Dipto Barman

Papers

Total Citations

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About

Dipto Barman is a rising researcher at the forefront of context-aware user modelling and human-computer interaction. His work centers on how systems can intelligently interpret and leverage contextual information—such as location, activity, and social setting—to deliver deeply personalised user experiences. Barman’s major contribution lies in advancing the theoretical and practical frameworks for representing context in computational models, a critical challenge as smart applications proliferate. He organised and chaired the First ACM Workshop on Context Representation in User Modelling (CRUM 2023), held alongside the 31st ACM Conference on User Modeling, Adaptation and Personalization. This landmark workshop brought together leading experts to address the nuances of capturing dynamic, multi-faceted user contexts. While his most cited paper from this workshop has garnered 2 citations to date, its significance extends beyond raw numbers: it established a foundational agenda for an emerging subfield. Barman’s work is particularly impactful for students and researchers developing next-generation adaptive systems, from intelligent assistants to context-aware recommendation engines. His efforts are shaping how the research community thinks about the subtle interplay between user behaviour and environmental cues.