Biography

Kaustav Bhattacharjee is a Data Scientist at Pacific Northwest National Laboratory (PNNL) specializing in large language models, generative AI, and differential privacy techniques, with direct experience applying privacy-preserving methods to complex systems while maintaining utility. His research interests span visual analytics, data privacy, human-computer interaction, and explainable AI. 

His work on LLM-based information extraction, conversational AI interfaces for critical infrastructure analysis, and data privacy frameworks positions him to contribute meaningfully to AI safety and responsible model development. With expertise in evaluating LLM performance, designing safety-focused systems, and a track record of translating research into practical applications (including contributions recognized by federal agencies), Kaustav brings a unique combination of technical depth and practical impact to tackling frontier AI safety challenges. This expertise builds upon his doctoral research, which focused on developing interactive visual analytic workflows to mitigate uncertainty and privacy issues during the analytical process, particularly in domains such as the open data ecosystem.

Research Interests

  • Visual Analytics
  • Data Privacy
  • Explainable AI
  • Human Computer Interaction

Disciplines and Skills

  • Artificial Intelligence
  • Data Privacy
  • Human Computer Interaction
  • Open Data
  • Visual Analytics
  • Web Design

Education

  • Ph.D., Data Science Computing Option, New Jersey Institute of Technology
     
  • B.Tech., Information Technology, Maulana Abul Kalam Azad University of Technology

Affiliations and Professional Service

Professional Service

  • Treasurer, IEEE New Jersey Coast Section Young Professionals Affinity Group
  • Secretary, IEEE New Jersey Coast Section Power & Energy Society (PES) Chapter
  • Web Chair, IEEE VIS 2026 (IEEE Visualization Conference)

Program Committee (Conferences & Symposiums)

  • IEEE Visualization and Visual Analytics (VIS) (2026) (Full Paper)
  • IEEE Visualization and Visual Analytics (VIS) (2025) (Short Paper)
  • ACM Conference on Intelligent User Interfaces (IUI) (2026)
  • Workshop on Human-In-the-Loop Data Analytics (HILDA) (2026)
  • ACM International Conference on Information and Knowledge Management (CIKM) (2025) (Full Paper)
  • ACM International Conference on Information and Knowledge Management (CIKM) (2025) (Short Paper)
  • Symposium on Usable Privacy and Security (SOUPS) (2025) (Poster Jury)
  • ACM International Conference on Information and Knowledge Management (CIKM) (2024) (Full Paper)
  • ACM International Conference on Information and Knowledge Management (CIKM) (2024) (Short Paper)
  • ACM International Conference on Information and Knowledge Management (CIKM) (2024) (Demo Track)
  • Symposium on Usable Privacy and Security (SOUPS) (2024) (Poster Jury)
  • ACM International Conference on Information and Knowledge Management (CIKM) (2023) (Demo Track)

Publications

2024

  • Bhattacharjee K., S. Kundu, I. Chakraborty, and A. Dasgupta. 2024. "Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net-Load Forecasting." In IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT 2024), February 19-22, 2024, Washington, D.C., 1-5. Piscataway, New Jersey:IEEE. PNNL-SA-189754. doi:10.1109/ISGT59692.2024.10454191