Portrait of Subham Sah

Hi, I'm Subham Sah

Researcher in visual analytics and human-computer interaction
University of North Carolina at Charlotte

I study how people make sense of data, and how the design of visualizations and language-based interfaces can support more accurate, reflective decision-making. My research sits at the intersection of visual analytics, human-computer interaction, and natural language interfaces, with a particular interest in belief updating, uncertainty, and human-centered uses of large language models.

I work with collaborators in computing and cognitive science at UNC Charlotte. Recent projects examine how data visualizations can correct partisan misperceptions, how elicitation and narrative framing change engagement with data-driven news, and how large language models can translate natural-language questions into inspectable analytic specifications for visualization.

Research interests

Visual analytics; uncertainty visualization; agentic AI; human-centered AI agents; natural language interfaces for visualization; social media data exploration; judgment and decision making.

  • Visual analytics
  • HCI
  • NLP interfaces
  • Uncertainty visualization
  • Agentic AI
  • Human-centered AI agents

News

  • Our paper Prediction market visualizations, betting, and uncertainty: A study of Reddit Posts and Comments appears in IEEE VIS Uncertainty Visualization: How to Make it Interpretable, Integrable, and Accessible?.
  • Presented a poster at the ThinkAI Symposium 2026 on The application and development of AI Models on studying leaders’ and followers’ use of emotional expressions in virtual meetings, including AI-based methods to capture emotional behavior as it unfolds over time for a more behaviorally grounded and temporally sensitive understanding of leadership interactions.
  • Received the Faculty Runner-Up Award from the School of Data Science at UNC Charlotte for work on Leading and following with emotion: An investigation of Emotional Expression in Virtual Meeting.
  • Our paper on using data visualizations to correct political misperceptions appears in IEEE Transactions on Visualization and Computer Graphics.
  • Presented NL4DV-LLM at the NLVIZ Workshop at IEEE VIS 2024.
  • Paper on elicitation and contrasting narratives in data-driven news published in IEEE TVCG and presented at IEEE VIS 2024.

Publications

  1. Prediction market visualizations, betting, and uncertainty: A study of Reddit Posts and Comments

    Subham Sah, Alireza Karduni, Douglas Markant, and Wenwen Dou.

    IEEE VIS Uncertainty Visualization Workshop, 2026.

  2. Correcting Misperceptions at a Glance: Using Data Visualizations to Reduce Political Sectarianism

    Douglas Markant, Subham Sah, Alireza Karduni, Milad Rogha, My Thai, and Wenwen Dou.

    IEEE Transactions on Visualization and Computer Graphics, 32(1), 1361–1371, 2026.

  3. Generating Analytic Specifications for Data Visualization from Natural Language Queries using Large Language Models

    Subham Sah, Rishab Mitra, Arpit Narechania, Alex Endert, John Stasko, and Wenwen Dou.

    NLVIZ Workshop, IEEE VIS, 2024.

  4. The Impact of Elicitation and Contrasting Narratives on Engagement, Recall and Attitude Change with News Articles Containing Data Visualization

    Milad Rogha, Subham Sah, Alireza Karduni, Douglas Markant, and Wenwen Dou.

    IEEE Transactions on Visualization and Computer Graphics, 30(7), 4375–4389, 2024.

  5. Interactive Topic Guided Thematic Analysis for Social Media Data

    Subham Sah.

    M.S. thesis, University of North Carolina at Charlotte, 2022.

Selected research

Awards and recognition