Objectives
Design reviews are often ineffective—way too often! We fail to achieve the goals of the review, have unproductive battles over personal opinion, and perhaps even leave in tears. Even experienced teams have these problems. We need to do better!
This workshop explores why traditional design reviews are often ineffective (hint: focusing on personal opinion or minor details never helps), practical tools to make reviews more productive, and different design review techniques. We will explore how to give and receive effective design feedback, and the value of using design review rules—especially for cross-function teams. We will work in teams to perform several design reviews of the same app (a baseline, a streamlined cognitive walkthrough, and a scenario review) to try the different techniques and see the pros and cons of each first hand.

About the Speaker(s) Everett McKay is Principal of UX Design Edge and a UX design trainer and consultant with global clientele. Everett's specialty is finding practical, intuitive, simple, highly usable solutions quickly for web, mobile, and desktop applications. Everett has over 30 years' experience in user interface design and has delivered UX design workshops to an international audience that includes Europe, Australia, Asia, South America, and Africa. Everett is author of "Intuitive Design: Eight Steps to an Intuitive UI", the definitive guide to designing intuitive interactions, and "UI Is Communication: How to Design Intuitive, User Centered Interfaces by Focusing on Effective Communication", a groundbreaking approach to UI design using human communication-based principles and techniques. While at Microsoft, Everett wrote the Windows UX Guidelines for Windows 7 and Windows Vista. Everett holds a master's degree in computer science from MIT.

Understanding a person’s psychophysiological condition is crucial for different fields of applications, including health monitoring and cognitive stress measurement. Continuous measurement helps us understand the physical and cognitive condition of a person. Heart rate, breathing rate, blood pressure and heart rate variability helps to assess the affective nature of a person. This can help study stress level, attention, fatigue, discomfort, delirium, and productivity of a human being including a factory worker, or a driver. But Most of the measurement methods available in practice require instrumentation, which are often intrusive in nature, impossible to use for continuous monitoring and need experts to operate. Remote measurement eases the inconvenience associated with contact-based devices, reduces person hour, and enables safer alternative. The recent pandemic has further demonstrated the importance of contactless measurement methods. One major part of this tutorial will cover remote measurement of vital signs.
The tutorial will also discuss recent advances in ubiquitous health monitoring. Ubiquitous health monitoring refers to the continuous and seamless monitoring of an individual's health and physiological parameters using various interconnected and pervasive technologies. The goal of ubiquitous health monitoring is to provide real-time and non-intrusive data collection, analysis, and feedback to support healthcare and promote wellness. This concept leverages the widespread adoption of wearable devices, Internet of Things (IoT) sensors, and other smart technologies to monitor a person's health status constantly, regardless of their location or activity.

In this tutorial we would present how the community can take advantage of recent developments in wearables and remote measurement for continuous monitoring of vital signs. With increasing use of cyber physical systems, internet of things across industries including wearables, remote measurement is gaining more attention than ever. Due to the development of artificial intelligence and emergence of big data analysis in last decade, vital sign measurements are now very accurate and can extract different modalities of vital sign. This tutorial aims to provide a comprehensive detail of all such development, underlying technology, and their scope in human factor research.

This tutorial will discuss several important components of remote measurements and summarizes work from last two decades in a half-day session:

1. Scopes: First, we’ll discuss the scopes and promises of remote measurement of vital signs (heart rate, respiration rate, blood pressure, heart rate variability), and ubiquitous health monitoring across industry and discuss the benefits. This part will further discuss the scope of ubiquitous health monitoring, related challenges, sensors, and technologies. (Dr. Lynn Abbott) - 30 min
2. Application: Next, we’ll discuss the roles of vital sign in psychophysiological measures including arrythmia, cognitive stress, attention, fatigue, discomfort, and drowsiness. (Dr. Abhijit Sarkar) – 30 min
3. Existing Methods: Next, we’ll discuss promises and limitations of existing methods for remote measurement of vital signs. This includes methods that uses conventional cameras, RF cameras, radar, Wifi. This will highlight some of the major accomplishment for each of the methods. (Dr. Lynn Abbott) – 30 min
4. Break – 15 min
5. Ubiquitous health monitoring (UHM): This session will discuss what UHM is, components of UHM, current state of research in wearable technologies, cloud-based computing of health data, and how advanced data analytics techniques are used for UHM (Dr. Sarkar, Dr. Abbott).
6. Camera based method: (Dr. Abhijit Sarkar) – 60 minutes
a. First, we’ll discuss how data from RGB and NIR cameras contains blood volume pulse information from human face.
b. Next, we’ll discuss challenges from motion and ambient illumination and methods to address those challenges.
c. Next, we’ll show how advance computer vision, signal processing, and machine learning methods including deep learning are used to extract blood volume pulse, and respiration rate.
d. Next, we’ll discuss how thermal imaging can be used for the study of human psychophysiology.
e. Finally, we’ll discuss next frontiers in remote measurements, and current states.
7. Discussion: (Dr. Abhijit Sarkar, Dr. Lynn Abbott) – (15 minutes)

