Current Position

Computer Science & Engineering, Northwestern University, Evanston IL - Allen K. and Johnnie Cordell Breed Assistant Professor, 2018 - current.

Medill School of Journalism, Northwestern University, Evanston IL - Assistant Professor, 2018 - current.

Previous Academic Positions

Information School, University of Washington, Seattle - Assistant Professor, 2015 - 2018.

Computer Science & Engineering, University of Washington, Seattle - Adjunct Assistant Professor, 2015 - 2018.

Computer Science, University of California Berkeley - Tableau Research Postdoctoral Fellow, mentor Maneesh Agrawala, 2014.

Education

PhD in Information Science, The University of Michigan School of Information, Ann Arbor, MI. 2009 - 2013. Committee: Eytan Adar (chair), Thomas Finholt, Paul Resnick, Priti Shah

Master of Science in Information (Information Analysis and Retrieval), The University of Michigan School of Information, Ann Arbor, MI, 2006 - 2008. Advisors Lada Adamic and Michael McQuaid

Master of Fine Arts in Writing and Poetics, Prose Concentration, Jack Kerouac School for Disembodied Poetics at Naropa University, Boulder, CO, 2004 - 2006. Advisor: Donald Preziosi (UCLA)

Bachelor of Arts, Comparative Studies, The Ohio State University, Columbus, OH, 2000 - 2003.

Awards

Honorable Mention for Best Paper. ACM CHI 2018. Top 5% of full paper submissions.

Honorable Mention for Best Paper. IEEE InfoVis 2017. One of three total awards given annually to full paper submissions.

Best Paper. ACM CHI 2017. Top 1% of full paper submissions.

Honorable Mention for Best Paper. ACM CHI 2017. Top 5% of full paper submissions.

Gary M. Olson Outstanding Ph.D. Student, May 2013. School of Information at the University of Michigan, Ann Arbor, MI, 2013.

Rackham Centennial Award Merit Scholar, Apr 2012. Rackham Graduate School at the University of Michigan, Ann Arbor, MI, 2012.

Honorable Mention for Best Paper. IEEE InfoVis 2011. One of three total awards given annually to full paper submissions.

Naropa “Secret Attic” Faculty's Choice Best Master's Thesis Award. Naropa University, Boulder, CO, 2006.

Research Funding

NSF Small Award, co-PI Jeff Heer. ($500k). 2019. Representing and Learning Visualization Design Knowledge.

Microsoft Faculty Fellowship. ($200k). 2019.

U.S. Navy (with Stottler Henke and Associates) ($300k). 2019. Visual Tools and Progressive Automation for Complex Knowledge Management and Decision Support (N17A-T004).

NSF CAREER Award ($523k). 2018. Enhancing Critical Reflection on Data by Integrating Users' Expectations in Visualization Interaction

U.S. Navy (with Stottler Henke and Associates) ($70k). 2017. Visualizing Complex Scientific Knowledge for Decision Making

Adobe Software, Unrestricted Research Donation ($20k). 2017, 2018.

NSF CRII Award ($170k). 2016. Facilitating Consumption and Re-expression of Scientific Information in a Journalism Context

Google Faculty Award ($67k). 2015 (with Sean Munson). Visualizing Uncertainty for Bus Arrival Time Predictions

(Inaugural) Tableau Software Postdoctoral Fellowship. 2014. Supported work with Maneesh Agrawala in CS Division at UC Berkeley.

Rackham Centennial Award ($6k). 2012. Rackham Graduate School at the University of Michigan, Ann Arbor, MI.

Graduate Student Research Grants, July 2011, August 2012. Rackham Graduate School at the University of Michigan, Ann Arbor, MI.

Yahoo Boost Award ($2k), April 2010. Yahoo Research with the University of Michigan, Ann Arbor, MI.

Grant Opportunities for Collaborative Spaces ($5k). 2009. University of Michigan, Ann Arbor, MI. PDF proposal

Refereed Conference & Journal Publications

All IEEE VIS papers appear in the first issue of Transactions on Visualization & Computer Graphics the following year.

