Research Projects

Adapting Bug Bounties for Detecting Bias in Machine Learning

Lead Mentor: Jason Hong

Project Description: This project adapts bug bounty programs from cybersecurity to (1) design and implement a novel online game-like system to enable and to incentivize crowd workers to uncover potential blind spots and biases in ML systems; and (2) generate more comprehensive and fairness-aware dataset for ML researchers to use. Developers will be able to upload or connect their own ML systems to a site we will create, have them tested for a wide range of potential biases, and get both a report of problems as well as a data set of cases where the system fails. Where possible, we will also aim to make these data sets available to the general public.

Skills or Requirements:

  • UX design
  • Crowd Sourcing
  • Machine learning
  • Game design

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Crowd Sourcing
  • Games
  • User Experience (UX)
Advancing Fairness in AI with Human-Algorithm Collaborations

Lead Mentor: Haiyi Zhu

Project Description: Artificial intelligence (AI) systems are increasingly used to assist humans in making high-stakes decisions, such as online information curation, resume screening, mortgage lending, police surveillance, public resource allocation, and pretrial detention. While the hope is that the use of algorithms will improve societal outcomes and economic efficiency, concerns have been raised that algorithmic systems might inherit human biases from historical data, perpetuate discrimination against already vulnerable subgroups, and generally fail to embody a given community’s important values. Responsible AI development requires that steps be taken to mitigate these risks as part of system design. In this project, we account for the context-specific fairness principles of actual stakeholders, their acceptable fairness-utility trade-offs, and the cognitive strengths and limitations of human decision-makers throughout the development and deployment of the algorithmic system. In this project, we propose to address these challenges through close human-algorithm collaborations, combining innovative machine learning methods with approaches from human-computer interaction (HCI) for eliciting feedback and preferences from human stakeholders.

Skills or Requirements:

  • Able to design user-interface interfaces that allow people to effectively express their perceptions on fairness
  • Able to create innovative machine learning algorithms that incorporate different forms of fairness notions
  • Able to interview participants to understand how they use the algorithm outputs in real-world contexts

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Ethics
  • Social Computing
Adventures in 3D Printing Processes and Techniques

Lead Mentor: Scott Hudson

Project Description: This project will involve a range of activities aimed at advancing the state of the art in 3D printing and related fabrication. Components will include research on new 3D printers and print processes that are can have an HCI impact. For example, we may consider new techniques for 3D printing of soft materials, use of industrial knitting, or weaving machines for fabrication, or the development of entirely new types of fabrication machines for use with textiles or other materials. We may also consider 3D printing of devices with integrated input sensors, 3D printing or other fabrication of large objects (at furniture, room or larger scale), as well as advanced techniques such as 3D printing of mechanical meta-materials. Every student directly involved in the project will build and take home a 3D printer.

Skills or Requirements:
Preferred skills include one or more of: 3D modeling and/or printing experience, experience with textile fabrication (knitting, weaving, etc.), experience building electro-mechanical devices (e.g., robots), material science knowledge, software implementation, or knowledge of optimization or program synthesis techniques.
Required: a willingness to have fun and work outside the box.

Research Areas in Which This Project Falls:

  • Computer Aided Manufacturing
  • Enabling Technologies
  • Tools
Augmented Reality for Accessibility

Lead Mentor: Jeffrey Bigham

Project Description: Augmented reality technologies offer a number of interesting potential opportunities to improve accessibility to the world for people with disabilities. In this project, students will design and develop prototype systems leveraging increasingly powerful augmented reality platforms targeting the support of people with vision impairments, cognitive impairments, and motor impairments.

Skills or Requirements:

  • Strong technical background
  • Some familiarity with computer vision
  • Human-Computer Interaction

Research Areas in Which This Project Falls:

  • Accessibility
  • Artificial Intelligence (AI)
Building Social Justice into Platforms

Lead Mentor: Sara Kingsley

Project Description: My project audits algorithms and online platforms for bias against demographic groups. The project also seeks to investigate and uncover information about how algorithms distribute economic opportunities among workers. After collecting and evaluating platform data, we design software interventions for when algorithms or platforms fail to treat people equally or disadvantage workers.

