Aritra Dasgupta
Aritra Dasgupta
Assistant Professor, Data Science
5116 Guttenberg Information Technologies Center
Education
Ph.D.; University of North Carolina at Charlotte; Computer Science; 2012
M.S.; University of North Carolina at Charlotte; Computer Science; 2008
B.Tech.; West Bengal University of Technology; Information Technology; 2005
M.S.; University of North Carolina at Charlotte; Computer Science; 2008
B.Tech.; West Bengal University of Technology; Information Technology; 2005
Past Courses
CS 450: DATA VISUALIZATION
DS 650: DATA VISUALIZATION AND INTERPRETATION
IS 247: DESIGNING THE USER EXPERIENCE
IS 331: DATABASE DESIGN, MGMT & APPL
IS 650: DATA VISUALIZATION & INTERPRET
IS 650: DATA VISUALIZATION AND INTERPRETATION
IS 657: SPATIOTEMPORAL URBAN ANALYTICS
IS 698: ST: DATA VISUALIZATION AND INTERPRETATION
DS 650: DATA VISUALIZATION AND INTERPRETATION
IS 247: DESIGNING THE USER EXPERIENCE
IS 331: DATABASE DESIGN, MGMT & APPL
IS 650: DATA VISUALIZATION & INTERPRET
IS 650: DATA VISUALIZATION AND INTERPRETATION
IS 657: SPATIOTEMPORAL URBAN ANALYTICS
IS 698: ST: DATA VISUALIZATION AND INTERPRETATION
Conference Proceeding
Knowing what to look for: A Fact-Evidence Reasoning Framework for Decoding Communicative Visualization
2020
Privacy-Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities
2020
Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling
2020
UrbanForest: Seeing the data forest despite the trees
2020
Guess Me If You Can: A Visual Uncertainty Model for Transparent Evaluation of Disclosure Risks in Privacy-Preserving Data Visualization
2019
2020
Privacy-Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities
2020
Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling
2020
UrbanForest: Seeing the data forest despite the trees
2020
Guess Me If You Can: A Visual Uncertainty Model for Transparent Evaluation of Disclosure Risks in Privacy-Preserving Data Visualization
2019
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Journal Article
Dasgupta, Aritra, & Wang, Hong, & Nancy, O'Brien, & Burrows, Susannah (2019). Separating the Wheat from the Chaff : Comparative Visual Cues for Transparent Diagnostics of Competing Models. IEEE Transactions on Visualization and Computer Graphics,
Dasgupta, Aritra, & Poco, Jorge, & Rogowitz, Bernice, & Han, Kyungsik, & Bertini, Enrico, & Silva, Claudio (2019). The Effect of Color Scales on Climate Scientists' Objective and Subjective Performance in Spatial Data Analysis Tasks. IEEE transactions on visualization and computer graphics,
Burrows, Susannah, & Dasgupta, Aritra, & Reehl, Sarah, & Bramer, Lisa, & Ma, Po-Lun, & Rasch, Philip, & Qian, Yun (2018). Characterizing the relative importance assigned to physical variables by climate scientists when assessing atmospheric climate model fidelity. Advances in Atmospheric Sciences, 35(9), 1101--1113.
Dasgupta, Aritra, & Lee, Joon-Yong, & Wilson, Ryan, & Lafrance, Robert, & Cramer, Nick, & Cook, Kristin, & Payne, Samuel (2017). Familiarity Vs Trust: A Comparative Study of Domain Scientists’ Trust in Visual Analytics and Conventional Analysis Methods. IEEE Transactions on Visualization \& Computer Graphics(1), 1--1.
Dasgupta, Aritra, & Poco, Jorge, & Bertini, Enrico, & Silva, Claudio (2016). Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study. Computing in Science and Engineering, 18, 92--100.
Dasgupta, Aritra, & Poco, Jorge, & Rogowitz, Bernice, & Han, Kyungsik, & Bertini, Enrico, & Silva, Claudio (2019). The Effect of Color Scales on Climate Scientists' Objective and Subjective Performance in Spatial Data Analysis Tasks. IEEE transactions on visualization and computer graphics,
Burrows, Susannah, & Dasgupta, Aritra, & Reehl, Sarah, & Bramer, Lisa, & Ma, Po-Lun, & Rasch, Philip, & Qian, Yun (2018). Characterizing the relative importance assigned to physical variables by climate scientists when assessing atmospheric climate model fidelity. Advances in Atmospheric Sciences, 35(9), 1101--1113.
Dasgupta, Aritra, & Lee, Joon-Yong, & Wilson, Ryan, & Lafrance, Robert, & Cramer, Nick, & Cook, Kristin, & Payne, Samuel (2017). Familiarity Vs Trust: A Comparative Study of Domain Scientists’ Trust in Visual Analytics and Conventional Analysis Methods. IEEE Transactions on Visualization \& Computer Graphics(1), 1--1.
Dasgupta, Aritra, & Poco, Jorge, & Bertini, Enrico, & Silva, Claudio (2016). Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study. Computing in Science and Engineering, 18, 92--100.
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Chapter
Dasgupta, Aritra (2018). Experts’ Familiarity Versus Optimality of Visualization Design: How Familiarity Affects Perceived and Objective Task Performance, Springer, Cham. (pp. 75--86). Springer, Cham