Lecture (LEC)

• Above class open to HCI Design masters only
• Above class meets with INFO-I 400
• TOPIC: VIZ DATA WITH TABLEAU

Topic: Viz data with tableau

Lecture (LEC)

• TOPIC: PROTOTYPING WITH ARDUINO TOOLS
• Above class meets with INFO-I 341

Topic: Prototyping with arduino tools

Lecture (LEC)

• TOPIC: PROTOTYPING WITH ARDUINO TOOLS
• Above class meets with INFO-I 341

Topic: Prototyping with arduino tools

Lecture (LEC)

• TOPIC: ADVANCED INFORMATION ETHICS
• Above class meets with INFO-I 400

Topic: Advanced information ethics

Lecture (LEC)

• TOPIC: BUILDING VIRTUAL WORLDS
• Above class meets with INFO-I 443

Topic: Building virtual worlds

Lecture (LEC)

• TOPIC:INTRO TO VIRTUAL REALITY
• Above class meets for the thirteen week session
• Above class meets with INFO-I 304

Topic: Intro to virtual reality

Lecture (LEC)

• TOPIC:ARTIFICIAL LIFE IN VR
• Above class meets with INFO-I 444
• Above class meets for the thirteen week session

Topic: Artificial life in vr

Lecture (LEC)

• TOPIC:SMART CITIES
• Above class meets for the thirteen week session
• Above class meets with INFO-I 400

Topic: Smart cities

Lecture (LEC)

• Above class meets for the thirteen week session
• Above class meets with INFO-I 400 and SGIS-S 300
• TOPIC: Innovation for Impact

Topic: Innovation for impact

Lecture (LEC)

• TOPIC:VISUAL DESIGN
• Above class requires permission of Department
• Above class meets for the thirteen week session
• Above class meets with INFO-I 363
• Above class for HCI MS students only

Topic: Visual design

Visual design for the web is the process of creating the aesthetics and visual elements of a website or web application. It involves a variety of design principles such as layout, imagery, colors, typography, and user interface (UI) elements to construct a user-friendly and visually engaging online experience. Visual design is important because it directly affects how users perceive and interact with a website. Effective visual design enhancing user experience, usability, and accessibility. Designers need to consider factors like user behavior, cognitive psychology, and the goals of the website to create a design that not only looks good but also effectively communicates the intended message and provides a positive user experience. In this project-based introduction course, we will explore the principles of visual design through a series of lectures, readings, in-class activities, creative projects, and Adobe Illustrator and Photoshop training. Students will learn about color theory, grid systems, logo design, perception, balance, line, repetition, composition, branding and Gestalt principles, and apply these principles to screen-based user interfaces. Students will learn how to evaluate visual design, how to take better photographs, how to select content, how to edit and manipulate images, how to create basic geometric illustrations, and original digital designs. In the final project, students apply these collective skills and concepts to create a brand and web interface design. Learning Outcomes After this course, you will be able to: - Identify and apply visual components and design principles - Analyze a photograph based on both quality and appropriateness - Optimize and crop a photograph using Photoshop - Make informed photographic decisions to compose better images - Create illustrations within Adobe Illustrator using the pen tool and tracing techniques - Apply color theory and typographic principles to digital designs - Compose a visual design layout using a grid system or modular components - Sketch designs for interfaces, paying attention to the overall visual design and interface usability

Lecture (LEC)

• TOPIC: 3D DIGITIZATION
• Above class meets with INFO-I 400

Topic: 3d digitization

In today's data-driven world, the process of 3D digitization (3DD) is rapidly gaining prominence as it offers invaluable spatial insights. This course explores the fundamental principles and practical aspects of various range-sensing technologies available today. It covers both active methods, such as laser scanning, and passive approaches relying on image-based techniques like photogrammetry. Moreover, this course provides an in-depth exploration of the data processing techniques required to transform spatial data into accurate 3D computer models of physical objects. Students will gain hands-on experience by working on their own 3D capture projects under the instructor's guidance. 3D digitization has found applications in diverse fields, including Engineering, Architecture, Medicine, Industrial Design, Forensics, Library Science, Robotics, and Cultural Heritage documentation. This course is designed to be accessible to students with varying backgrounds, making it an excellent opportunity to harness the power of spatial information in a wide range of professional disciplines. SW tools: MATLAB, FARO Scene; Agisoft Metashape; Meshmixer; Meshlab.