Skills or Requirements:

  • Python
  • Statistics
  • Machine Learning (preferred but not required)

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Ethics
  • Methods
  • Social Computing
  • Social Good
  • Societal Problems
ClassInSight: Personal Informatics for Teachers

Lead Mentor: John Zimmerman & Amy Ogan

Project Description: People get better at something when they have actionable feedback that helps them improve. Our project is placing sensor in classrooms to detect what is happening; what is the teacher doing and how are students reacting. We then provide visualizations for teachers to help them reflect on their actions, make a plan for their next class, and view their data to measure their success. We are looking to RAs that can help analyze collected data, create visualizations, and assess how teachers make sense of what’s happening in their classrooms.

Skills or Requirements:

  • Visual and information design
  • Data visualization (e.g. D3, P5)
  • Responsive web design and development
  • Interviewing and qualitative research

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Data Visualization
  • Design Research
  • Education
  • User Experience (UX)
Designing data visualizations for Interpretable Machine Learning in Healthcare

Lead Mentor: Adam Perer

Project Description: Machine learning is being actively deployed in healthcare institutions. However, doctors and patients often have little understanding how these automated algorithms are making predictions. This summer, we'll be building novel visual interfaces to help explain what these algorithms are doing to the stakeholders. We'll be partnering with a local research hospital, working with real ML models on real patient data, and designing new interfaces to convey the inner workings of these models.

Skills or Requirements:

  • Web programming skills
  • Data visualization interest
  • Healthcare interest
  • Machine learning interest

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Data Visualization
  • Healthcare
  • Social Good
Designing interventions to improve math education

Lead Mentor: Nikki Lobczowski

Project Description: We have two ongoing projects. The first involves an app, Personalized Learning2 (PL2), that helps mentors working with K-12 students who are learning math online. A key component of this project is the ongoing creation and revision of resources, which are designed to support the mentors as they help the students. The second project, Multiplier Effects on Math Education (MEME), focuses on creating an AI-based tutor that incorporates cognitive and motivational interventions to produce a multiplier effect on algebra learning. Next year, we will be adding a metacognitive component in hopes of increasing effectiveness further. Moving forward, we specifically need help with the following tasks: Content development of resources for PL2, interviews and focus groups with mentors, content development of math problems and/or metacognitive component for MEME, and AI-based tutor development of metacognitive component for MEME.

Skills or Requirements:

  • Background in programming preferred but not required
  • Interest in STEM education
  • Background or interest in learning, motivation, and/or metacognition
  • Background in mathematics preferred but not required
  • Background or interest in user centered design

Research Areas in Which This Project Falls:

  • Design Research
  • Education
  • Learning Sciences and Technologies
  • User Experience (UX)
Develop a Web Application for the McLearn Lab

Lead Mentor: Bruce McLaren

On this project, the REU intern will develop a web application for the McLearn Lab, Professor McLaren's lab. The web app will be interactive, including demos of existing technology and communication with lab members. It will be a universal application that runs in the browser, or on a smartphone, and provides up to the minute information about the research and work of Professor McLaren's research lab. As part of this project, the intern will learn about current McLearn Lab projects involving games, virtual reality, and intelligent tutors. The intern will also learn about industry standard software development skills, including agile software development, version control, test-driven development and continuous integration.

Skills or Requirements:

  • Modern web development technologies, e.g., HTML, JavaScript

Research Areas in Which This Project Falls:

  • Data Visualization
  • Education
  • Intelligent Tutoring Systems
  • User Experience (UX)
  • Virtual Reality (VR)
Developing a Digital Learning Game for Learning Non-Routine Mathematics

Lead Mentor: Bruce McLaren

Project Description: In this project, the REU intern will help in developing a game called "Dueling Den" which is designed to help high school students learn to become more flexible math problem solvers. The problems that HS students work with in the game are known as "non-routine math problems" and involve creative problem solving with multiple solutions. The intern will work closely with McLearn Lab PhD student Nguyen in developing this novel card game. Work on this project will involve HTML and JavaScript programming. The REU intern will also be involved in game design and will learn about educational technology studies.