* denotes student advisee. I use an authoring convention where students are listed first. Through 2016, I appear earlier in the author list when I am the primary faculty mentor. From 2017 - present, I list myself last when I am the primary faculty mentor.

Kim*, YS, Henry, N., Lee, B., Brehmer, M., Pahud, M., Hinckley, K., Hullman, J. Inking Your Insights: Investigating Digital Externalization Behaviors During Data Analysis, ACM Interactive Surfaces & Systems (ISS) 2019. PDF

Hullman, J. Why Authors Don't Visualize Uncertainty. IEEE VIS 2019. PDF

Xiong, C., Shapiro, J., Hullman, J., Franconeri, S. Illusion of Causality in Visualized Data. IEEE VIS 2019. PDF

Kim*, YS., Dontcheva, M., Adar, E., and Hullman, J. Vocal Shortcuts for Creative Experts. ACM CHI 2019. PDF

Kale*, A., Kay, M., and Hullman, J.. Decision-Making Under Uncertainty in Research Synthesis: Designing for the Garden of Forking Paths. ACM CHI 2019. PDF

Kim*, YS., Walls, L., Krafft, P., and Hullman, J. A Bayesian Cognition Approach to Improve Data Visualization. ACM CHI 2019. PDF Github

Phelan, C., Hullman, J., Kay, M., and Resnick, P. Some Prior(s) Experience Necessary: Templates for Getting Started with Bayesian Analysis. ACM CHI 2019. PDF

Nguyen*, F., Shrestha*, S., Germuska, J., Kim*, YS., and Hullman, J.. Belief-Driven Data Journalism. Computation+Journalism 2019. PDF

Hullman, J., Qiao*, X., Correll, M., Kale*, A., and Kay, M. In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation. IEEE VIS 2018.

Kale*., A., Nguyen*, F., Kay, M., and Hullman, J.. Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data. IEEE VIS 2018.

Hullman, J., and Bach, B. Picturing Science: Design Patterns in Graphical Abstracts. DIAGRAMS 2018. PDF

Hullman, J., Kim*, YS., Nguyen*, F., Speers, L., and Agrawala, M. Improving Comprehension of Measurements Using Concrete Re-expression Strategies. ACM CHI 2018. PDF

Fernandes, M., Walls, L., Munson, S., Hullman, J., and Kay, M. Uncertainty Displays Using Quantile Dotplots or CDFs Improve Transit Decision-Making. ACM CHI 2018. Honorable Mention PDF

Qu*, Z. and Hullman, J.. Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring. IEEE InfoVis 2017. Honorable Mention PDF

Kim*, YS., Reinecke, K., and Hullman, J.. Data Through Others' Eyes: The Impact of Visualizing Others’ Expectations on Visualization Interpretation. IEEE InfoVis 2017. PDF

Hullman, J., Kay, M., Kim*, YS., and Shrestha, S. Imagining Replications: Graphical Prediction & Discrete Visualizations Improve Recall & Estimation of Effect Uncertainty. IEEE InfoVis 2017. PDF

Hullman, J., Kosara, R., and Lam, H. Finding a Clear Path: Structuring Strategies for Visualization Sequences. EuroVis 2017. PDF

Kim*, YS, Reinecke, K., and Hullman, J. Explaining the Gap: Visualizing One's Predictions Improves Recall and Comprehension of Data. ACM CHI 2017. Best Paper Award PDF

Kim, Y., Wongsuphasawat, K., Hullman, J., and Heer, J. Graphscape: A Model for Automated Reasoning About Visualization Similarity and Sequencing. ACM CHI 2017. Honorable Mention PDF

Adar, E., Gearig, C., Balusubramanian, A., and Hullman, J. Persalog: Personalization of News Article Content. ACM CHI 2017. PDF

Kim*, YS, Hullman, J., Burgess, M., and Adar, E. SimpleScience: Lexical Simplification of Scientific Terminology. EMNLP 2016 Download PDF

Kim*, YS, Hullman, J., and Agrawala, M. Generating Personalized Spatial Analogies for Distances and Areas. ACM CHI 2016 PDF | Data repository | Tapestry Keynote | Atlas of Me Chrome plugin

