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List of Courses

C02: HCI History and Today’s Challenges—What Was Anticipated, What Was Not

1 unit(s) | Monday 11:00:00 AM – 12:15:00 PM | Course Website

This course is for students, practitioners and faculty interested in understanding the evolution of the field of human-computer interaction, a journey that has led to the vital opportunities and serious challenges that shape the present and future. Early HCI visions were achieved. This yielded anticipated benefits and unanticipated consequences. The course surveys HCI in computer science, human factors, information systems, and information science. It covers relationships to design and artificial intelligence. It relies on timelines, images, and few bullet points. By understanding the forces that governed the paths and interactions of several disciplines, we can better comprehend significant issues that engage and engulf us today. With hindsight into past achievements and oversights, we can identify future possibilities that will call for and in some cases demand creative engagement.

Instructor(s)

Jonathan Grudin
I have been active in CHI and CSCW research since each field formed. I wrote and edited an HCI history column in Interactions magazine, published in Annals of the History of Computing, and authored a 2017 book on this topic. I am a CHI Academy member and ACM Fellow.

Intended Audience (Level: Easy)

No prerequisites. Students, faculty, and practitioners have taken past versions of this course. It is both “Introductory” and an advanced treatment of the topic. New material includes the origins of important trends that have arisen in the last few years; the course is intended for an audience looking forward, not solely looking back.

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C03: Dealing with Ethical Challenges in HCI Fieldwork

2 unit(s) | Monday 2:00:00 PM – 5:15:00 PM | Course Website

We are witnessing an increase in fieldwork within the field of HCI, particularly involving marginalized or under-represented populations. This has posed ethical challenges for researchers during such field studies, with “ethical traps” not always identified during planning stages. This is often aggravated by the inconsistent policy guidelines, training, and application of ethical principles. We ground this in our collective experiences with ethically-difficult research, and frame it within common principles that are common across many disciplines and policy guidelines – representative of the instructors’ diverse and international backgrounds.

Instructor(s)

Cosmin Munteanu
Prof. Cosmin Munteanu is an Assistant Professor at the Institute for Communication, Culture, Information, and Technology at University of Toronto Mississauga and Director of the Technologies for Ageing Gracefully lab. Cosmin has conducted research on the ethical aspects of conducting technology-centric ethnographies and fieldwork and on issues of digital divides and interactive technologies for marginalized populations. Cosmin is an organizer for the Workshop on Ethical Encounters in Human-Computer Interaction (held at ACM CHI 2015, 2016, and 2017), which aims to engage multidisciplinary researchers in a dialogue about the ethical challenges faced in fieldwork with emerging interactive technologies. He has served as scientific reviewer for ethics applications during his tenure at the National Research Council Canada, is currently a member of the ACM SIGCHI Committee on Ethics, and is actively conducting research in the field of ethics as a recipient of a Social Sciences and Humanities Research Council of Canada Knowledge Synthesis Grant.

Roisin McNaney
Dr. Roisin McNaney is a Lecturer in Digital Health at Bristol University. Her research interests focus around the role that digital technologies might play in supporting self-monitoring and management Practices in people with Parkinson’s specifically and chronic health conditions more generally. She comes from a clinical background originally and has experience working in both clinical and HCI research environments. She is one of the organizers of the Workshop on Ethical Encounters in HCI held at CHI 2016 and 2017.

Jenny Waycott
Dr. Jenny Waycott is a Lecturer in the Department of Computing and Information Systems at the University of Melbourne. Her current work focuses on the design and use of new technologies to support older adults who are socially isolated. Jenny is the principal organizer of the CHI Workshop Series on “Ethical Encounters in HCI”, as well as serving as a full member on the ACM SIGCHI Ethics Committee.

Intended Audience (Level: Easy)

The course welcomes all attendees with interest in or who have conducted field studies of mobile interactive technologies, regardless of the particular ethics approval process or policy framework that is relevant to their discipline or country where this is conducted. No prior knowledge or experience is required.

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C04: Inbodied Interaction 101: A Human Physiology to Neurology Informed Approach to HCI Research and Design

1 unit(s) | Monday 2:00:00 PM – 3:15:00 PM | Course Website

Inbodied Interaction (II) aligns interaction design strategies with how the body’s internal processes function optimally. The purpose of this course is to provide an introduction to II by (i) overviewing these internal neuro-, physio-, chemic0- systems, (ii) offering a practical model to start to apply them in design (iii) exploring each through the lens of HCI examples. With this introduction, participants will have a functional map to deepen their knowledge of inbodied systems, and how using this alignment opens design spaces. This is also the foundation course for Inbodied Interaction 102: new measures for HCI and human performance design.

Instructor(s)

m.c. schraefel
m.c. is a researcher in pain/human performance and computer science and a certified strength and conditioning coach, nutritionist and functional neurologist. In HCI, she is a past health chair for CHI 2017/2018, and a past Technical Program Chair and Papers Chair. m.c. has co-lead various dagstuhls related to health and wellbeing; human performance. She iniitated and co-leads the body as starting point workshops, and the Inbodied Interaction Summer School, co sponsored by ACM SIGCHI

Aaron Tabor
Aaron is a PhD student in Computer Science/HCI at UNB. His work focuses on rigorous interrogation of the use of HRV as a measure of the efficacy of breathing rate in particular, and the connection of breathing depth in cognitive performance. He is interested in developing cognitive assessment test suites for personal self-assessment of health interventions.

Josh Andres
Josh leads HCI research at IBM Research, Australia, and has published particularly in exertion games, and is a founder of the Body as a Starting Point workshop series – he leads work on the use of PA for eBike acceleration control.

Intended Audience (Level: Easy)

The course is designed for anyone interested in HCI research/design that involves the human body. This includes researchers in health and wellbeing, exergames, cognitive performance, mindfulness. It offers a road map into the body’s complex internal processes by providing accessible models for approaching: what the body is as a complex adaptive system; main non-volitional, always on processes and systems; access to those systems via volitional, essential processes for life. From this practical mapping, researchers will be able to dig deeper into the physiology/neurology/chemistry of the body to help inform and expand their own HCI research and design work.