Skills or Requirements:

  • Programming skills in HTML and JavaScript are required
  • Game design experience/skills are helpful but not necessary
  • Education or ed psych background would be helpful

Research Areas in Which This Project Falls:

  • Games
  • Learning Sciences and Technologies
  • User Experience (UX)
Easy authoring of intelligent tutoring software (CTAT)

Lead Mentor: Vincent Aleven

Project Description: Past research shows that intelligent tutoring systems--software that coaches students step-by-step as they try to solve complex problems--can be very helpful aids to learning, for example in middle school and high school mathematics learning. The effectiveness of tutoring software has been shown in many different subject areas, and some ITSs have reached commercial markets and are in daily use in many schools. Inspired by these results, we have developed authoring tools that make the creation of tutoring software much easier--in many cases, even without programming. Instructors in fields such as math and physics have used our tools to create lessons for their classes. We now want to reimplement our authoring tools with the knowledge we have gained over the 15 years since their first release. We seek to make them intuitive, clear, efficient and readily available--without requiring complicated installation or advance instruction. We want to improve both the creation of the student-facing user interface and the specification of the tutoring knowledge and behavior behind it. We want to support teams of teachers collaboratively creating these self-coaching, self-grading online activities that they might assign instead of conventional homework.

Skills or Requirements:

  • The work involves UI design, web programming, building tool prototypes, and trying them out with tutor authors.

Research Areas in Which This Project Falls:

  • Education
  • End-User Programming
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
  • Tools
  • User Experience (UX)
Embedding erroneous examples in a digital learning game

Lead Mentor: Bruce McLaren

Project Description: For this project, the REU intern will implement erroneous examples (i.e., examples with incorrect responses that match common student misconceptions) within a digital learning game. The student will assist in analyzing data from a previous study using erroneous examples in the game to identify the components that worked best, and they will help iterate a new design that incorporates these components. The student may also assist in better understanding the learner's experience in the game, particularly when encountering erroneous examples. The intern should have an interest in education and learning from technology, a computer science and programming background, and experience with HTML and JavaScript. The intern should also be willing to learn new technologies. The intern will learn about research on learning with educational technology, how to develop web-based applications using industry standards and best practices - agile software development, responsive web design, JS templating and design patterns - and version control, unit testing and debugging web applications.

Skills or Requirements:

  • Programming experience with HTML and JavaScript is essential
  • Familiarity with version control, web programming, and agile software development are desirable

Research Areas in Which This Project Falls:

  • Education
  • Games
  • Learning Sciences and Technologies
  • User Experience (UX)
Engaging educational technology for middle-school students

Lead Mentor: Vincent Aleven

Project Description: In research studies, we found out that Lynnette, a basic tutoring system for middle-school equation solving, helps students learn but also that it is not as engaging for students as we would like it to be. We have worked to make Lynnette more engaging, by adding a space theme, a badge system, and a drag-and-drop interaction format for equation solving. We would like to make Lynnette even more engaging. We have a variety of ideas, including personalized dashboards, culturally-adaptive story problems, and adapting instruction to social and meta-cognitive factors (e.g., sense of belonging in classroom, self-efficacy). We are open to other ideas as well. The work involves design brainstorming, co-design with middle-school students, prototyping, and trying out prototypes with students.

Skills or Requirements:

  • Preferred skills: Design/HCI, prototyping, web development
  • Experience with game design, educational technology, and designing for teenagers is not required but would be considered a plus

Research Areas in Which This Project Falls:

  • Education, Games
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Enhancing conceptual learning with an intelligent tutoring system for middle-school equation solving

Lead Mentor: Vincent Aleven

Project Description: From our past studies (done in middle school classroom) we know that Lynnette, an intelligent tutoring system for basic equation solving that we created, is very effective in helping students learn to solve equations. Lynnette, however, is less effective in helping students develop a strong conceptual understanding of algebra. In this project, we are extending Lynnette, so it helps students come away with a much better mix of conceptual knowledge and equation-solving skill. We are designing worked examples, self-explanation prompts, and interactive diagrams. The work involves design, developing prototypes, and trying them out with middle school students. We have extended Lynnette so that students, as they solve an equation, explain each of solution steps by selecting a "tape diagram" representation that represents the step. We now look to extend the tape diagrams, for example so they represent negative numbers, so that variables in these diagrams can actually "vary" (e.g., "accordion variables"). Animations might be very helpful.

Skills or Requirements:

  • Preferred skills: Design/HCI/prototyping
  • Knowledge of animations (in web pages), education, and educational technology

Research Areas in Which This Project Falls:

  • Data Visualization
  • Education
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Expanding the Apprentice Learner Architecture

Lead Mentor: Erik Harpstead

Project Description: The goal of the Apprentice Learner Architecture project is to create a computational theory of human learning that can be used to simulate the learning process with instructional technology. The architecture itself is highly modular and can be re-configured to use several different machine learning approaches. In this project an REU will work with the team to expand the current suite of supported machine learning mechanisms and contribute to the overall system. They will also test modifications to the architecture by running simulations of learning in existing educational technology platforms and comparing behavior against pre-recorded educational data. Ultimately, this work will contribute to establishing a platform to advance computational cognitive science research.