Kay, M., Kola, T., Hullman, J., and Munson, S. Approximately When is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems. ACM CHI 2016 PDF, Code repository

Hullman, J., Resnick, P., and Adar, E. Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences About Reliability of Variable Ordering. PLOS ONE 2015. Animated PDF (view in Adobe Acrobat) | Animated appendix | Zipped results | Zipped interface/stimuli

Kim*, YS, Hullman, J., and Adar, E. DeScipher: A Text Simplification Tool for Science Journalism. Computation+Journalism 2015. PDF

Gearig, C, Adar, E., and Hullman, J., Designing for Personalized Article Content. Computation+Journalism 2015. PDF

Hullman, J., Krupka, E., and Adar, E. Evaluating Approaches To Crowdsourced Visual Analytics. Paper selected for presentation at Collective Intelligence 2015.

Hullman, J., Diakopoulos, N., Momeni Roochi, E., and Adar, E. Content, Context, and Critique: Commenting on a Data Visualization Blog, ACM CSCW 2015. PDF

Gao, T., Hullman, J., Adar, E., Hecht, B., and Diakopoulos, N. NewsViews: An Automated Pipeline for Creating Custom Geovisualizations for News. ACM CHI 2014. Demo, PDF

Hullman, J., Drucker, S., Henry-Riche, N., Lee, B., Fisher, D., and Adar, E. A Deeper Understanding of Sequence in Narrative Visualization, IEEE InfoVis 2013. PDF

Hullman, J., Diakopoulos, N., and Adar, E. Contextifier: Automatic Generation of Annotated Stock Visualizations. ACM CHI 2013. Demo, PDF

Hullman, J., Adar, E., and Shah, P. Benefitting InfoVis with Visual Difficulties. IEEE InfoVis 2011. Honorable Mention PDF

Hullman, J., and Diakopolous, D. Visualization Rhetoric: Framing Effects in Narrative Visualization. IEEE InfoVis 2011. PDF

Hullman, J., Adar, E., and Shah, P. The Effect of Social Information on Visual Judgments. ACM CHI 2011. PDF

Workshops Organized & Refereed Workshop Publications

(Workshop organized) Boukhelifa, N., Bezerianos, A., Bertini, E., Collins, C., Drucker, S., Hullman, J., Sedlemeir, M. EVIVA ML: Evaluation of Interactive Visual Machine Learning. Workshop organized at IEEE VIS 2019.

Kale*, A., and Hullman, J. Adaptation and Learning Priors in Visual Inference. VISxVISION Workshop at IEEE VIS 2019. PDF

Kim*, YS., Walls, L., Krafft, P., and Hullman, J. Modeling the Interpretation of Visualized Statistics as Bayesian Cognition. Behavioral Economics Workshop at Economics and Computation (EC) 2019. PDF Github

(Workshop organized) Aitamurto, T., Annany, M., Anderson, C., Birnbaum, L., Diakopoulos, N., Hansen, M., Hullman, J., Ritchie, N. HCI for Accurate, Impartial and Transparent Journalism: Challenges and Solutions. Workshop organized at ACM CHI 2019.

Qiao*, X. and Hullman, J. Translating Scientific Graphics for Public Audiences. Proc. VisGuides: 2nd Workshop on the Creation, Curation, Critique and Conditioning of Principles and Guidelines in Visualization. IEEE VIS 2018.

(Workshop organized) Greis, M., Hullman, J., Correll, M., Kay, M., and Schaer, O. Designing for Uncertainty in HCI: When Does Uncertainty Help? Workshop at ACM CHI 2017.

Hullman, J. Why Evaluating Uncertainty Visualization is Error Prone. Proc. BELIV 2016 PDF

Qu*, Z. and Hullman, J. Evaluating Visualization Sets: Trade-offs Between Local Effectiveness and Global Consistency. Proc. BELIV 2016 PDF

Kim*, Y-S and Hullman, J. Expectation Visualization: Opportunities for Personalized Feedback. IEEE InfoVis 2015 Workshop on Personal Visualization. Chicago, IL (Oct. 25, 2015). PDF

Hullman, J. How Prior Knowledge Affects the Processing of Visualized Data. ACM CHI 2013, Many People Many Eyes workshop. Paris, France (Apr. 28, 2013). PDF

Participant at ACM CSCW CrowdCamp 2013 Workshop. San Antonio, TX (Feb. 23-24, 2013).