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C05: Inbodied Interaction 102: Understanding the selection and application of non-invasive neuro-physio measurements for inbodied interaction design

1 unit(s) | Monday 4:00:00 PM – 5:15:00 PM | Course Website

As a means to validate the effects of interaction designs, particularly those involving physiological processes, like: breathing in mindfulness; heartrate in exertion games, and blood flow to the brain for cognitive load assessments, HCI researchers are increasingly turning to body-based signals as signals to quantify effects and guide design decisions. These design decisions can be informed by Inbodied Interaction principles of aligning knowledge of how the body performs optimally (physiologically, neurologically) with our designs. The purpose of this course is to present new-to-HCI neuro-physiological measures including peripheral awareness, deep HRV, and new pre-cortical assessments to open new design opportunities. Students will leave the course with this set of new assessments, as well as practical worked examples of how to choose and apply which measures as best suited for a particular design and evaluation context.

Instructor(s)

m.c. schraefel
m.c. is a researcher in pain/human performance and computer science and a certified strength and conditioning coach, nutritionist and functional neurologist. In HCI, she is a past health chair for CHI 2017/2018, and a past Technical Program Chair and Papers Chair. m.c. has co-lead various dagstuhls related to health and wellbeing; human performance. She iniitated and co-leads the body as starting point workshops, and the Inbodied Interaction Summer School, co sponsored by ACM SIGCHI

Aaron Tabor
Aaron is a PhD student in Computer Science/HCI at UNB. His work focuses on rigorous interrogation of the use of HRV as a measure of the efficacy of breathing rate in particular, and the connection of breathing depth in cognitive performance. He is interested in developing cognitive assessment test suites for personal self-assessment of health interventions.

Josh Andres
Josh leads HCI research at IBM Research, Australia, and has published particularly in exertion games, and is a founder of the Body as a Starting Point workshop series – he leads work on the use of PA for eBike acceleration control.

Intended Audience (Level: Medium)

People who are interested in health and wellbeing design, exergames, human performance and are curious to explore new modes of assessment and new areas of the brain-body connection (like the midbrain and cerebellum) to inform design. Prerequistes are either Inbodied Interaction 101, inbodied interaction summer school or body as a starting point workshops.

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C10: So You Think You Can’t Draw? A Hands-on Introductory Course on Sketching in HCI Techniques

2 unit(s) | Tuesday 9:00:00 AM – 12:15:00 PM

Hand-drawn sketching is a practice as old as our ancestors. From cave painting to picture-books, we have explored the world with our visual senses. Within Human-Computer Interaction, sketches can be used to document, ideate, and describe concepts between researcher, user, or client. Attendees will leave the course with the confidence to engage actively with sketching on an everyday basis in their research practice.

Instructor(s)

Makayla Lewis
Makayla Lewis is a postdoctoral research fellow at University of the Arts London, she uses participatory and visual methods to explore human factors of cybersecurity, smart money, and artificial intelligence. Makayla is also an accomplished visual thinker and sketcher who organizes the monthly SketchnoteHangout.com, SketchnoteLDN amongst other sketching events and courses, and provides visuals and sketchnotes for international companies and conferences such as CHI and ISS.

Miriam Sturdee
Miriam Sturdee is a Research Fellow at Lancaster University, specialising in creative practices in computer science. She holds an MFA in Visual Communication from Edinburgh college of art, and works at the intersection of art and computing, as well investigating how sketching practice can support the development of novel technologies and public engagement.

Intended Audience (Level: Easy)

The content of this course is suitable for individuals from industry and academia that have an interest in learning and or improving their sketching skills. Novices, experts and those with an interest are welcome to attend. No prerequisites.

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C11: Sketching in HCI: Research Practice & Publication (Advanced)

2 unit(s) | Tuesday 2:00:00 PM – 5:15:00 PM | Course Website

Sketching in Human Computer Interaction is a valuable tool for subjective practice, but also a tool for engagement with collaborators, stakeholders, and participants. This hands-on practice can be utilised in a variety of contexts. The course enables those already in possession of sketching skills the confidence to take their work to the next level. Drawing from expertise gained by working in both academia and industry, the instructors will lead course attendees on a journey through practical applications of sketching in HCI, from subjective sketching to participant engagement and publishing, using hands on tasks and group activities.

Instructor(s)

Miriam Sturdee
Miriam Sturdee is a Research Fellow at Lancaster University, specialising in creative practices in computer science. She holds an MFA in Visual Communication from Edinburgh college of art, and works at the intersection of art and computing, as well investigating how sketching practice can support the development of novel technologies and public engagement.

Makayla Lewis
Makayla Lewis is a postdoctoral research fellow at University of the Arts London, she uses participatory and visual methods to explore human factors of cybersecurity, smart money, and artificial intelligence. Makayla is also an accomplished visual thinker and sketcher who organizes the monthly SketchnoteHangout.com, SketchnoteLDN amongst other sketching events and courses, and provides visuals and sketchnotes for international companies and conferences such as CHI and ISS.

Intended Audience (Level: Medium)

This course is aimed at those who already have experience with sketching and that are including (or begun to include) sketching in their everyday research and practice (practical applications) within the HCI context. Therefore we expect people joining this course to be confident in sketching their ideas and happy to share their images with the group.

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C15: Introduction to AI Fairness

1 unit(s) | Wednesday 9:00:00 AM – 10:15:00 AM | Course Website

Today, AI is used in many high-stakes decision-making applications in which fairness is an important concern. Already, there are many examples of AI being biased and making questionable and unfair decisions. Recently, the AI research community has proposed many methods to measure and mitigate unwanted biases, and developed open-source toolkits for developers to make fair AI. This course will cover the recent development in algorithmic fairness, including the many different definitions of fairness, their corresponding quantitative measurements, and ways to mitigate biases. This course is open to beginners and is designed for anyone interested in the topic of AI fairness.

