Ranjitha Kumar

schoolUniversity of Illinoisbar_chart#1602 Global Rank

Total Papers

HCI Rank

#1602

Research Areas

Years Active

Recent Publications

From Code Generation to Conceptual Learning: Student Use of LLMs in a Web Programming Course

As AI-assisted coding becomes standard in software development, computer science educators need a clearer understanding of how Large Language Models (LLMs) can support the learning process. Recent work has examined how students can benefit from using LLMs in courses, but most rely on self-reported usage or controlled…

MOBILEHCI '25CorrespondingInteractive Data Visualization +1

On-Device Interaction Mining

Interaction mining is a popular technique for capturing design and interaction data while a mobile app is being used. Over the years, researchers have leveraged interaction mining systems to build large repositories of interaction data, enabling novel, ML-based tools for UX practitioners, designers, and programmers. E…

UIST '23CorrespondingExplainable AI (XAI) +1

Learning Custom Experience Ontologies via Embedding-based Feedback Loops

Companies and organizations rely on behavioral analytics tools like Google Analytics to monitor their digital experiences. Making sense of the data these tools capture, however, requires manual event tagging and filtering---often a tedious process. Prior research approaches have trained machine learning models to auto…

CSCW '21CorrespondingSocial Media

FITNet: Identifying Fashion Influencers on Twitter

The rise of social media has changed the nature of the fashion industry. Influence is no longer concentrated in the hands of an elite few: social networks have distributed power across a broader set of tastemakers. To understand this new landscape of influence, we created FITNet --- a network of 10,000 fashion-related…

UIST '21CorrespondingVoice User Interface (VUI) Design +1

App-Based Task Shortcuts for Virtual Assistants

Virtual assistants like Google Assistant and Siri often interface with external apps when they cannot directly perform a task. Currently, developers must manually expose the capabilities of their apps to virtual assistants, using App Actions on Android or Shortcuts on iOS. This paper presents SAVANT, a system that aut…

CHI '18CorrespondingGenerative AI (Text, Image, Music, Video) +1

Designing the Future of Personal Fashion

Advances in computer vision and machine learning are changing the way people dress and buy clothes. Given the vast space of fashion problems, where can data-driven technologies provide the most value? To understand consumer pain points and opportunities for technological interventions, this paper presents the results…

UIST '18CorrespondingAlgorithmic Transparency & Auditability +1

Learning Design Semantics for Mobile Apps

Recently, researchers have developed black-box approaches to mine design and interaction data from mobile apps. Although the data captured during this interaction mining is descriptive, it does not expose the design semantics of UIs: what elements on the screen mean and how they are used. This paper introduces an auto…

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