Skills or Requirements:

  • A strong technical background in programing (specifically python) and machine learning is a requirement
  • Experience working on large collaborative software projects would be a plus
  • Prior experience / course work in cognitive psychology / science would be helpful in considering psychological implications of new machine learning techniques

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Education
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Facilitating Public Deliberations of Fairness Metrics in Machine Learning

Lead Mentor: Jason Hong

Project Description: This project aims at (1) developing more intuitive and generally understandable representations and interfaces to help the general public (i.e., lay people) better understand fairness metrics developed by machine learning experts; and (2) building an online platform to help the general public discuss, deliberate and debate issues around AI and fairness. It aims at serving as a communication channel connecting the general public and the machine learning community to foster democratic debate around various statistical notions of fairness.

Skills or Requirements:

  • User interface design
  • Data visualization
  • Statistical analysis
  • Machine learning

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Data Visualization
  • Ethics
  • Societal Problems
  • User Experience (UX)
Fuse: a tool for making sense of complex information

Lead Mentor: Niki Kittur

Project Description: Over a trillion hours per year are spent searching for and making sense of complex information. For a lot of this "sensemaking," search is just the beginning: it’s also about building up your landscape of options and criteria and keeping track of all you’ve considered and learned as you go. We've found through more than a decade of research that existing tools don't support this messy process. So we are building a tool that does.

Skills or Requirements:

  • Knowledge of and interest in consumer-focused digital products
  • Able to quickly iterate and pivot depending on the needs of the team
  • Critical thinking and feedback skills for product development and critiques
  • Fluent in UX research, design, and basic knowledge of coding

Research Areas in Which This Project Falls:

  • Design Research
  • Service Design
  • Tools
  • User Experience (UX)
Games for Explaining Artificial Intelligence 

Lead Mentor: Adam Perer

Project Description: As AI continues to become more ubiquitous, its impacts users on a variety of levels. AI developers need techniques to ensure their models are working correctly. Stakeholders need oversight to ensure the models they deploy won’t be harmful. And consumers, the end users of models, may need tools to trust the AI when making decisions. Explainable AI (XAI) offers the promise of transparency and the capability to simplify complex AI models to be interpretable to humans. However, while many XAI techniques have been proposed, few have been tested beyond anecdotal use. There still exists a need to accurately assess how interpretable such explanations are, with quantifiable measurements, assessed with actual humans. We argue that explanations cannot be evaluated in an automated manner, as only humans can determine if an explanation makes sense for a human. Our research involves building a novel, scalable platform that supports quantifiable assessment of AI Explanations with humans, by designing novel games with a purpose.

Skills or Requirements:

  • Web development skills
  • Interest in games
  • Interest in explainable AI

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Crowd Sourcing
  • Data Visualization
  • Games
Human-AI co-orchestration of dynamically-differentiated, collaborative classrooms

Lead Mentor: Vincent Aleven

Project Description: Real-world experience in classrooms equipped with online intelligent tutoring systems (ITSs) has shown that, even though the software is coaching each student individually with adaptive guidance, teachers still play an enormous role in student learning. For example, we have seen teachers in these classrooms pair quicker students with slower ones--on the fly, just for the class period--to extend one-on-one aid for those needing further help. For teachers to be most effective, however, they must be able, in real time, to see how their students are doing (struggling, disengaged, finishing early, etc) and to take action to aid those who need help. We are creating tools by which middle-school teachers can effectively orchestrate activity in these classrooms without taking their attention away from the students. The tools use wearable and mobile devices (we are experimenting with mixed-reality glasses, smartwatches, tablets, and so forth) with artificial intelligence to turn the voluminous data generated by the software into actionable diagnostic information and recommendations for teachers. In a new project, we plan to provide ITSs that support both individual and collaborative problem-solving by students, to enhance the effectiveness of the pairings we have observed. We seek an intern interested in any of the many efforts needed to make these technologies work, from testing and refining collaborative ITSs with students to design-based research for designing and prototyping intuitive, comprehensible visualizations for teachers, for different hardware options, and trying them out with teachers.