Instructor(s)

Yunfeng Zhang
Yunfeng is a Research Staff Member at IBM Research AI. His research interests lie in the intersection between HCI and AI. His recent research projects involved creating conversational agents, modeling social interactions, and studying AI explainability, fairness, and trust. He contributed to the IBM’s AI Fairness 360 and AI Explainability 360 open source toolkits, which are designed to help AI developers create intelligible and fair AI solutions. He received his Ph.D. in computer and information science from the University of Oregon in 2015.

Rachel Bellamy
Rachel is a Principle Research Scientist and Chair of the Computer Sciences Council at IBM T J Watson Research Center, Yorktown Heights, New York. In this role she heads a Council that manages a Research portfolio of exploratory science projects. Prior to this, she led an interdisciplinary team of human-computer interaction researchers, user experience designers and software engineers. That team most recently contributed to several IBM Research’s Trusted AI projects, including the AI Fairness 360 and AI Explanability 360. Rachel received her doctorate in cognitive psychology from University of Cambridge, UK in 1991. She received a Bachelor of Science in psychology with mathematics and computer science from University of London in 1986. Before coming to IBM Research, she worked in Apple Computer’s Advanced Technology Group researching software support for collaborative learning.

Q. Vera Liao
Vera is a Research Staff Member in IBM Research AI. Her research interests are on human-AI interaction and intelligent user interfaces. Her current work focuses on user-aware conversational agents, human centered ma- chine learning, AI explainability and fairness. Her work contributed to IBM’s AI Explainability 360, an open-source toolkit providing educational and technical resources for AI explainability. Recently, she organized several workshops and a panel on topics that connect the HCI and AI communities at premier HCI conferences including ACM CSCW and IUI. She received her Ph.D. in computer science from the University of Illinois at Urbana-Champaign.

Moninder Singh
Moninder is a Research Staff Member in the IBM Research AI organization at the IBM T. J.Watson Research Center. He received his Ph.D. in Computer and Information Science from the University of Pennsylvania in 1998. He is primarily interested in developing and deploying solutions for interesting analytics and decision support problems. His main research areas are machine learning and data mining, artificial intelligence, data privacy, information retrieval, probabilistic modeling and reasoning, and text mining. He has been actively working in issues of fairness and trust in AI, has contributed to the IBM’s AI Fairness 360 and AI Explainability 360 open source toolkits, and has given several tutorials/talks and published papers on issues relating to trust in AI models.

Intended Audience (Level: Easy)

The intended audience for this course is any CHI attendees who have already, or intend to engage in developing, designing and researching on the topic of AI fairness. The course does not require any advanced knowledge in AI, data science or programming, though a basic understanding of machine learning concepts such as classification, training data, and features could be helpful. The course will include 20-30 minutes hands-on practice with Python scripts provided. Interested attendees could further explore the code but programming is not required. Course instructors will provide introductory materials for machine learning and Python programming beforehand for interested attendees.

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C16: Machine Learning for Non-Programmers

4 unit(s) | Wednesday 9:00:00 AM – 5:15:00 PM

Machine learning (ML) for data analysis have attracted the HCI community in the recent years. Multiple prebuilt ML libraries are available for popular programming languages such as R and Python to build and evaluate ML models. However, their usage demands good programming knowledge. The proposed course relaxes the need of programming by offering the model building via an open-source data mining tool called Orange. Orange features drag-and-drop functionality which enables ML developers to focus on model building rather than worrying about coding syntax. This course introduces the complete data mining pipeline with hands-on exercises on build and evaluating ML models.

Instructor(s)

Dvijesh Shastri
Dr. Dvijesh Shastri is an Associate Professor of Computer Science at the University of Houston – Downtown. His research interest is in affective computing, human behavior analysis, and data analytics. He has developed a series of computer vision and machine learning algorithms that capture physiological signals from facial thermal imagery for detecting individuals’ psychological states. He has co-authored multiple publications in the field of Human-Computer Interaction. He has been teaching graduate data analytics courses including machine learning, data visualization, and Python for data analytics.

Intended Audience (Level: Easy)

Anyone with interest in learning machine learning for data analysis can attend the course. This includes those who have no knowledge of machine learning as well as those who are novice to this field. The course will benefit to those too who are primarily interested in learning the Orange tool.

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C18: Future Cars as a Space for Work & Play — Non-Driving-Related Tasks in the Transition to Automated Driving

3 unit(s) | Wednesday 11:00:00 AM – 5:15:00 PM | Course Website

The objective of this CHI course is to provide CHI attendees with an introduction and overview of the rapidly evolving field of automotive user interfaces (AutomotiveUI). The course will focus on UI aspects in the transition towards automated driving. In particular, we will also discuss the opportunities of cars as a new space for non-driving-related activities, such as work, relaxation, and play. For newcomers and experts of other HCI fields, we will present the special properties of this field of HCI and provide an overview of new opportunities, but also general design and evaluation aspects of novel automotive user interfaces.

Instructor(s)

Bastian Pfleging
Bastian Pfleging is assistant professor for Future Mobility at Eindhoven University of Technology, Netherlands. His research interests are user interfaces for future mobility, multimodal interaction, workload [10, 13], and non-drivingrelated activities [7, 12]. Bastian is actively involved in organizing conferences like CHI, UIST, AutomotiveUI, MobileHCI and is steering committee member of AutomotiveUI.

Andrew Kun
Andrew L. Kun is professor of Electrical and Computer Engineering at the University of New Hampshire. His research focus is human-computer interaction in vehicles [3, 4, 6, 5], as well as the use of visual behavior and pupil diameter measures [10] to assess and improve the design of interfaces. He is the steering committee chair of AutomotiveUI.