(Workshop organized) Diakopolous, N., DiMicco, J., Hullman, J., Karhalios, K., and Perer, A. Telling Stories with Data: The Next Chapter. Workshop at IEEE InfoVis 2011.

Hullman, J. Not all HITs are Created Equal: Controlling for Reasoning and Learning Processes in MTurk. Position paper presented at ACM CHI 2011, Workshop on Crowdsourcing and Human Computation. Vancouver, BC (May 8, 2011). PDF, blog post

Hullman, J., McQuaid, M., Chia, Y., Lin, T., and Zhang, Z. Chance-it: Motivating Collaborative Exploration using Spatial Layout on a Multitouch Surface. Position paper presented at ACM CHI 2011, Workshop on Large Displays in Urban Life. Vancouver, BC (May 7, 2011).PDF

Hullman, J. Visual Texts: Adapting Narratology for Information Visualization. Position paper and featured presenter at Telling Stories with Data workshop, IEEE InfoVis, Oct. 2010, Salt Lake City, UT. PDF slides

Hullman, J. Framing Artistic Visualization: Aesthetic Object as Evidence. Position paper presented at ACM Creativity & Cognition workshop Understanding the Creative Conversation: Modeling to Engagement, Oct. 2009, Berkeley, CA. PDF

Book Chapter

Hullman, J., Rhodes, R., Rodriguez, F., and Shah, P. (2012) Research on Graph Comprehension and Data Interpretation: Implications for Score Reporting. In Zapata, D., & Zwick, R. (Eds.) Recent Research on Score Reporting. Princeton, NJ: Educational Testing Service. PDF

Refereed Posters and Demos

Gao, T., Hullman, J., Adar, E., Hecht, B, & Diakopoulos, D. NewsViews: A System for Automatically Producing Contextualized Geovisualizations for News. Demo presented at Tapestry Conference, Feb. 2014.

Hullman, J., Diakopoulos, D., Adar, E. Putting News in Context, Automatically: An Approach to Generating Relevant & Salient News Visualizations. Poster and demo presented at Computation & Journalism Symposium, Georgia Tech, Jan. 2013.

Hullman, J. Visualization Bootstrapping - A Confirmatory Technique for Visual Analytics. Poster at InfoVis 2012, Seattle WA.

Technical Reports

Lease, M., Hullman, J., Bigham, J.P., Bernstein, M.S., Kim, J., Lasecki, W.S., Bakhshi, S., Mitra, T., and Miller, R.C. Mechanical Turk is Not Anonymous. Social Science Research Network 2013. [Reached Top Ten Downloaded Articles]. Available here.

Hullman, J. & Chia, Y. UM DL1 Multitouch Table Technical Report. University of Michigan Digital Media Commons. (2010). Technical Report. Available here

Invited Articles & Blog Posts

Hullman, J. Confronting Unknowns: How to Read Common Visualizations of Uncertainty. Scientific American. Sept. 2019.

Bakshi, S., Bernstein, M., Bigham, J., Hullman, J., Kim, J., Lasecki, W., Lease, M., Miller, R., Mitra, T. Benchmarking the Crowd. Invited guest post, Follow the Crowd Blog, Mar. 2013.

Bakshi, S., Bernstein, M., Bigham, J., Hullman, J., Kim, J., Lasecki, W., Lease, M., Miller, R., Mitra, T. Mechanical Turk Workers are Not Anonymous. Invited guest post, Follow the Crowd Blog, Mar. 2013.

Hullman, J. Social Proof, Graph Perception, and the Wisdom of the Crowd. Invited guest post, Follow the Crowd Blog, Edited by M. Bernstein et al. July 2011. Available here.

