Publications

• 2025
• Bhattacharjee, Kaustav, Soumya Kundu, Indrasis Chakraborty and Aritra Dasgupta. "Who should I trust? A Visual Analytics Approach for Comparing Net Load Forecasting Models." In Proceedings of 2025 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge). [in publication] [arXiv version]

• 2024
• Yang, Ruyi, Jingyu Hu, Zihao Li, Jianli Mu, Tingzhao Yu, Jiangjiang Xia, Xuhong Li, Aritra Dasgupta, and Haoyi Xiong. "Interpretable machine learning for weather and climate prediction: A review." Atmospheric Environment (2024): 120797. [paper]


• Koli, Vrushali, Jun Yuan, and Aritra Dasgupta. "Sensemaking of Socially-Mediated Crisis Information." In Proceedings of the Third Workshop on Bridging Human--Computer Interaction and Natural Language Processing, pp. 74-81. 2024. [paper]


• Wenskovitch, John, Corey Fallon, Kate Miller, and Aritra Dasgupta. "Characterizing Interaction Uncertainty in Human-Machine Teams." In Proceedings of 2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS), pp. 1-6. IEEE, 2024. [paper]


• Bhattacharjee, Kaustav, Soumya Kundu, Indrasis Chakraborty and Aritra Dasgupta. "Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net Load Forecasting." In Proceedings of 2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), pp. 1-5. IEEE, 2024. [paper]

• 2023
• Yuan, Jun, and Aritra Dasgupta. "A Simple Scoring Function to Fool SHAP: Stealing from the One Above." In Proceedings of the NeurIPS 2023 Workshop on XAI in Action [paper]


• Yuan Jun, Kaustav Bhattacharjee, Akm Zahirul Islam and Aritra Dasgupta. "TRIVEA: Transparent Ranking Interpretation using Visual Explanation of black-box Algorithmic rankers." In Visual Computer (2023), doi: https://doi.org/10.1007/s00371-023-03055-x. [paper]


• Bhattacharjee, Kaustav, and Aritra Dasgupta. "VALUE: Visual Analytics driven Linked data Utility Evaluation." In Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA), ACM, 2023, doi: https://doi.org/10.1145/3597465.3605225. [paper]


• Yuan, Jun, and Aritra Dasgupta. "A Human-in-the-loop Workflow for Multi-Factorial Sensitivity Analysis of Algorithmic Rankers." In Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA), ACM, 2023, doi: https://doi.org/10.1145/3597465.3605221. [paper]


• Chakraborty, Indrasis, Aritra Dasgupta, Javier Rubio-Herrero, Sai Pushpak Nandanoori, Soumya Kundu and Vikas Chandan. "Application of Machine Learning for Energy-Efficient Buildings." In: Fathi, M., Zio, E., Pardalos, P.M. (eds) Handbook of Smart Energy Systems. Springer, Cham. doi:https://doi.org/10.1007/978-3-030-72322-4_102-1 [paper]


• Sloane, Mona, Ian René Solano-Kamaiko, Jun Yuan, Aritra Dasgupta, and Julia Stoyanovich. "Introducing contextual transparency for automated decision systems." Nature Machine Intelligence (2023): 1-9. [paper]


• Bhattacharjee, Kaustav, and Aritra Dasgupta. "Power to the Data Defenders: Human-Centered Disclosure Risk Calibration of Open Data." 2023 Symposium on Usable Security and Privacy (USEC)(2023), doi: https://dx.doi.org/10.14722/usec.2023.237256. [paper]

• 2022
• Bhattacharjee, Kaustav, Akm Islam, Jaideep Vaidya, and Aritra Dasgupta. "PRIVEE: A Visual Analytic Workflow for Proactive Privacy Risk Inspection of Open Data." 2022 IEEE Symposium on Visualization for Cyber Security (VizSec), Oklahoma City, OK, USA, 2022, pp. 1-11, doi: https://doi.org/10.1109/VizSec56996.2022.9941431. [paper]


• Yuan, Jun, Julia Stoyanovich, and Aritra Dasgupta. "Rankers, Rankees, & Rankings: Peeking into the Pandora's Box from a Socio-Technical Perspective." Position paper presented at 2022 CHI Workshop on Interrogating Human-Centered Data Science (2022). [paper]