Orit Shaer
Orit Shaer is Associate Professor of computer science and director of Media Arts and Sciences at Wellesley College. Her expertise is in designing, implementing and evaluating novel human-computer interactions including augmented reality (e.g. [15], and tangible interaction [14]. She serves as program co-chair of the 2020 ACM Tangible, Embedded, and Embodied Interaction (TEI) conference.

Intended Audience (Level: Easy)

We target a broad audience including AutomotiveUI novices (students, industrial / academic researchers), but also researchers, practitioners, and designers with experiences in creating AutomotiveUIs. With the upcoming driving automation, we see the car as a novel platform for interactive systems, which makes it interesting for a multitude of attendees.

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C19: Exploring Human-Drone Interaction

1 unit(s) | Wednesday 4:00:00 PM – 5:15:00 PM | Course Website

Drones are becoming increasingly interactive and offer novel opportunities for mobile interactions. This hands-on course will present rapid prototyping techniques for designing drone interfaces. We will use physical prototyping to approach participatory design techniques when designing future interactions, and digital prototyping tools with small-sized drones using Python (with an option for visual programming) to implement part of the interaction. The course will include an introduction to the field of human-drone interaction and its methodologies, two hands-on prototyping sessions with physical materials and digital tools, and a presentation session where participants get to show off their prototypes!

Instructor(s)

Jessica Cauchard
Dr. Jessica Cauchard is an Assistant Professor in the department of Industrial Engineering and Management at Ben Gurion University of the Negev in Israel. She is a leading researcher in the field of human-drone interaction and has extensive experience in developing and presenting workshops and courses for academic and professional audiences. Dr. Cauchard has a strong interest in autonomous vehicles and intelligent devices and how they change our device ecology. She completed her PhD at the University of Bristol, UK in Computer Science in 2014 and then worked as a postdoctoral scholar at Stanford University where she received a Magic Grant for her work on interacting with drones by the Brown Institute for Media Innovation in 2015.

Intended Audience (Level: Easy)

The course is designed for an audience that is new to or excited about interacting with drones. Participants with basic HCI, user experience, or interaction design skills will find the contents of this course accessible. No prototyping or programming skills are required, although some familiarity with programming is helpful.

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C20: Additional Insights: How to use Eye Tracking and Brain Sensing in Virtual Reality

1 unit(s) | Thursday 9:00:00 AM – 10:15:00 AM | Course Website

Virtual Reality has the potential to transform the way we work, rest and play. We are seeing use cases as diverse as education and pain management, with new applications being imagined every day. Virtual Reality technology comes with new challenges, and many obstacles need to be overcome to ensure good user experience. Recently many new Virtual Reality systems with integrated eye-tracking have become available. At the same time, many research labs are using Functional Near-Infrared Spectroscopy (fNIRS) to non-invasively measure brain activity and serve as a brain-computer interface. This course presents timely, relevant information on how Virtual Reality can leverage eye-tracking and brain activity data to optimize the user experience and to alleviate usability issues surrounding many challenges in immersive VEs. The integration of these sensors allows us to determine additional insights into human behavior, including where the viewer is focusing their attention, and monitor cognitive load. Advancing these approaches could make the Virtual Reality experience more comfortable, safe and effective for the user, and open a new world to facilitate new experimentation for Human Computer Interaction (and Brain Computer Interaction) researchers.

Instructor(s)

Ann McNamara
Ann McNamara is an Associate professor in the Department of Visualization at Texas A&M University. Her research focuses on novel approaches for optimizing an individual’s experience when creating, viewing and interacting with virtual and augmented spaces. She is the recipient of an NSF CAREER AWARD entitled Advancing Interaction Paradigms in Mobile Augmented Reality using Eye Tracking. This project investigates how mobile eye tracking, which monitors where a person is looking while on the go, can be used to determine what objects in a visual scene a person is interested in, and thus might like to have annotated in their augmented reality view. In 2019, she was named as one of twenty-one Presidential Impact Fellows at Texas A&M University

Ranjana Mehta
Ranjana Mehta is an Associate professor in the Department of Industrial and Systems Engineering at Texas A&M University. Her research in the Neuro-Ergonomics Lab utilizes theories, methods, and techniques from physiology, biomechanics, neuro-science, psychology, and public health to better understand operator behavior and capabilities when interacting with simple and complex work systems. HF/E investigations involve examining multi-factorial causes and consequences of operator stress and fatigue, brainbehavior relationships with changing workforce demographics (aging, obesity), and development of HF/E tools to assess operator health and performance in hazardous work environments. She is the recipient of numerous awards including the Creativeness in Ergonomics Practitioner of the Year Award, Applied Ergonomics Society (IISE), 2019, the William C. Howell Young Investigator Award, Human Factors and Ergonomics Society, 2017, and the James G. Zimmer New Investigator Research Award, American Public Health Association, 2014

Intended Audience (Level: Easy)

The target audience for this course is researchers interested in applying eye-tracking and brain activity sensing in VirtualReality. This course represents a birds-eye view of the eye-movements, eye-tracking, brain activity capture, metrics available, data capture and analysis, and state-of-the-art applications of sensing in VR. Those wishing to grasp the basics will all benefit from this course

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C24: Introduction to Explainable AI

1 unit(s) | Thursday 11:00:00 AM – 12:15:00 PM | Course Website

As Artificial Intelligence (AI) technologies are increasingly used to make important decisions and perform autonomous tasks, providing explanations that allow users to understand the AI has become a ubiquitous concern in human-AI interaction. Recently, a number of open-source toolkits are making the growing collection of of Explainable AI (XAI) techniques accessible for researchers and practitioners to incorporate explanation features in AI systems. This course is open to anyone interested in implementing, designing and researching on the topic of XAI, aiming to provide an overview on the trends and methods of XAI and also help attendees gain hands-on experience of creating different styles of explanation with an XAI toolkit.