Hullman, J. Managing Reasoning Styles on Amazon’s Mechanical Turk. Invited guest post. Experimental Turk Blog. Edited by G. Paolacci. April 2011. Available here.

Hullman, J. Mastering Motion Charts. The Official Google Analytics Blog. Invited guest post in Advanced Topics in Visualization, appearing 27 Jan. 2009. Available here.

Hullman, J. Trend Analysis with Motion Charts. The Official Google Analytics Blog. Invited guest post in Advanced Topics in Visualization, appearing 10 Feb. 2009. Available here.

Invited Presentations & Interviews

“How to Visually Communicate Uncertain Data (keynote)” Conference on Global Risk, Uncertainty, & Volatility. Swiss National Bank & U.S. Federal Reserve Board. Zurich, Switzerland Nov. 2019.

“Supporting Reasoning Under Uncertainty with Dta Visualization (keynote)” CNA Insurance Conference. CNA. Chicago, IL Sept. 2019.

“Seeing What We (Should) Think Through Visualization Interaction.” Chicago Data Vis Meetup, Chicago, IL June 2019.

“Improving Inference and Decision Making from Visualized Data.” Lawrence Dumas Domain Dinner, Northwestern University, Evanston, IL May 2019.

“Supporting Reasoning with Uncertainty with Data Visualization.” Biostats Seminar, Feinberg School of Medicine, Northwestern University, Chicago, IL Apr. 2019.

“Supporting Reasoning with Uncertainty with Data Visualization.” Michigan Interactive and Social Computer Seminar (MISC), University of Michigan, Ann Arbor, MI Mar. 2019.

“Interactive Visualization for News Readers' Beliefs: Why and How.” (with Yea Seul Kim). NICAR 2019 Invited Session, Newport Beach, CA Mar. 2019.

“Seeing What We (Should) Think Through Visualization Interaction.” Medill Faculty Colloquium, Northwesern University, Evanston, IL Feb. 2019.

“Supporting Reasoning About Uncertainty Through Data Visualization.” Scientific Computing & Imaging Institute, University of Utah, Salt Lake City, UT. Jan. 2019.

“Supporting Reasoning About Uncertainty Through Data Visualization.” NORC at the University of Chicago, Chicago, IL. Dec. 2018.

“Supporting Reasoning About Uncertainty Through Data Visualization.” Neubauer Collegium, University of Chicago, Chicago, IL. Nov. 2018.

“Seeing What We (Should) Think Through Visualization Interaction.” MIT CSAIL HCI Seminar, Boston, MA. Oct. 2018.

“Interrogating Shared Representations. (Invited discussant for Jeff Heer's presentation on Agency & Automation).” HCIC, Watsonville CA. June 2018.

“Improving Data Reasoning Through Visualization & Automation.” Northwestern University, CS+X Seminar, Evanston, IL. Mar 2018.

“Reconciling Single Vs. Multiple View Criteria in InfoVis. (with Zening Qu).” Tableau Software, Seattle, WA. Dec. 2017.

“Seeing What We Think Through Visualization Interaction.” Northwestern University, Technology & Social Behavior Series Distinguished Lecture. Evanston, IL. 2017.

“Visualization Tools for Improving Reasoning with Data” Microsoft Research, New York City, NY, July 2016.

The Visual Uncertainty Experience. OpenVis 2016, Boston, MA Apr. 2016. Slides

“Using Storytelling Patterns to Make Data Relatable” Invited keynote, Tapestry Conference 2016, Estes Park, CO Mar. 2016. Watch on youtube

“Using Data-Driven Storytelling to Make Data and Science Relatable.” Invited presentation at Dagstuhl Seminar on Data-driven Storytelling, Wadern Germany Feb. 2016.

“Visualizing Uncertainty: Benefits of Hypothetical Outcome Plots.” NSF-sponsored M9 Hazard Mapping Workshop, University of Washington, Seattle, WA Sept. 2015.

“Evaluating Graphics Ideas discussion (invited guest expert).” Stat 206, Statistical Communication and Graphics (Prof. A. Gelman), Harvard University, Cambridge, MA Feb. 2015.

