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Tera Marie Greensmith (Green)

Tera is currently a Principal Data Scientist at AT&T Mobility, where she extends her graduate studies by studying human behavior in a Big Data environment (More information can be found here.)

Tera holds a PhD, summa cum laude, and was under the senior supervision of Brian D. Fisher, Ph.D. Her research was centered in applied cognitive science for visual analytics, with a emphasis on the roles and impact of individual differences on complex cognition, the mechanization of complex reasoning, the development of cognitive models for mixed initiative interfaces, and the use of intelligent agents in the creation of intuitive visual analytics interfaces.

Tera holds a B.A. summa cum laude from the University of North Carolina at Charlotte in Psychology, with minor in Cognitive Science (2008). Undergraduate research was conducted largely out of the Charlotte Visualization Center under the mentorship William Ribarsky, Ph.D., Director of the Charlotte Visualization Center and Chair, Department of Computer Science. Undergradate projects included the creation of the Human Cognition Model, a descriptive framework and research agenda, and early work in comparative studies of human learning and interaction behaviours.

Projects:

● Personal Equation of Interaction (PEI): Individual differences as predictors of interactive interface learning (as PI). Experimental studies to isolate which inherent individual differences, such as personality, self-belief factors, and other cognitive proclivities predict interface interaction and complex cognitive performance. Creation and validation of predictive measures for specific genres of learning and reasoning. Creation of fuller-bodied user profiles based on inherent differences.

● ALIDA: Active Learning Intent Discerning Agent: Intelligent agents for discernment and prediction of user intent in visualization interaction. (as Principal Investigator (PI)). Creation of autonomous agents which use machine learning and rule-based models to ascertain and anticipate the interest and goal behaviors of users in visual analytics interfaces.

● Use of interactive visualization as an analytical tool for flow cytometry. (with Richard Arias-Hernandez and Brian Fisher PhDs.) Expert domain case studies to assess the value of Principal Component Analysis visualization in flow cytometric analysis, which an eye toward more generalizeable design guidelines. Funded in part by US Department of Homeland Security International Program grant "Deriving and Applying Cognitive Principles for Human/Computer Approaches to Complex Analytical Problems.

Refereed Journal and Conference Publications:

  1. R. Arias-Hernandez, T.M. Green, and B. Fisher. "From cognitive amplifiers to cognitive prostheses: understandings of the material basis of cognition in visual analytics". In: Carusi, A. and Sissel Hoel, A. (Eds.), Computational picturing, imaging and visualising. Special Issue for Interdisciplinary Science Reviews 37(1). Maney Publishing: London, UK. (2012)
  2. T.M. Green, R. Arias-Hernandez, and B. Fisher. "Individual differences and translational science for human centric visualizations." In W. Wang,( Ed.) Human Centric Visualization. (in press)
  3. T.M. Green and R. Maciejewski. "The Role of Reasoning in Visual Analytics." Hawaii International Conference on System Sciences 2013. (under review).
  4. T.M. Green and B. Fisher. "Impact of personality factors on interface interaction and development of user profiles: Next steps in the Personal Equation of Interaction" Information Visualization. 11(2). 1 -17. (2012).
  5.  B. Fisher, T.M. Green, and  R. Arias-Hernandez. "Visual analytics as a translational cognitive science," Topics in Cognitive Science 3(3), M. Hagarty, (Ed.) 609-625. (2011).
  6. T.M. Green and B. Fisher, "The personal equation of complex individual cognition during visual interfac interaction," Human Aspects of Visualization: Second IFIP WG 13.7 Workshop on Human-Computer and Visualization, HCIV (INTERACT) 2009: Lecture Notes in Computer Science, A. Ebert, A. Dix, N.D. Gershon and M. Pohl, Eds.. 38-57. (2011).

  7. R. Arias-Hernandez, J. Dill, T.M. Green, and B. Fisher.   “Visual Analytics and Human Computer Interaction,” Interactions, Vol. 18, No. 1, January-February, 2011, pp. 51-55. Association for Computing Machinery. (2011).