Skills or Requirements:

  • Preferred skills HCI/design skills, especially related to mixed-reality and/or wearable devices
  • AI/machine learning/data mining;
  • Web technologies

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Augmented Reality (AR)
  • Data Visualization
  • Design Research
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
  • User Experience (UX)
  • Wearables
Improving Smartphone Privacy

Lead Mentor: Jason Hong

Project Description: We want to help Android app developers be better about privacy. We've developed a plug-in for Android Studio to give developers feedback, and want to add more features to help automatically generate privacy policies, privacy-oriented user interfaces, and to make apps easier to analyze. See https://coconut-ide.github.io for more info.

Skills or Requirements:

  • Android (or lots of Java experience)
  • Preferred but not required to have some background in privacy, security, static or dynamic analysis, user interface design

Research Areas in Which This Project Falls:

  • Security and Privacy
Incorporating and Balancing Stakeholder Values in Algorithm Design

Lead Mentor: Haiyi Zhu

Project Description: This project will create a general method for value-sensitive algorithm design and develop tools and techniques to help incorporate the tacit values of stakeholders, balance multiple stakeholders' values, and achieve collective goals in the development of an algorithm. The research community has paid increasing attention to the role of human values in algorithm design and development. For example, fairness-aware machine learning research attempts to translate fairness notions into formal algorithmic constraints and develop algorithms subject to such constraints. Despite the mathematical rigor of these approaches, prior research suggests a disconnect between the current discrimination-aware machine learning research and stakeholders' realities, context, and constraints; this disconnect is likely to undermine practical initiatives. Furthermore, studies have suggested that there are often tensions among a diverse set of values relevant to the design of the algorithm. A new general method will be developed in the context of Redesigning Wikipedia's Objective Revision Evaluation Service (ORES), a machine learning-based service designed to generate real-time predictions on edit quality and article quality, which will benefit vast numbers of people who consume the Wikipedia content either directly or indirectly through other applications.

Skills or Requirements:

  • Interacting with people: Abilities to conduct interviews to understand human stakeholders' values
  • Algorithm Design: Abilities to formulate values, formally define the corresponding system criteria, and create algorithms that considers these criteria
  • Visualization: Abilities create visualization tools to explain the values and potential value trade-offs in machine learning algorithms

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Data Visualization
  • Social Computing
  • Societal Problems
Interactive care pathways

Lead Mentor: John Zimmerman & Jodi Forlizzi

Project Description: Care pathways are flowcharts that document the standard of care for diagnosis and treatment of common health problems. For example, there is a care pathway describing what clinicians should do if an infant comes to the emergency room with a fever. When they are used, care pathways improve consistency of care and health outcomes. We are working to develop interactive care pathways. These automatically generate the clinical notes. They also collect detailed info about clinician actions in support of data-driven innovation.

Skills or Requirements:

  • Web design
  • Front-end development; Javascript
  • Prototyping
  • User testing

Research Areas in Which This Project Falls:

  • Context-Aware Computing
  • Data Visualization
  • Design Research
  • Healthcare
  • Service Design
  • User Experience (UX)
Internet of Things privacy

Lead Mentor: Jason Hong

Project Description: We're developing new kinds of programming models, feedback mechanisms, and other ways of improving privacy for Internet of Things. We have a smart building filled with sensors (see mites.io), and want to look at how to help people feel like they are in control of things and have a good understanding of what is being sensed.

Skills or Requirements:

  • Must have strong programming skills and organizational skills
  • Would be nice to also have some background in HCI, visualization, programming languages, and databases.

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Context-Aware Computing
  • Security and Privacy
LearnSphere

Lead Mentor: Ken Koedinger 

Project Description: A community data infrastructure to support learning improvement online. The LearnSphere project integrates existing and new educational data and analysis repositories to offer the world’s largest learning analytics infrastructure with methods, linked data and portal access to relevant resources

Skills or Requirements:

  • The student researcher will contribute to designs that enhance the general usability of the Tigris workflow tool.
  • The intern will need to draw on their Adobe, HTML and CSS skills and prior experience to create mock-ups and implement team-approved designs.
  • Ideally the candidate will also be able to conduct user interviews and create demo videos of the tool.