Instructor(s)

Q. Vera Liao
Vera is a Research Staff Member in IBM Research AI. Her research interests are on human-AI interaction and intelligent user interfaces. Her current work focuses on user-aware conversational agents, human centered machine learning, AI explainability and fairness. Her work contributed to IBM’s AI Explainability 360, an open-source toolkit providing educational and technical resources for AI explainability. Recently, she organized several workshops and a panel on topics that connect the HCI and AI communities at premier HCI conferences including ACM CSCW and IUI. She received her Ph.D. in computer science from the University of Illinois at Urbana-Champaign.

Moninder Singh
Moninder is a Research Staff Member in the IBM Research AI organization at the IBM T. J.Watson Research Center. He received his Ph.D. in Computer and Information Science from the University of Pennsylvania in 1998. He is primarily interested in developing and deploying solutions for interesting analytics and decision support problems. His main research areas are machine learning and data mining, artificial intelligence, data privacy, information retrieval, probabilistic modeling and reasoning, and text mining. He has been actively working in issues of fairness and trust in AI, has contributed to the IBM’s AI Fairness 360 and AI Explainability 360 open source toolkits, and has given several tutorials/talks and published papers on issues relating to trust in AI models.

Yunfeng Zhang
Yunfeng is a Research Staff Member at IBM Research AI. His research interests lie in the intersection between HCI and AI. His recent research projects involved creating conversational agents, modeling social interactions, and studying AI explainability, fairness, and trust. He contributed to the IBM’s AI Fairness 360 and AI Explainability 360 open source toolkits, which are designed to help AI developers create intelligible and fair AI solutions. He received his Ph.D. in computer and information science from the University of Oregon in 2015.

Rachel Bellamy
Rachel is a Principal Research Scientist and Chair of the Computer Sciences Council at IBM T J Watson Research Center. In this role she heads a Council that manages a Research portfolio of exploratory science projects. Prior to this, she led an interdisciplinary team of human-computer interaction researchers, user experience designers and software engineers. That team most recently contributed to several IBM Research’s Trusted AI projects, including the AI Fairness 360 and AI Explanability 360. Rachel received her doctorate in cognitive psychology from University of Cambridge, UK. She received a Bachelor of Science in psychology with mathematics and computer science from University of London. Before coming to IBM Research, she worked in Apple Computer’s Advanced Technology Group researching software support for collaborative learning

Intended Audience (Level: Easy)

The intended audience for this course are any CHI attendees who have already, or intend to engage in developing, designing and researching on the topic of XAI. The course does not require any advanced knowledge in AI, data science or programming, though a basic understanding of machine learning concepts such as classification, training data, and features could be helpful. The course will include 20 minutes hands-on practice with Python code samples provided. Interested attendees could further explore the code but programming is not required. The course instructors will provide instructions to use the code samples, as well as introductory materials for machine learning and Python programming beforehand for interested attendees.

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C01: Brainstorming 101: An Introduction to Ideation Techniques

3 unit(s) | Monday 11:00:00 AM – 5:15:00 PM | Course Website

Brainstorming 101 is an introductory course intended for beginner researchers and practitioners. Throughout the course, they will get acquainted with various ideation techniques to aid them in different phases of product design. The course progresses from a problem statement to a matured solution by introducing various unconventional ideation techniques addressing questions such as 1) How to divide problems into sub-problems? 2) How to find initial solutions? 3) How to dig deeper into the solutions? 4) How to combine ideas into one solution? 5) How to find the benefits and drawbacks of the solution? As a result, the participants will get hands-on experience of various ideation techniques suited to address these questions. Furthermore, they shall explore the key features, pros, and cons of each technique.

Instructor(s)

Sarah Suleri
Sarah Suleri is currently working as a UX researcher at the User-Centered Ubiquitous Computing department at Fraunhofer Institute for Applied Information Technology in Germany. She also teaches courses such as User-Centered Design and Design Thinking at RWTH Aachen University to bachelor’s and master’s students. She did her MSc. Media Informatics from RWTH Aachen University majoring in HCI with her focus on brain-computer interfaces. She is a certified professional for Usability, User Experience, and Requirement Engineering. She has worked on various European Union research projects, namely SatisFactory, CPSwarm, MONICA, eFactory, and DEMETER.

Intended Audience (Level: Easy)

This course is intended for beginner researchers and practitioners to get acquainted with different ideation techniques that can benefit them at various stages of product design. It is a hands-on course where 20-25 participants will experience these techniques, present their ideas, and discuss the pros and cons of each technique with others.

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C21: Designing for Sensory Appreciation: Cultivating Somatic Approaches for Experience Design

2 unit(s) | Thursday 9:00:00 AM – 12:15:00 PM | Course Website

This course explores somatic approaches to experience design in HCI. Designing for Sensory Appreciation focuses on cultivating our bodily sensory experience as a resource for design. This course exemplifies how somatic approaches can be applied through sensory appreciation in the form of case studies that incorporate experience-based activities. We invite a rethinking of the process of designing for technology based on the emerging somatic turn within Human Computer Interaction that acknowledges design for the experience of the self and recognizes the interiority of human experience as an equal partner in technological design processes.

Instructor(s)

Thecla Schiphorst
Dr. Thecla Schiphorst is a Professor in the School of Interactive Arts & Technology at Simon Fraser University. She has a 30 year history in designing for body-centered interaction and was one of forerunners of introducing somatic practices to the field of Interaction Design within HCI.

Lian Loke
Dr Lian Loke is a Senior Lecturer in Design Computing, and Director of the Master of Interaction Design and Electronic Arts, where she teaches interaction design and design research. Her research is at the nexus of performance, somatics, design and technology, and explores the aesthetics of interaction with the body as a central focus. Schiphorst and Loke are co-authors of an upcoming book: Experience as Skill: Transforming Ourselves Through a Somatic Design Focus (Springer 2020).