About the Speaker(s) Dr. Sarkar is a Senior Research Associate in the Virginia Tech Transportation. He leads the computer vision and machine learning group in the division of Data and Analytics. His current research focuses on application of computer vision, machine learning, biometric, and big data analysis for transportation safety, driver health monitoring, human factors, and affective computing. His current work is supported by Federal Highway Administration (FHWA), National Science Foundation (NSF) National Highway Traffic Safety Administration (NHTSA), National Academies of Sciences Engineering and Medicine, National Surface Transportation Safety Center for Excellence (NSTSCE), Safety through Disruption (Safe-D) University Transportation Center (UTC), and numerous proprietary companies. Dr. Sarkar has more than 30 technical publications, proceedings, and book chapters. He has software development experience in both academia and industry for 12 years. Dr. Abbott is a Professor at Virginia Tech, where he is a faculty member in the Bradley Department of Electrical and Computer Engineering. His primary research interests involve Computer Vision, Machine Learning, and Biometrics. In the area of biometrics, he has led efforts involving fingerprint analysis, authentication from cardiovascular signals, and facial expression recognition. His work is currently supported by the National Science Foundation (NSF) and by the Federal Highway Administration (FHWA). Dr. Abbott has authored or coauthored more than 160 technical publications and has been awarded one U.S. patent. He teaches graduate courses in the area of Computer Vision, and undergraduate courses in software development, microcontroller systems, and Artificial Intelligence.

Human Factors and Cybersecurity: 10 Things you need to know to protect yourself and your company from cyber attacks

Every day the number of ransomware, identity thefts, credit card fraud, email message hacking, etc. grows and costs individuals and institutions both short-term and long-term loss. The press is full of reports of data center breaches that result in loss of intellectual property, trade secrets, and/or customer data and affect the company’s reputation. Successful cyber protection at the individual level or enterprise level is not possible without having well-trained people who are aware of security risks and are knowledgeable enough to make sound judgments when they are confronted with cyber-attacks such as phishing or fraudulent phone calls. The active involvement of employees and their awareness are paramount to a company’s security compliance. The objective of this tutorial is to cover 10 important areas of cybersecurity risks and teach attendees about protective measures. After the completion of this training, session participants will learn practical ways of dealing with cyber-attacks, and a list of actions to take to protect themselves at both the individual and the company level.

About the Speaker(s) Dr. Abbas Moallem is the executive director of UX Experts, LLC, a UX/UI design and cyber security consultancy in Cupertino, California, and an adjunct professor at San Jose State University, where he teaches Human computer Interaction, Human Factors, Data Visualization and Cyber Security. Abbas is the editor of the Human-Computer Interaction and Cyber Security Handbook published in 2018 and Cybersecurity Awareness among College Students and Faculty published in 2019 by CRC Press. His latest books are “Understanding Cybersecurity Technologies” and “Smart and Intelligent System: The Human Elements in Artificial Intelligence, Robotics, and Cybersecurity” published in 2021 by CRC Press. Dr. Moallem has over 20 years of experience in the fields of human factors, ergonomics, human computer interaction (HCI) and usability. He has also served as a senior engineering product manager and usability expert at NETGEAR, a UI Architect at PeopleSoft, Oracle Corporation, Tumbleweed, and Axway for over 11 years. He has consulted in a variety of industries in Europe, Canada, and the US

This tutorial will provide all the basics and essential concepts of Python and Data Science.  It is the process of deriving knowledge and insights from a huge and diverse set of data. It extracts the data from the source and applying data visualization techniques. for this purpose, Data science needs a very versatile yet flexible language for highly complex mathematical processing. Python is most suited for general computing as well as scientific computing. This tutorial will increase awareness and understanding of key issues related to the tutorial topic. Further, they will learn;

•       Concepts and issues related to Data Science.
•       How these concepts relate to Python.
•       Principles and techniques that are useful in Data Science and Python libraries.