Research Areas in Which This Project Falls:

  • Design Research
  • Learning Sciences and Technologies
  • User Experience (UX)
LearnSphere: A community data infrastructure to support learning improvement online

Lead Mentor: Ken Koedinger 

Project Description: The LearnSphere project integrates existing and new educational data and analysis repositories to offer the world’s largest learning analytics infrastructure with methods, linked data and portal access to relevant resources. The student researcher will help analyze large amounts of educational data from students enrolled in online courses to help identify best learning practices.

Skills or Requirements:

  • R/Python/Excel
  • Basic programming skills
  • Basic stats knowledge

Research Areas in Which This Project Falls:

  • Data Visualization
  • Learning Sciences and Technologies
PL²: Personalized Learning

Lead Mentor: Ken Koedinger

Project Description: PL² is a project addressing the opportunity gap for marginalized students through personal mentoring and tutoring with artificial intelligence learning software.

Skills or Requirements:

  • The student researcher will contribute to designs that enhance the general usability of the PL2 dashboard tool (personalizedlearning2.org)
  • The intern will need to draw on their UI/UX and Communication Design skills and prior experience to create mock-ups to be presented for team approval
  • Adobe (XD) is preferred
  • Ideally the candidate will also be able to conduct user interviews and create demo videos of the dashboard
  • Front-end programming experience (HTML, CSS, Javascript) is a nice-to-have but not required.

Research Areas in Which This Project Falls:

  • Design Research
  • Learning Sciences and Technologies
  • User Experience (UX)
PrivacyIO: Discover Privacy Concerns using a Crowd

Lead Mentor: Jason Hong

Project Description: Imagine a data scientist in Uber finds that users are more likely to accept a high surge price if their smartphone battery level is low. Incorporating this insight into the system may improve corporate profit; however, it may also lead to negative headlines in the news media. We are developing a usability engineering technique to help practitioners to navigate similar decisions: 1) storyboarding for privacy scenarios; 2) heuristic evaluation for privacy problems. We are looking for one research assistant to help us validate our technique. Tasks will include a) generating storyboards using a system we have developed; b) scheduling study participants and running user studies. You will learn the state of arts privacy measuring technique from a UX perspective.

Skills or Requirements:

  • Genuine interest in HCI or privacy research, attention to detail, strong organizational skills, reliable, self-motivated, experience with conducting lab studies
  • Knowledge about usability techniques (e.g., storyboarding, heuristic evaluation) is a big plus.

Research Areas in Which This Project Falls:

  • Crowd Sourcing
  • Security and Privacy
Robot Re-embodiment

Lead Mentor: John Zimmerman & Aaron Steinfeld

Project Description: We are investigating how groups of people should interact with, coordinate, and collaborate with groups of robots. Our project specifically explores robots with super-human abilities, such as re-embodiment (can jump robot mind from body to body) and co-embodiment (many robot minds in a single body). This project prototypes possible futures. We run studies with real people interaction with robots to understand what robots should and should not do.

Skills or Requirements:

  • Industrial design prototyping
  • Speed dating with user enactments and/or storyboards
  • User testing
  • Qualitative data analysis

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Context-Aware Computing
  • Design Research
  • Human-Robot Interaction (HRI)
  • Service Design
  • User Experience (UX)
  • Voice
SensorInc: On self-sustaining IoT commons

Lead Mentor: Jason Hong

Project Description: Beyond the “smart home” and “smart enterprise”, the Internet of Things (IoT) revolution is creating “smart communities”, where shared IoT devices collectively benefit a large number of residents, for transportation, healthcare, safety, and more. However, large scale deployments of IoT-powered neighborhoods face two key socio-technical challenges: the significant upfront investment and the lack of information on local IoT needs. Our overarching goal is to design and implement an architecture that incentivizes residents to design and manage sensor deployment through sensor liquefaction. By turning shared sensors into liquid (i.e. tradeable) assets akin to a company stock, users can design and invest in promising IoT deployments and receive monetary rewards afterward. To achieve that goal, we will develop the foundational pricing theory for IoT sensor data and a practical architecture for IoT data trading. We are looking for one research assistant to help us explore the space of IoT data market and blockchain technologies through building a “Minimum Viable Product” prototype.

Skills or Requirements:

  • Genuine interest in IoT research
  • Strong programming skills, reliable, self-motivated
  • Experience with blockchain technology
  • Knowledge about market design is a big plus.

Research Areas in Which This Project Falls:

  • Internet of Things (IoT)
  • Security and Privacy
  • Sensors
Smart Tools: Supporting Documentation Practices in Maker & Project Based Learning

Lead Mentor: Marti Louw

Project Description: Innovating smart documentation (IoT) tools to support creative practice, reflection and learning in Maker and project-based curriculums. Summer research focuses on learning environments with youth in underserved community settings.