Kristina Höök
Dr. Kristina Höök is Professor of Interaction Design at the Royal Institute of Technology (KTH), Stockholm. Her recent book, Designing with the Body: Somaesthetic Interaction Design (MIT Press 2018) introduces soma design; a process that reincorporates body and movement into design that has long privileged language and logic.

Intended Audience (Level: Easy)

The intended audience members are HCI design practitioners, researchers and students that are interested in cultivating and applying somatic practices such as sensory appreciation to interaction and experience design processes. Audience members may be new to the topic or have prior experience in soma-design or body-based design explorations. We will conduct a pre-course poll in order to assess audience prior experience.

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C07: How to Write CHI Papers, Fourth Edition

3 unit(s) | Tuesday 9:00:00 AM – 3:15:00 PM | Course Website

Writing research papers can be extremely challenging specifically for scientific communities with their own review and style guidelines like CHI. The impact of everything that we do as researchers is based on how we communicate it. That is why writing for CHI is a core skill to learn because it is hard to turn a research project into a successful CHI publication. This fourth edition of the successful CHI paper writing course offers hands-on advice and more in-depth tutorials on how to write papers with clarity, substance, and style. It is structured into three 80-minute unit(s) with a focus on writing CHI papers.

Instructor(s)

Lennart Nacke
Lennart E. Nacke, Ph.D., is an Associate Professor for Human-Computer Interaction and Game Design at the University of Waterloo. He has taught the previous three iterations of this course at CHI since 2017. He runs the successful How to Write CHI Papers podcast and an interview series about writing CHI papers on YouTube. He has served on SIGCHI program and steering committees and taught University graduate classes on HCI research methods. Dr. Nacke has co-organized many workshops for CHI over the past five years; he also chaired the CHI PLAY 2014 and Gamification 2013 conferences, served as technical program co-chair for CHI PLAY 2015 and CHI Games and Play subcommittee co-chair for CHI 2017, INTERACT 2019 Full Papers Co-Chair, and was the chair of the CHI PLAY steering committee until 2018. He has also reviewed hundreds of papers and gotten lots of his own submissions rejected from CHI.

Intended Audience (Level: Medium)

This course introduces principles about writing (and to a lesser extent reviewing) for CHI to a junior audience. However, this does not mean that this course is not useful for senior CHI researchers, but the primary target audience is junior researchers. Thus, this course is particularly useful for young researchers, ranging from graduate students to postdocs and junior faculty. The expectation for the course audiences is that people have at least tried to submit a paper to CHI before (not necessarily that they have had one accepted) so that they are familiar with basic PCS terminology and the concept of the CHI conference (and CHI research in general).

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C14: How to: Peer Review for CHI (and Beyond)

4 unit(s) | Wednesday 9:00:00 AM – 5:15:00 PM | Course Website

A key challenge for people that are new to reviewing is pitching the review at the right level, and getting the tone and structure of a review right. This course aims to help participants understand a) the different expectations of different venues and submission types, b) the processes they use to make decisions, and c) good techniques for producing a review for these different circumstances. Combined with developing a good understanding of these different expectations, participants have a chance to critique anonymised proto-reviews, and try to guess the venue they are written for and the recommendation they make.

Instructor(s)

Max Wilson
The course is delivered by Dr Max L. Wilson, as Associate Professor at the University of Nottingham. Max, who currently sits on the CHI Steering Committee, has been a reviewer for CHI for over 10 years, and has reviewed for many other conferences including CSCW, UIST, SIGIR, CHIIR (and its former IIiX), ISWC, WWW, UbiComp and MobileHCI. Max has also reviewed for journals including: JASIST, JWS, IJHCI, IP&M, TOIS, TOCHI.

Intended Audience (Level: Easy)

Anyone new to reviewing (no prerequisites).

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C08: Online Survey Methodology for User Experience Research: A Framework for Utility and Quality

4 unit(s) | Tuesday 9:00:00 AM – 5:15:00 PM

Online surveys are an extremely popular research method in HCI and UX research. Surveys are often perceived to be easy to create [1] and sometimes used even if they are not the most appropriate method [7]. This course will review state-of-the-art methods, drawing from the past 20 years of research on online surveys [3, 4] and present applications for the user experience and HCI context [8]. Upon completion of the class, attendees will have a framework of survey quality, a roadmap to plan & implement, and resources to extend their knowledge of surveys for HCI and UX research. The instructors have conducted hundreds of surveys that tech companies use on a regular basis to inform business and product decisions. They also consult and reviews surveys on a daily basis. Finally, they regularly teach survey research, and have been instrumental in connecting User Experience Research with survey research principles and measurement best practices.

Instructor(s)

Mario Callegaro
Mario Callegaro is Senior UX Survey Research Scientist in the Google Cloud Platform UX (CPUX), team. He focuses on helping the team in collecting high quality surveys about our cloud platform products. Mario holds a M.S. and a Ph.D. in Survey Research and Methodology from the University of Nebraska, Lincoln. He has published over 40 peer-reviewed papers and book chapters and made over 150 conference presentations nationally and internationally in the area of survey methodology. Mario has published two books on web surveys: Web Survey Methodology (with Katja Lozar-Manfreda and Vasja Vehovar) and an edited book titled Online Panel Research: A Data Quality Perspective (Wiley). He has taught survey research at Google for the past 10 years and teaches ”Web Survey Methodology” at the online program in Survey and Data Science (IPSDS).

Ana Villar
Ana Villar is UX researcher at Facebook. She has worked in the field of survey methodology for over 20 years, specializing in cross-cultural surveys. In the past, Ana directed the cross-national online survey (CRONOS) panel, worked for the European Social Survey, and was a member of the Political Psychology Research Group at Stanford. Ana has published on the areas of web survey data collection, mixed mode data collection, and cross-cultural survey research. She has a Ph.D. in Survey Research and Methodology from the University of Nebraska-Lincoln.