“Making Sense of Scales.” DUB seminar at University of Washington (Depts of Information, Comp Science & HCDE), Seattle, WA, Jan. 2015.

“Tools for Understanding and Repurposing Visualized Data.” With Agrawala, M. Tableau Software, Seattle WA, Oct. 2014

“Narrative Visualization Research With Jessica Hullman (interview).” Data Stories #40, (hosts E. Bertini and M. Stefaner), Sept. 2014.

“Evaluating Graphics Ideas discussion (invited guest expert).” Stat 6191, Statistical Communication and Graphics (Prof. A. Gelman), Columbia University, New York, NY, Sept. 2014.

“Anticipating Context in Designing Visualizations for Communication.”
Presented at:

  • Adobe, San Francisco, CA July 2014.
  • Tableau Software, Seattle, WA June 2014.

“Understanding and Supporting Trade-offs in Designing Visualizations for Communication.”
Presented at:

  • Dept. of Computer Science, Stanford, Palo Alto, CA May 2014.
  • School of Interactive Computing, Georgia Tech. Atlanta, GA Mar. 2014.
  • School of Information, University of Washington, Seattle, WA Feb. 2014.
  • Dept. of Cognitive Science, University of California, San Diego, CA Feb. 2014.
  • Dept. of Computer Science, University of Minnesota, Minneapolis MN Feb. 2014.
  • Dept. of Computer Science, University of Colorado, Boulder CO Jan. 2014.

“Understanding and Automating Complex Visualization Design Processes.” Computer Science Division, Univ. of California Berkeley, Sept. 2013.

“Social and Contextual Visualizations”. With Adar, E. Gale Cengage Learning, Farmington, MI, Apr. 2013.

“Letting the Data (and People) Speak: Visualization as Communication & Analysis.” Tableau Software, Seattle, WA, Nov 2012.

“Visualization as Communication & Analysis.” DUB seminar at University of Washington (Depts of Information, Comp Science & HCDE), Seattle, WA, Oct 2012.

“Desirable difficulties in graphical displays.” With Shah, P.,Adar, E., Miyake, A., and Freedman, E. In J. Cromley (Chair), Cognitive processes in comprehension of visual representation: Art, diagrams, graphs, and models. American Educational Research Association (AERA), Vancouver, Canada, April 2012.

“Implications of the Crowd in Collaborative Visual Analytics.” HCI Lab at Tufts University Dept of Computer Science, Cambridge, MA, August 2011.

“Presenting Social Information Online: Evidence of Effects on Visual Judgments.” IBM Collaborative User Experience Research Group (CUE), T.J. Watson Research center, Cambridge, MA, June 2011.

“Visual Stories: Adapting Narratology for InfoVis.” F.I.R.S.T. (Featured Information Research Student Talks), University of Michigan School of Information, October 2010.

Invited Panels

Chang, R., Collins, C., Drucker, S., Endert, A., Hullman, J., and North, C. Panel on Evaluating Interactive Visual Machine Learning (EVIVA-ML) IEEE VIS 2019.

Cook, K. (Moderator), Godwin, S., Hullman, J. and Tietji, G. VAST Challenge Keynote Panel. IEEE VIS 2019.

Hullman, J. (Organizer, Chair), Kay, M., Kirby, M., and Padilla, L. Invited panel on The State-of-the-Art and Future of Uncertainty Visualization, JSM 2018.

Du Toit (Organizer), N., Fingerson, L., Hullman, J., Robbins, N. and Tyner, S. Invited panel on What Makes a Successful Data Visualization, JSM 2018.

Lanning, K. (Moderator), Hullman, J., Tversky, B., and Wickham, H. “Visualizing Uncertainty for Experimental Science.” Invited talk given at panel on: Data Visualization in Psychology: Some Principles and Practices. APS 2018.

Dragicevic, P. (Moderator), Haroz, S., Rensink, R., Hullman, J., and Kay, M. How Can We Improve Empirical Research on Understanding Visual Information? IEEE InfoVis 2016 Panel.