Skills or Requirements:

  • Students will support one or more of the following:
    • Conducting value-sensitive design research
    • Concept development
    • Technical prototype building
    • Field testing and evaluation of systems
  • Students will be able to deepen experience and skills in:
    • Qualitative research and evaluation
    • Conceptual design and communication
    • Hardware and software development (Arduino, Raspi)
    • And/or interactive prototyping

Research Areas in Which This Project Falls:

  • Design Research
  • Education
  • Internet of Things (IoT)
  • Learning Sciences and Technologies
  • User Experience (UX)
SmartSheet

Lead Mentor: Erik Harpstead

Project Description: The goal of the Smartsheet project is to develop a system whereby teachers can easily build electronic math worksheets that provide students with adaptive tutoring support on their homework or in class activities. To create this tutoring support, teachers need only engage in a bit more effort than writing problems on a tablet and way less effort than they usually spend on grading. The system leverages a computational model of human learning to enable teachers to program by teaching. This REU would contribute to the project by further exploring techniques teachers can use to provide instruction and feedback to an intelligent agent via sketch based interactions. The student will work to prototype and test new training interactions with uses to evaluate their instructional efficiency for the agent and ease of use for teachers.

Skills or Requirements:

  • A strong technical background in programming (primarily python and interactive web technologies, js/HTML5) would be a requirement
  • Prior experience with any kind of interactive machine learning would preferred but not a hard requirement
  • Prior experience running user studies would also be helpful

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Education
  • End-User Programming
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Social Commerce: The Role of Social Media in Product Design and Development for Micro-business Owners

Lead Mentor: Yasmine Kotturi

Project Description: Increasingly, individual creators and creative small businesses turn to various online spaces (such as online creative communities, crowds, forums) seeking feedback to facilitate their design processes and inform decisions for what products to make. To date, the role of social media in this online feedback loop is relatively uncharted, yet simultaneously of growing importance as "social commerce'' is on the rise. In this project, we are exploring how creators leverage their social media to solicit feedback, as well as probe ways to make such solicitations more effective. To make such exchanges more effective, we are leveraging a participatory design approach to build feedback software tools with and for creative small businesses. Interested students should be keen to learn about design methodologies, alongside enhancing their technical and research skills.

Skills or Requirements:

  • Object-oriented programming and data structures
  • Javascript
  • React
  • Node.js, Express, GraphQL, MongoDB (a plus, not required)

Research Areas in Which This Project Falls:

  • Social Computing
Social Cybersecurity Games and Interventions

Lead Mentor: Laura Dabbish

Project Description: This project leverages theory from psychology and known social influence principles to improve cybersecurity behavior and enhance security tool adoption. Students on this project will work on designing and developing web-based security-related mini games or interventions that incorporate cybersecurity training and information into people’s everyday workflows. They may also have an opportunity to conduct evaluations of these mini games or interventions.

Skills or Requirements:

  • Interest in interaction design, psychology and/or cybersecurity
  • Web programming (front-end or back-end)
  • Familiarity with inVision, Sketch, or other graphic design tools
  • Familiarity with Python or Javascript

Research Areas in Which This Project Falls:

  • Design Research
  • Games
  • Security and Privacy
  • Social Computing
Social Engineering Defense

Lead Mentor: Jeffrey Bigham

Project Description: In this project you will work on Active Social Engineering Defense. The goal of the project is to handle phishing and social engineering attacks and mediate communications between users and potential attackers. The system will actively detect attacks and coordinate investigations to discover the identity of the attacker through conversations on email or phone. The project has two subgoals - 1) Engage scammers for a long number of turns in order to waste their time, and 2) Actively elicit personal information from scammers during a conversation. For this project, you will develop rule-based, generative or retrieval systems which can handle conversations with a scammer. Your contributions can range from building data collection interfaces, analysis of collected data, and development of neural models for conversation.

