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S. Dey

4 papers hereh-index 8671 citations40 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.HC3
  • cs.CV1
same name
  • S. Dey — 33 papers, h 11
  • S. Dey — 27 papers
  • S. Dey — 18 papers, h 61
  • S. Dey — 13 papers, h 39
  • S. Dey — 10 papers, h 14
  • S. Dey — 9 papers, h 12

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.HC2026

Expecting Too Much, Getting Too Little: Exploring the Challenges and Design Opportunities of Asynchronous AI Interviewers

Md Nazmus Sakib, Naga Manogna Rayasam, Sanorita Dey

Organizations use asynchronous AI interview systems to efficiently manage large applicant pools, enabling quick and uniform evaluations. However, concerns remain about their impact…

cs.HC2025

Competing or Collaborating? The Role of Hackathon Formats in Shaping Team Dynamics and Project Choices

Sadia Nasrin Tisha, Md Nazmus Sakib, Sanorita Dey

Hackathons have emerged as dynamic platforms for fostering innovation, collaboration, and skill development in the technology sector. Structural differences across hackathon format…

cs.HC2025

ReflectEd: Evaluating Reflection-Driven Learning in an AI-Assisted System

Md Nazmus Sakib, Ishika Tarin, Naga Manogna Rayasam +2

In collaborative settings, sustaining momentum and engagement between checkpoints (e.g., meetings) can be challenging, often leading to task drift and reduced preparedness. To addr…

cs.CV2025

Analyzing the Sensitivity of Vision Language Models in Visual Question Answering

Monika Shah, Sudarshan Balaji, Somdeb Sarkhel +2

We can think of Visual Question Answering as a (multimodal) conversation between a human and an AI system. Here, we explore the sensitivity of Vision Language Models (VLMs) through…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.