Aaron Sedley
Aaron Sedley is a Staff User Experience Researcher at Google, focused on measuring users’ attitudes via surveys. Aaron initiated Happiness Tracking Surveys (HaTS) at Google in 2006, a platform that measures attitudes in the context of product usage, which is deployed across Google’s products. In addition to his leadership on HaTS, Aaron consults across Google on survey methodology, planning and implementation. Aaron also focused on Change Aversion at Google, establishing principles to minimize negative reactions when launching changes to a familiar product. Aaron co-authored (with Hendrik Müller and Elizabeth Nunge) the chapter Survey Research in HCI, in Ways of Knowing in HCI, pp. 229-266 (Springer), and taught two popular survey methodology courses (with Hendrik Müller) at CHI in 2014 and 2015. Prior to joining Google, Aaron held research positions with New York Times Digital, Young & Rubicam, and the Carnegie Endowment for International Peace. He earned a bachelor’s degree in Government from Wesleyan University (CT).

Intended Audience (Level: Medium)

The intended audience is user experience researchers and designers who conduct or want to conduct surveys as part of their job. We also welcome HCI and related fields students interested in improving their survey skills.

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C12: Practical UX Research Methodologies: Contextual Inquiry

2 unit(s) | Tuesday 2:00:00 PM – 5:15:00 PM

Half-Day course which utilizes both lectures and interactive activities to demonstrate the practical UX research methodology of contextual inquiry. Experts from UEGroup, a Silicon Valley research and design company, will lead an interactive discussion and give practical suggestions for developing contextual inquiry methodologies including: ensuring how to get the best results, and understanding how to extend learning past the initial visit.

Instructor(s)

Sarah Garcia
Sarah Garcia is UEGroup’s Director of Research with a background in market and user experience research. Sarah’s experience with UX research is extensive, ranging from consultancy work with Disney Interactive Media and Google to groundbreaking medical research for companies such as Boston Scientific and Stryker. Sarah is experienced with on screen and device usability, developing innovative testing methodologies and training while mentoring other UEGroup staff for the past 14 years.

Intended Audience (Level: Easy)

Course attendees will gain a better understanding of how to plan and execute in context research no matter the budget or time constraints. Course attendees will be able to write a flexible research plan, understand techniques for note-taking, observing and creating actionable insights. This course will be interactive with a lot of opportunities to practice observational skills. No previous experience is required, but even those with some experience will benefit from refreshing new methods.

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C23: Usability Testing: Creative Techniques for Answering Your Research Questions

2 unit(s) | Thursday 9:00:00 AM – 12:15:00 PM

Half-day course which utilizes both lectures and interactive activities to demonstrate the practical UX research methodology of usability testing. Experts from UEGroup, a Silicon Valley research and design company, will lead an interactive discussion and give practical suggestions for developing usability testing methodologies including: understanding the available metrics for measuring; writing a test plan, recruiting participants, insuring the participant is engaged and comfortable, as well as moderating, data analysis and reporting guidance. Given that technology and methodologies are constantly changing, this course will focus on ways to be creative with the resources available, in order to best satisfy research needs.

Instructor(s)

Sarah Garcia
Sarah Garcia is UEGroup’s Director of Research with a background in market and user experience research. Sarah’s experience with UX research is extensive, ranging from consultancy work with Disney Interactive Media and Google to groundbreaking medical research for companies such as Boston Scientific and Stryker. Sarah is experienced with on screen and device usability, developing innovative testing methodologies and training while mentoring other UEGroup staff for the past 14 years.

Intended Audience (Level: Easy)

This course offers practical information on conducting usability testing in various forms, both traditional and non-traditional. If you’re looking to hone your research skills and gain inspiration for new approaches to usability testing, this course is for you.

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C09: Rapid Prototyping for AR/VR Experiences

2 unit(s) | Tuesday 9:00:00 AM – 12:15:00 PM | Course Website

This course will provide an introduction to techniques for rapid prototyping for Augmented Reality (AR) and Virtual Reality (VR) experiences. With the rise of consumer head mounted displays and powerful mobile phones, AR and VR is becoming increasingly popular. However, until recently, developing AR and VR experiences required strong programming skills. In this course participants will learn how to rapidly prototype AR/VR experiences without the need for programming. Using a mixture of lecture and hands-on activities participants will learn about methods for quickly creating their own AR/VR interfaces. The course will use a mixture of traditional prototyping tools such as sketching, as well as easy to use, free tools for creating AR/VR experiences. This is an ideal course for people who was to quickly prototype and test the core elements of AR/VR experiences before developing their final applications. This will be particularly valuable for User Centred Design/Interaction Design approaches to AR/VR where the focus is on iteratively prototyping experiences as soon as possible to get feedback from the intended users. The course is accompanied by a website which contains all of the course material, plus links to papers, videos, tools, websites, and software tools useful for AR/VR rapid prototyping.

Instructor(s)

Mark Billinghurst
Mark Billinghurst is Professor of Human Computer Interaction at the University of South Australia in Adelaide, Australia, and Professor in the BioEngineering Institute at the University of Auckland in New Zealand. He earned a PhD in 2002 from the University of Washington and researches innovative computer interfaces that explore how virtual and real worlds can be merged, publishing over 500 research papers in topics such as wearable computing, Augmented Reality and mobile interfaces. Prior to joining the University of South Australia he was Director of the HIT Lab NZ at the University of Canterbury, in Christchurch, New Zealand. He has also previously worked at British Telecom, Nokia, Google, and the MIT Media Laboratory, and is a current Amazon Scholar. He received the 2013 IEEE VR Technical Achievement Award for contributions to research and commercialization in AR and in 2019 the IEEE VGTC Virtual/Augmented Reality Career Award for lifetime contributions to Human-Computer Interactions for Augmented and Virtual Reality.

Intended Audience (Level: Easy)

This course is for practitioners who would like to be able to quickly create their own AR/VR experiences. There is no prerequisite experience needed.