Skills or Requirements:

  • Strong programming skills
  • Human-computer interaction
  • Natural language processing, and machine learning

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
Social Programmable Robots: Teaming with Robots to Improve Computer Science Skills and Attitudes/dt>

Lead Mentor: Amy Ogan

Project Description: Help us with an exciting project at the intersection of HCI and learning science. By imbuing a programmable robot with social characteristics, and positioning the robot as part of the “team”, we aim to design a culturally-responsive curriculum for Latina, African American, and Indigenous girls who have been excluded by approaches that decouple technical skill and social interaction. This project investigates how to design a social robot for programming activities. The robot can be programmed using a visual programming language, and can convey emotion with its facial expressions, sounds, and movements. The project will explore whether learning to program with this socially expressive robot improves computer science (CS) outcomes such as attitudes, self-efficacy, and knowledge.

Skills or Requirements:

  • Design
  • Psychology
  • UX

Research Areas in Which This Project Falls:

  • Education
  • Human-Robot Interaction (HRI)
  • Learning Sciences and Technologies
  • Social Good
Studying Social Influences on Security and Privacy Behavior

Lead Mentor: Laura Dabbish

Project Description: Research on the human factors of cybersecurity often treats people as isolated individuals rather than as social actors within a web of relationships and social influences. We are developing a better understanding of social influences on security and privacy behaviors across contexts. Students on this project will conduct interviews and surveys on people's cybersecurity behaviors in different types of relationships (in groups and teams in the workplace, within families, and in romantic relationships). They may also have the opportunity to develop and prototype new system design ideas based on research findings.

Skills or Requirements:

  • Coursework in psychology, design or cybersecurity
  • Interest in developing interviewing and survey design skills
  • Experience with statistical analysis techniques or packages such as R
  • Interest in interaction design

Research Areas in Which This Project Falls:

  • Design Research
  • Security and Privacy
  • Social Computing
  • User Experience (UX)
SUGILITE: A Multi-Modal Agent that Learns Tasks from Natural Language and Demonstrations

Lead Mentor: Brad Myers

Project Description: Intelligent virtual assistants on smartphones like Siri and Google Assistant can perform tasks on the user's behalf, but their capabilities are limited to the apps and services they support, without a way for users to teach them new tasks. Prof. Brad Myers and PhD student Toby Li in the HCII (along with collaborators across SCS) have a research project on designing and implementing a multi-modal smartphone intelligent agent that enables the users to teach it new procedures, concepts and user preferences by demonstration and natural language instructions. We have finished the development of a first version of the system and are looking for students to help design and develop new features. More details about this project, including demo videos and previous publications, are available at http://toby.li/research/. Possible projects may focus on a wide range of topics from interface design and user research to semantic parsing, dialog systems and interactive machine learning depending on student interests.

Skills or Requirements:

  • Required skills: Strong Java programming skills
  • Preferred skills: Android development, natural language processing (especially semantic parsing), interactive machine learning, user-centered research and design

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • End-User Programming
  • Internet of Things (IoT)
  • Voice
Using interaction designs and Machine Learning to understand human learning

Lead Mentor: Paulo Carvalho

Project Description: The project explores learning processes by contrasting learning from retrieval practice and learning from studying examples. The goal of this project is to resolve and clarify how these processes compete for cognitive resources, including attention and working memory, in ways that depend on the knowledge content to be learned using a combination of experimental and computational approaches.

Skills or Requirements:

  • Familiarity with Python/R
  • Basic knowledge of statistical analyses
  • Some knowledge of psychology/science of learning is preferred but not required

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Verdant: Creating Summaries from Complex Data Experimentation Histories

Lead Mentor: Brad Myers

Project Description: Programming for data science and machine learning (ML) projects is an exciting and important area of computational work today. Much of working with ML or data is an iterative experiment-driven process where individuals try out many different approaches to find answers they need. Prof. Brad Myers and PhD student Mary Beth Kery in the HCII have an ongoing research project studying how people experiment in code. This work includes qualitative studies with programmers, along with designing and building new kinds of developer tools in computational notebooks to support exploratory programming. More details about the publications, systems, and work so far can be found at https://marybethkery.com/. This summer research project will focus on summarizing complex experiments with code/data to help others on a team understand what the original programmer of the experiments did. Possible project focuses are flexible depending on the REU student's skills and interests but may include: interviewing data scientists, conducting user-centered design studies, interaction design, or developing intelligent algorithms and interface for summarizing experiment data in an easily readable manner.

Skills or Requirements:

  • Required skills: Python programming skills
  • Preferred skills: Web development (Javascript, CSS, Typescript, React), design skills, machine learning (beginner), user-centered research and design

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Data Visualization
  • End-User Programming
  • Tools