Content and Benefits:
This tutorial is suitable for non-programmers as well as programmers who don't know Python. It will help how to do data analyses using the Python language and Pandas The exercises will include the design and evaluation

This tutorial will discuss how both Data Science and Python are interrelated and essential for Data visualization.
This tutorial will include both presentations and practical work.
The tutorial will also provide guidelines for future research

Topics Covered:
•       Basic steps in data science
•       Python: basics, variables, data types, objects, loops, conditions
•       Python: functions, string functions, lists, tuples, dictionaries, sets
•       Exploratory Data analysis by using Jupyter Notebooks, Numpy, pandas etc.

You won't become a full-fledged Python programmer, but you'll learn enough to continue your own Python education afterwards.

About the Speaker(s) Dr.Javed Anjum Sheikh, Associate Profesor/Director CS&IT in the University of Minhaj University Lahore – before that, I was the Assistant Professor/Campus Director/Associate Dean of the University of Lahore, Gujrat Campus and was the Assistant Professor (Associate Director) of the faculty of Computing and IT.

Neuroscience is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales and the techniques used by neuroscientists have expanded enormously, from molecular and cellular studies of individual neurons to imaging of sensory, motor and cognitive tasks in the brain.

About the Speaker(s) Adrian Curtin is a researcher with Shanghai Jiao Tong University and Drexel University. His research background focuses on the neuroergonomic application of neuroimaging, particularly in mental health, neurostimulation, and in analysis method development.

Heuristic evaluation is a well-known technique that evaluates a design based on its compliance with recognized usability principles. Heuristic evaluations have the benefit of being very efficient and focused (for example, an accessibility evaluation is focused on accessibility problems.) However, most practitioners prefer user-based testing because they have more confidence in the results. Ideally, teams should use both, as effective heuristic evaluations make user-based testing more productive by focusing on hard-to-find problems.
But a heuristic evaluation is only as good as the set of heuristics used, and the most popular heuristics are well past their “best by” dates. Arguably the most popular usability heuristics were devised by Jakob Nielsen and Rolf Molich—in 1990! Considering how rapidly UI design has changed, the relevance and practical value of even 5-year-old heuristics should be suspect. Less popular heuristics are often vague and hard to apply meaningfully (example: “…check whether the user has enough control…” What does that even mean?)

This tutorial will consist of two parts. In Part 1, we will quickly review the most well-known usability heuristics, plus a summary of the top design principles recommended by the most popular platforms (iOS, Android, Windows, and Mac). The class will break into three teams (representing desktop, web, and mobile), and devise their own usability heuristics using a structured process. The focus of the results will be on their practical value. At the end of this part, each team will present their results to the class.
For Part 2, we will review the ground rules for effective heuristic evaluations, then as apply our newly created heuristics to desktop, web, and mobile designs (at least one for each platform). The tutorial will end with a discussion about the effectiveness of the evaluations and how to further improve the process.

About the Speaker(s) Everett McKay is Principal of UX Design Edge and a UX design consultant and trainer with global clientele that includes Europe, Asia, South America, Australia, and Africa. Everett's specialty is finding practical, intuitive, simple, highly usable solutions quickly for web, mobile, and desktop applications. Everett has over 30 years' experience in user interface design—and even more programming UIs. (He loves React!)

Everett is author of "Intuitive Design: Eight Steps to an Intuitive UI", the definitive guide to designing intuitive interactions, and "UI Is Communication: How to Design Intuitive, User Centered Interfaces by Focusing on Effective Communication", a groundbreaking approach to UI design using human communication-based principles and techniques. While at Microsoft, Everett wrote the Windows UX Guidelines for Windows 7 and Windows Vista. Everett holds a master's degree in computer science from MIT.

Neuroscience (or neurobiology) is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales and the techniques used by neuroscientists have expanded enormously, from molecular and cellular studies of individual neurons to imaging of sensory, motor and cognitive tasks in the brain.

About the Speaker(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s): Dr. Adrian Curtin, Drexel University

Neuroscience (or neurobiology) is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales and the techniques used by neuroscientists have expanded enormously, from molecular and cellular studies of individual neurons to imaging of sensory, motor and cognitive tasks in the brain.

About the Speaker(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s)(s): TBD