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C13: Introduction to Re-Programmable Color-Changing Materials

1 unit(s) | Tuesday 4:00:00 PM – 5:15:00 PM

Re-programmable materials, such as those which can change their color in response to external stimuli, hold the promise for a future in which objects will re-configure according to a user’s needs. In this course, we will provide participants with an in-depth understanding of color-changing materials, brainstorm novel applications in HCI, discuss technical solutions to realize participants’ ideas, and conduct a hands-on session with one color-changing system from our prior works. Our team is uniquely positioned to host this workshop since we combine expertise in materials, optics, computational geometry, and personal fabrication. At the end of this course, we will summarize the results as a research agenda for future work on re-programmable color-changing materials.

Instructor(s)

Yuhua Jin
Yuhua Jin (Postdoctoral Associate MIT CSAIL) conducts research at the intersection of HCI and Optical Engineering. His current work focuses on developing novel optical methods for personal fabrication tools. His recent work PhotoChromeleon has received a Best Paper Award at ACM UIST 2019.

Isabel Qamar
Isabel Qamar (Postdoctoral Associate MIT CSAIL) conducts research at the intersection of HCI and Material Science to develop re-programmable and interactive materials. She has received best paper and honorable mention awards for her work at ACM CHI and UIST and has hosted inter-disciplinary workshops aimed at bridging these fields.

Michael Wessely
Michael Wessely (Postdoctoral Associate MIT CSAIL) conducts research on developing interactionaware materials that can change shape and color, and scale from small prototypes to interactive architecture. He has published several papers at ACM CHI and ACM UIST including one best paper award.

Stefanie Mueller
Stefanie Mueller (Assistant Professor MIT CSAIL) conducts research on how personal fabrication and advances in material science can be used to create personal physical objects that adapt themselves over time to better accommodate a users’ preferences and needs. Stefanie has also given a range of live demos, and organized workshops, tutorials, and courses over the last few years at ACM CHI and ACM UIST.

Intended Audience (Level: Easy)

Researchers/practioners interested in color-changing materials and their potential applications to HCI. No prerequisite experience is required.

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C17: Prototyping Transparent and Flexible Electrochromic Displays

3 unit(s) | Wednesday 9:00:00 AM – 3:15:00 PM | Course Website

This course is a hands-on introduction to the fabrication of flexible, transparent free-form displays based on electrochromism for an audience with a variety of backgrounds, including artists and designers with no prior knowledge of physical prototyping. Besides prototyping using screen printing or ink-jet printing of electrochromic ink and an easy assembly process, participants will learn essentials for designing and prototyping electrochromic displays

Instructor(s)

Markus Löchtefeld
Markus Löchtefeld is an Associate Professor in the Department of Architecture, Design and Media Technology at Aalborg University, Denmark. He teaches interactive device prototyping and interaction design methods and his research focuses on wearable- and tangible computing as well as novel prototyping and fabrication techniques.

Walther Jensen
Walther Jensen is a PhD Student in the Department of Architecture, Design and Media Technology at Aalborg University, Denmark. His research focuses on novel fabrication techniques for ambient displays as well as Human-Drone interaction.

Heiko Müller
Heiko Müller is a post-doctoral researcher in the UX team at the University of Lapland. He has a background in ambient light displays.

Ashley Colley
Ashley Colley is a User Experience researcher and Senior Researcher in the UX team at University of Lapland. He has an extensive background as a creative technologist, e.g. among wellness tracking and interactive prototypes.

Intended Audience (Level: Easy)

The course is intended for an audience that wants to know about prototyping with flexible displays and printed electronics. Participants should have sufficient technical background to download, install and run the Arduino programming environment on their laptops, and be able to physically handle (or have assistance handling) simple manual prototyping techniques. Furthermore, basic knowledge of graphical design and image editing as well as basic electronics will be an advantage.

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C22: Make This! Introduction to Electronics Prototyping Using Arduino

2 unit(s) | Thursday 9:00:00 AM – 12:15:00 PM | Course Website

This course is a hands-on introduction to interactive electronics prototyping for people with a variety of backgrounds, including those with no prior experience in electronics. Familiarity with programming is helpful, but not required. Participants learn basic electronics, microcontroller programming and physical prototyping using the Arduino platform, then use digital and analog sensors, LED lights and motors, to build, program and customize a small paper robot.

Instructor(s)

Nikolas Martelaro
Nikolas Martelaro is an Assistant Professor at Carnegie Mellon’s Human-Computer Interaction Institute. His research includes creating new tools to support interaction design with interactive and intelligent objects. Nik holds a Ph.D. in ME Design from Stanford.

J.D. Zamfirescu-Pereira
J.D. Zamfirescu-Pereira is a Ph.D. student at University of California at Berkeley, and an Assistant Professor at California College of the Arts. He teaches hands-on programming and electronics to artists and designers, and studies how humans interact with autonomous systems. He holds a Masters degree in EECS from MIT.

David Goedicke
David Goedicke is an Information Science Ph.D. Student at Cornell Tech focusing on building simulations to understand design for automation. He received his Masters in Human-Media Interaction from Twente University.

Wendy Ju
Wendy Ju is an Assistant Professor of Information Science with the Jacobs Technion-Cornell Institute at Cornell Tech in NYC. She received her Ph.D. from Stanford and her Masters from the MIT Media Lab, and is the author of The Design of Implicit Interactions, available from Morgan and Claypool.

David Sirkin
David Sirkin is Executive Director for Interaction Design Research at the Center for Design Research at Stanford. He teaches design methodology, and studies human-robot and autonomous vehicle interaction. He received his PhD from Stanford, and Masters degrees in EECS and Management from MIT.

Intended Audience (Level: Easy)

The course is intended for an audience that is new to, wants to know more about, or already has a passing familiarity with, the tools, techniques, and resources for electronics and physical prototyping. No electronics, programming, or prototyping experience is required, although some familiarity with programming is helpful.

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