  8. T.M. Green, R. Wakkary, and R. Arias-Hernandez, “Expanding the scope: Interaction Design perspectives for visual analytics,” Proceedings of Hawai’I International Conference on System Sciences 44, January 2011, Koloa, Hawai’i. (2011).
  9. R. Arias-Hernandez, L.Kaastra, T.M. Green and  B. Fisher,, "Pair Analytics: Capturing Reasoning Processes in Collaborative Visual Analytics," Proceedings of Hawai’I International Conference on System Sciences 44, January 2011, Koloa, Hawai’i. (2011).
  10. T.M. Green and B. Fisher, “The personal equation of complex individual cognition during visual interface interaction”, INTERACT '09: Lecture Notes in Computer Science. M. Pohl, A. Dix, A. Ebert and N. Gershon (Eds.)   (2010).
  11. T.M. Green and B. Fisher, “Towards the Personal Equation of Interaction: The impact of personality factors on visual analytics interface interaction, “  IEEE Visual Analytics Science and Technology (VAST) 2010. (2010).
  12. T.M. Green, D.H. Jeong, and B. Fisher. “Using personality factors to predict interface learning performance,” Proceedings of Hawai’i International Conference on System Sciences 43, January 2010, Koloa, Hawai’i, USA. 1-10 (2010).  (Won Best Paper in Track)
  13. D.H. Jeong, T.M. Green, W. Ribarsky, and R. Chang (2010). “Comparative evaluation of two interface tools in performing visual analytics tasks,” Proceedings of BELIV workshop, ACM SIG CHI 2010, April 10-11. Atlanta, GA, USA. (2010).
  14. T.M. Green, W. Ribarsky and B. Fisher  “Building and applying a human cognition model for visual analytics,” Information Visualization 8(1), 1-13 (2009).
  15. R. Chang, C. Ziemkiewicz, T.M. Green, and W. Ribarsky. “Defining insight for visual analytics,” Visualization Viewpoint, Computer Graphics & Applications  29(2), 14-17 (2009).
  16. T. Green, W. Ribarsky and B. Fisher. “Visual analytics for complex concepts using a human cognition model.” In: D. Ebert and T. Ertl (eds.) IEEE Visual Analytics Science and Technology: VAST ’08; 21–23 October. Columbus, OH, Los Alamitos, CA: IEEE Computer Society Press, 91–98 (2008).
  17. T. Green and W. Ribarsky. “Using a Human Cognition Model in the Creation of  Collaborative Knowledge Visualizations.” Proceedings of SPIE (Defense & Security Conference 2008), Vol. 6983, pp. C1‐C10 (2008).

Refereed Short Papers:

  1. T.M. Green and B. Fisher. "Using Translational Science in Visual Analytics," Proceedings of the IEEE Visual Analytics Science and Technology 2012, October 14-19. Seattle WA. (under review).
  2. T.M. Green and B. Fisher. "Visual analytics as an interdisciplinary decision science," Proceedings of the Society of Judgement and Decision Making Conference 2010, St. Louis, MO. Nov 20-22. (2010).
  3. T.M. Green, R. Maciejewski, and S. DiPaola. "ALIDA: Using machine learning for intent discernment in visual analytics interfaces," Proceedings of IEEE Visual Analytics Science and Technology 2010, Salt Lake City, UT. Oct 19-24.(2010).
  4. D.H. Jeong, T.M. Green, W. Ribarsky and R. Chang. “Comparing two Interface tools in performing visual analytics tasks,” In Proceedings of IEEE Visual Analytics Science and Technology 2009,  219-220 (2009).
  5. T.M. Green and K. Najarian. "Correlations between emotion regulation, learning performance, and cortical activity". Proceedings of the 29th Annual Conference of the Cognitive Science Society.  August 2007. Nashville, TN, USA. (2007).

Workshops and Tutorials:

  1. T.M. Green. "Collaboration in Visually Enabled Cogntiion." Fundamentals and Application of Visual Analytics (tutorial). Hawaii International Conference on System Sciences, January 4. Grand Wailea, Maui, USA. (2012).
  2. . M. Green, D. Dunsmuir, J. Dill and B. Fisher. "Analytic Provenance for Collaborative Cognition with CZSaw." Analytic Provenance: Process+Interaction+Insight Workshop, SIG CHI 2011, May 7-8. Vancouver, BC Canada. (2011).

Other Contributions:

  1. T.M. Green and S. DiPaola, “Intent discerning agent for more intuitive visualizations,” Proceedings of the Annual Conference of the Cognitive Science Society, 9-15 August, Portland, OR, USA. (2010).
  2. T.M. Green, B. Fisher, and  D.H. Jeong, “Personality factors predict visual Analytics performance,” Visual Analytics Consortium, Pacific Northwest National Laboratory, August 2009, Richland WA, USA. (2009).
  3. Green, T.M. & Najarian, K. “Is emotion regulation a predictor of learning performance and associated cortical activity?” North Carolina Cognition Conference, February 2007. Chapel Hill, NC, USA. (2007).