Forbes, A. (Moderator), Doerk, M., Hullman, J., Offenhuber, D., Paris-Westbrook, J., Trowbridge, A. Critical Visualization. IEEE InfoVis 2016 Panel.

Howe, B. (Moderator), Fisher, D., Heer, J., Hullman, J., Payne, J. The Art and Science of Data Visualization. UW eScience Panel.

Teaching

Northwestern University Evanston, IL

  • EECS 396/496, Interactive Information Visualization, 2019-
  • JOUR 330, Data Analysis and Visualization for Journalism, 2018-:

The University of Washington iSchool Seattle, WA

  • INFX 474, Interactive Information Visualization, 2015-2018
  • INFX 562, Interactive Information Visualization, 2015-2018

The University of California, Berkeley, Berkeley, CA

  • Co-instructor (with Maneesh Agrawala), CS 294-10 Visualization, 2014.

The University of Michigan, Ann Arbor, MI

  • Graduate Student Instructor, SI 649 Information Visualization, 2011
  • Graduate Student Instructor, SI 508/Complex Systems 608 Networks: Theory and Applications, 2011
  • Graduate Student Instructor, Russian 348, 2007
  • Graduate Student Instructor, Russian 347, 2008
  • Graduate Student Instructor - Grader, English 367, 2006

Naropa University, Boulder, CO

  • Graduate Student Instructor, Writing Seminar I, 2005.
  • Graduate Student Instructor, Writing Seminar II, 2005-2006

Advisees & Mentoring

Ph.D. Students Advised

  • Paula Kayongo, Northwestern CS Ph.D. student. Chair. 2019 - current.
  • Hyeok Kim, Northwestern CS Ph.D. student. Chair. 2019 - current.
  • Priyanka Nanayakara, Northwestern TSB Ph.D. student. Chair. 2019 - current.
  • Abhraneel Sarma, Northwestern CS Ph.D. student. Chair. 2019 - current.
  • Alex Kale, UW iSchool Ph.D. student. Chair. 2017 - current.
  • Yeaseul Kim, UW iSchool Ph.D. student. Chair. 2015 - current.

Ph.D. Committees

  • Daniel Epstein, UW Computer Science & Engineering. Committee Member. 2018.
  • Ray Zhang, UW Human Centered Design & Engineering. Committee Member. 2018.

Undergrad & Post-Baccalaureate Researchers

  • Boning Zhang, Undergraduate intern from SJTU. 2019.
  • Emily Qiao, Research assistant University of Washington. 2018-2019.
  • Madeleine Grunde-McLaughlin, REU undergraduate from UPenn. 2019.
  • Francis Nguyen, UW iSchool Grad, Research Assistant at Northwestern Computer Science & Engineering. 2016 - current.
  • Samana Shrestha, DREU undergraduate from Vassar College. Mentoring resulting in IEEE VIS 2017 publication. 2016.
  • Tara Kola, DREU undergraduate from Tufts University. Mentoring resulting in ACM CHI 2016 publication. 2015.
  • Lauren Speers, CS undergraduate at UC Berkeley. Mentoring resulting in ACM CHI 2018 publication. 2014.
  • Tong Gao, M.S.I. at University of Michigan. Mentoring resulting in ACM CHI 2014 publication. 2012-2013.

Service

Organizing Committees
IEEE VIS 2019 Tutorials Chair
Computation+Journalism 2019 Program Chair
IEEE VIS 2019 Community Chair

Program Committees
IEEE InfoVis 2019
ACM CHI 2019
IEEE InfoVis 2016, 2018
HILDA (Human-In-the-Loop Data Analytics) 2017, 2018
EuroVis State of the Art Reports 2018
Computation + Journalism 2016, 2017, 2018
BELIV 2016, 2018
ACM UIST 2015
IEEE VisArts Program 2015

Faculty Committees
Strategic Planning Committee, Computer Science, Northwestern University 2019.
Curriculum Committee, Medill School of Journalism, Northwestern University 2018-2019.
Open Position Search, University of Washington Information School, 2018.
Data Science Lecturer Search (Chair), University of Washington Information School, 2017.