Recognizing the critical role of online communities in healthcare access.
💻 Human - Computer Interaction
⭐ Narrative Social Media
📝 Web Scraping Observational Research Workshop Wizard of Oz
🌀 Define
✅ Completed/Submitted
Overview: This study examines how individuals use the subreddit r/abortion to seek information on self-managed abortion post-Dobbs, focusing on procedural, legal, and experiential aspects. It's follow-up study also includes designing a workshop and talking with women about their experiences on interacting with prototype website for abortion-information seeking.
Research Goals:
To analyze the types of information sought regarding self-managed abortion and identify patterns in discussion, emotional tone, and linguistic features to identity needs of individuals.
Iterating design prototypes for abortion information website and testing its usability with workshops.
My Role: Collaborator responsible for data scraping, quantitative analysis, and writing.
Key Findings:
Users seek information on procedure and post-abortion care , legal and logistical concerns, and share personal experiences.
The subreddit acts as both an informational resource and an emotional support space.
People prefer seriousness in design, and fast access to information.
Design Recommendations / Impact:
Develop more accessible, reliable online resources on self-managed abortion.
Create digital tools for structured information-sharing and emotional support.
Improve moderation and content accuracy in online abortion discussions.
Deliverables:
Two research papers are submitted to a journal and currently under review.
🧠 Cognitive Science
⭐ Cognition
📝 Data Visualization Natural Language Processing (NLP) Modeling Web Scraping
🌀Empathize
✅ Completed
Overview: The human mind generates a continuous stream of spontaneous thoughts (STs), yet little is known about their structural flow. This study investigates whether STs follow structured cognitive patterns or transition randomly.
Deliverables:
Presentation at Princeton University.
Presentation at SPSP (Society for Personality and Social Psychology Conference).
🧠 Cognitive Science
⭐ Cognition Emotion Human-AI Narrative
📝 Data Visualization Natural Language Processing (NLP) Survey Design and Analysis
🌀Empathize
✅ Completed
Overview: Humans retell stories all the time. But how about ChatGPT? Can we rely on their skills, or gain insights toward human cognition? This project, published in Nature Scientific Reports on ChatGPT and human retellings revealed linguistic differences but an emotional stability in retellings told by humans vs. ChatGPT.
Deliverables:
🧠 Cognitive Science
⭐ Emotion Human-AI Narrative Social Media Well-being
📝 Data Visualization Natural Language Processing (NLP) Survey Design and Analysis Web Scraping
🌀Empathize
✅ Completed
Overview: We are comparing the language of lonely vs. control group in Twitter with NLP and computational techniques. Turns out we can understand if people are lonely by looking at their tweets!
Deliverables:
🧠 Cognitive Science
⭐ Cognition Emotion Human-AI Narrative
📝 Data Visualization Natural Language Processing (NLP) Survey Design and Analysis
🌀Empathize
⏯️ Ongoing
Overview: We are examining meaningful life episodes of individuals and the role of feedback received in social media --> no spoiler about the hypotheses yet!
PS. one of my meaningful life episodes on the right.
🧠 Cognitive Science
⭐ Memory Theory of Mind (ToM)
📝 Data Visualization Survey Design and Analysis
🌀Empathize
⏯️ Ongoing
Overview: We aim to understand the relation between theory of mind and autobiographical memory skills. In simple worlds, we question how our understanding of what others think affects our personal memories.