Michael McQuaid Headshot

Michael McQuaid

Lecturer
School of Information
Golisano College of Computing and Information Sciences

734-274-1547
Office Hours
1200--1400 Monday, Wednesday
Office Location

Michael McQuaid

Lecturer
School of Information
Golisano College of Computing and Information Sciences

Education

BFA, New York University; MBA, MS, University of Wisconsin; Ph.D., University of Arizona

734-274-1547

Personal Links

Currently Teaching

ISTE-780
3 Credits
Rapidly expanding collections of data from all areas of society are becoming available in digital form. Computer-based methods are available to facilitate discovering new information and knowledge that is embedded in these collections of data. This course provides students with an introduction to the use of these data analytic methods, with a focus on statistical learning models, within the context of the data-driven knowledge discovery process. Topics include motivations for data-driven discovery, sources of discoverable knowledge (e.g., data, text, the web, maps), data selection and retrieval, data transformation, computer-based methods for data-driven discovery, and interpretation of results. Emphasis is placed on the application of knowledge discovery methods to specific domains.
ISTE-432
3 Credits
Database applications have aspects that need to be considered when designing and developing larger-scale systems. In this course students will explore topics such as concurrent processing, scalability, performance, and security within the context of developing larger-scale data/base information processing systems. Programming projects are required.
ISTE-782
3 Credits
This course introduces students to Visual Analytics, or the science of analytical reasoning facilitated by interactive visual interfaces. Course lectures, reading assignments, and practical lab experiences will cover a mix of theoretical and technical Visual Analytics topics. Topics include analytical reasoning, human cognition and perception of visual information, visual representation and interaction technologies, data representation and transformation, production, presentation, and dissemination of analytic process results, and Visual Analytic case studies and applications. Furthermore, students will learn relevant Visual Analytics research trends such as Space, Time, and Multivariate Analytics and Extreme Scale Visual Analytics.
HCIN-620
3 Credits
Designing meaningful relationships among people and the products they use is both an art and a science. This course will focus on the unique design practice of: representing and organizing information in such a way as to facilitate perception and understanding (information architecture); and, specifying the appropriate mechanisms for accessing and manipulating task information (interaction design). This course will also explore the various design patterns (design solutions to particular problems) that are appropriate for the HCI professional. Students will need prior knowledge of an interface prototyping tool.
ISTE-262
3 Credits
This course explores how the fields of psychology, digital design, and computing converge in the design, development, and evaluation of new technologies that people find effective and enjoyable to use. Students will investigate the field of human-computer interaction (HCI), with a focus on how users' various sensory, motor, and cognitive abilities are essential to their successful use of technology. Students will be exposed to modern research methods and paradigms in field of human-computer interaction, including predictive modeling, heuristic evaluation, interpretive methods, and experimental user testing. Students will learn key design principles and guidelines and apply them to analyze existing designs and conduct a design process that is centered on human users of technology.
ISTE-264
3 Credits
This course will explore how modern human centered computing design and evaluation methodologies can be effectively used to create high-quality and usable technologies for a variety of users. Students will learn how an initial design can be evaluated and improved through the use of prototyping and user evaluations. Students will investigate a variety of high- and low-fidelity prototyping techniques, plan an iterative design process for an application, conduct an evaluation of a prototype, and analyze the results of user testing to drive a design process. Programming is required.
ISTE-599
1 - 3 Credits
Independent study offers a student an opportunity to explore, in greater depth, a topic previously introduced in a prior course or a topic of special interest. A faculty member supervises the student's work. A student and faculty member will collaboratively develop an independent study proposal that describes the student's plan of work, expected deliverables, evaluation criteria, and number of credits that will be earned. Requires department consent.
HCIN-600
3 Credits
This course provides students with an introduction to the practical application of various research methods that can be used in human computer interaction. The course provides an overview of the research process and the literature review, and provides experience with qualitative, survey, and experimental research methods. Students will study existing research and design and conduct studies. Students will need to have taken a statistics course before registering for this class.

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Published Conference Proceedings
Mahapatra, Chandan, et al. "Barriers to End-User Designers of Augmented Fabrication." Proceedings of the CHI Conference on Human Factors in Computing Systems Proceedings (CHI 2019), May 4-9,2019, Glasgow, Scotland. Ed. Stephen Brewster. New York, NY: ACM Press, Web.