Core Reading List

Last Updated: 10 Feb 2021

Kotaro Hara and Wang Yong compiled the core reading list for the Ph.D. Qualification Exam for students under Human-Machine Interaction group.

Selection Process

We had a couple of goals in selecting papers for the reading list.

  • We aimed to identify a few foundational papers that discuss contribution types in Human-Computer Interaction (HCI) research and study methods commonly used to make those contributions. These papers should provide the basis for students to read other papers in the reading list critically. Also, our hope is that students will learn from these papers on how to make research contributions in the research field.
  • We wanted to pick high-quality papers from a diverse subdomain. But HCI as a field is a broad, and we cannot select papers from every subdomain. So we chose the ones that are and would be relevant for our group. For instance, the list includes papers from accessibility and information visualization—domains that Kotaro and Yong work on. We also intentionally excluded some subdomains, such as ubicomp which the Pervasive Sensing and Systems group covers. We avoided including too many papers from each of subdomains and pursued the breadth. The presence of student-compiled reading list encouraged this decision; students should pursue the depth when compiling their list to learn about their main research field.
  • We selected papers that are not too long. Reading 25 articles from the core reading list is a lot of work. And we did not want to over-burden students by asking multiple documents with hundreds of pages. So we tried to avoid long survey papers and books.
  • We picked papers that are published recently. We want students to read many classic papers that affected the course of the research field. But our priority was to expose students to more recent research works topics that would be more relevant for the current and future discourse in the research field.

Core Reading List

Here are core reading list. The areas of paper include: (i) Contribution Types, (ii) Research Methods, (iii) Accessibility, (iv) CSCW and Crowdsourcing, (v) HRI and Agent-based Technology, (vi) Information Visualization and Visual Analytics, (vii) Modeling, and (viii) User Interface and Interaction.

Contribution Types

  • Wobbrock and Kienz (2016) Research Contributions in Human-Computer Interaction, Interactions May-June 2016
  • Hudson and Mankoff (2014) Concepts, Values, and Methods for Technical Human–Computer Interaction Research,

Research Methods

  • McDonald et al. (2019) Reliability and Inter-rater Reliability in Qualitative Research: Norms and Guidelines for CSCW and HCI Practice
  • Sedlmair, Michael, Miriah Meyer, and Tamara Munzner. "Design study methodology: Reflections from the trenches and the stacks." IEEE transactions on visualization and computer graphics 18, no. 12 (2012): 2431-2440.
  • Wobbrock (2011) Practical Statistics for Human-Computer Interaction


  • Jain et al. (2019) Exploring Sound Awareness in the Home for People Who are Deaf or Hard of Hearing
  • Lasecki et al. (2012) Real-Time Captioning by Groups of Non-Experts
  • Wobbrock et al. (2010) Ability-Based Design: Concept, Principles and Examples

CSCW and Crowdsourcing

  • Bernstein et al. (2010) Soylent: A Word Processor with a Crowd Inside
  • Hara et al. (2018) A Data-Driven Analysis of Workers’ Earnings on Amazon Mechanical Turk
  • Koyama et al. (2017) Sequential Line Search for Efficient Visual Design Optimization by Crowds

HRI and Agent-based Technology

  • Fang (HRI 2015) Embodied Collaborative Referring Expression Generation in Situated Human-Robot Interaction
  • Porfirio (UIST 2018) Authoring and Verifying Human-Robot Interactions

Information Visualization and Visual Analytics

  • Munzner, Tamara. "A nested model for visualization design and validation." IEEE transactions on visualization and computer graphics 15, no. 6 (2009): 921-928.
  • Holten, Danny, and Jarke J. Van Wijk. "Force-directed edge bundling for graph visualization." In Computer graphics forum, vol. 28, no. 3, pp. 983-990. Oxford, UK: Blackwell Publishing Ltd, 2009.
  • Cui, Weiwei, Shixia Liu, Li Tan, Conglei Shi, Yangqiu Song, Zekai Gao, Huamin Qu, and Xin Tong. "Textflow: Towards better understanding of evolving topics in text." IEEE transactions on visualization and computer graphics 17, no. 12 (2011): 2412-2421.
  • Liu, Dongyu, Di Weng, Yuhong Li, Jie Bao, Yu Zheng, Huamin Qu, and Yingcai Wu. "Smartadp: Visual analytics of large-scale taxi trajectories for selecting billboard locations." IEEE transactions on visualization and computer graphics 23, no. 1 (2016): 1-10.


  • Banovic et al. (2016) Modeling and Understanding Human Routine Behavior
  • Fast et al. (2016) Empath: Understanding Topic Signals in Large-Scale Text
  • Kay et al. (2016) When (ish) is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems
  • Muller et al. (2017) Control Theoretic Models of Pointing

User Interface and Interaction Method

  • Green et al. (2013) The Efficacy of Human Post-Editing for Language Translation
  • Kasahara et al. (2016) Parallel Eyes: Exploring Human Capability and Behaviors with Paralleled First Person View Sharing
  • Manniono and Abouzied (2018) Expressive Time Series Querying with Hand-Drawn Scale-Free Sketches
  • Willett et al. (2015) Lightweight Relief Shearing for Enhanced Terrain Perception on Interactive Maps