• 2021
• Vaidya, Sahaj, Jie Cai, Soumyadeep Basu, Azadeh Naderi, Donghee Yvette Wohn, and Aritra Dasgupta. "Conceptualizing Visual Analytic Interventions for Content Moderation." In Proceedings of 2021 IEEE Visualization Conference (VIS), IEEE, 2021. [paper]


• Wenskovitch, John, Corey Fallon, Kate Miller, and Aritra Dasgupta. "Beyond Visual Analytics: Human-Machine Teaming for AI-Driven Data Sensemaking."Proc. of IEEE VIS 2021 Workshop on Trust and Expertise in Visual Analytics, 2021. [paper]
• 2020
• Vaidya, Sahaj, and Aritra Dasgupta. "Knowing what to look for: A Fact-Evidence Reasoning Framework for Decoding Communicative Visualization." In 2020 IEEE Visualization Conference (VIS), pp. 231-235. IEEE, 2020. [paper]


• Islam, Akm, and Aritra Dasgupta. "UrbanForest: Seeing the data forest despite the trees." In IEEE Visualization Conference (VIS) 2020 Posters, 2020 [paper]


• Bhattacharjee, Kaustav, Min Chen, and Aritra Dasgupta. "Privacy‐Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities." Computer Graphics Forum 39.3 (2020): 675-92. [paper]


• Dasgupta, Aritra, Jorge Poco, Bernice Rogowitz, Kyungsik Han, Enrico Bertini, and Claudio T. Silva. “The Effect of Color Scales on Climate Scientists’ Objective and Subjective Performance in Spatial Data Analysis Tasks.” IEEE Transactions on Visualization and Computer Graphics 26, no. 3 (2018): 1577-1591. doi:https://doi.org/10.1109/tvcg.2018.2876539. [paper]


• Dasgupta, Aritra, Hong Wang, Nancy O'brien, and Susannah Burrows. "Separating the Wheat from the Chaff: Comparative Visual Cues for Transparent Diagnostics of Competing Models." IEEE Transactions on Visualization and Computer Graphics 26.1 (2020): 1043-053. [paper]


• 2019
• Dasgupta, Aritra, Robert Kosara, and Min Chen. "Guess Me If You Can: A Visual Uncertainty Model for Transparent Evaluation of Disclosure Risks in Privacy-Preserving Data Visualization." In 2019 IEEE Symposium on Visualization for Cyber Security (VizSec), pp. 1-10. IEEE, 2019. doi:https://doi.org/10.1109/VizSec48167.2019.9161608 [paper]


• 2018
• Burrows, Susannah M., Aritra Dasgupta, Sarah Reehl, Lisa Bramer, Po-Lun Ma, Philip J. Rasch, and Yun Qian. "Characterizing the Relative Importance Assigned to Physical Variables by Climate Scientists When Assessing Atmospheric Climate Model Fidelity." Advances in Atmospheric Sciences 35.9 (2018): 1101-113. [paper]


• Dasgupta, Aritra, Meg Pirrung, Joe Bruce, Jean Scholtz, Kyungsik Han, and Dustin Arendt. "Bridging Computation and Visual Communication of Change using Levels of Abstraction." IEEEVIS Workshop on Visual Communication (2018). [paper]


• Dasgupta, Aritra. "Experts’ Familiarity Versus Optimality of Visualization Design: How Familiarity Affects Perceived and Objective Task Performance." Cognitive Biases in Visualizations (2018): 75-86. Print. [paper]


• Felix, Cristian, Aritra Dasgupta, and Enrico Bertini. "The Exploratory Labeling Assistant: Mixed-Initiative Label Curation with Large Document Collections." In Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology, pp. 153-164. 2018. doi:https://doi.org/10.1145/3242587.3242596 [paper]


• Dasgupta, Aritra, Dustin L. Arendt, Lyndsey R. Franklin, Pak Chung Wong, and Kristin A. Cook. "Human factors in streaming data analysis: Challenges and opportunities for information visualization." In Computer graphics forum, vol. 37, no. 1, pp. 254-272. 2018. doi:https://doi.org/10.1111/cgf.13264 [paper]