Lecture (LEC)

• TOPIC: HCI/d Studio Practice
• Open to HCI MS students only

Topic: Hci/d studio practice

Lecture (LEC)

• Above class meets for the thirteen week session
• Above class meets with INFO-I 304
• TOPIC:INTRO TO VIRTUAL REALITY

Topic: Intro to virtual reality

Lecture (LEC)

• TOPIC: Innovation for Impact II
• Above class meets for the thirteen week session
• Above class requires instructor permission
• Above class meets with INFO-I 400
• Above class location and meeting times arranged

Topic: Innovation for impact ii

Lecture (LEC)

• TOPIC: Curiosity

The course will focus on curiosity research, from a psychological perspective, computational models and applications in machine learning and robotics. During the course computational tools will be taught to help the students understand, design and implement computational models of curiosity: reinforcement learning, Markov decision processes, Bayesian inference, information theory and artificial neural networks. The course will also include applications of curiosity models to human behavior, data science and curious robots. Knowledge of Python is required.

Lecture (LEC)

• TOPIC: Fundamentals and Applications of Large Language Models

Topic: Fund & app of larg lang models

Lecture (LEC)

• TOPIC: Data Visualization

Topic: Data visualization

Data visualization plays a pivotal role in understanding information, from news articles to cutting-edge scientific research, and is employed across diverse settings, from home offices to the world's largest corporations. As an integral component of data analysis, data visualization has become a crucial skill for all knowledge workers. This introductory course delves into the core concepts of statistical data analysis and visualization. You will explore the foundations of data visualization, covering topics such as perception, integrity, design principles, statistical methods, data classifications, and various visualization techniques. Through hands-on exercises utilizing the Python stack, students will develop practical skills in data processing and visualization. You can check 2024 Fall course website: https://haewoon.github.io/dviz-course-2024-fall/

Lecture (LEC)

• Above class meets for the thirteen week session
• Above class meets with a section of INFO-I 304
• TOPIC: Introduction to Virtual Reality

Topic: Introduction virtual reality

Lecture (LEC)

• TOPIC: Data Visualization

Topic: Data visualization

Welcome to our exciting journey into the world of Data Visualization! This course is designed to provide you with a solid understanding of visualization fundamentals, emphasizing practical skills and real-world applications through Python and Javascript. Visualizing data is an essential skill for researchers, data scientists, analysts, journalists, and professionals in various fields dealing with information. It is an important tool for understanding complex datasets and making data-driven decisions. Also, it can play an important role in troubleshooting issues within complex data analysis pipelines or AI models. Furthermore, data visualization serves as a powerful medium for communicating data-driven insights and narratives with colleagues or broader audiences. Objectives By the end of this course, you are expected to be able to: - Prepare and manipulate basic data types, such as numerical, categorical, and textual data. - Explain and summarize data using descriptive statistics. - Analyze data using exploratory visualization techniques. - Critically analyze and improve visualizations based on principles such as human perception, design, visualization techniques, technology, and ethics. - Understand how visualizations can be misleading or misrepresent data. - Use ethical considerations when creating and deploying visualizations, such as fairness, accuracy, transparency, accessibility and diversity. - Use modern libraries and tools for creating interactive visualizations. - Integrate visualization into data analysis and machine learning pipelines. - Prepare narrative visualizations to communicate data-driven insights and stories. - Create and deploy interactive visualizations to the web. - You will showcase your learned skills by undertaking a course project, in which you will develop a visualization to reveal insights from real-world datasets. This project will require detailed documentation of each step involved in its development, from initial concept to final execution. Prerequisites In this course, we will primarily use Python for data analysis and visualization tasks. Thus, you are required to have a good understanding of algorithms and practical experience with Python. We also expect you to have some level of familiarity with web technologies (HTML, CSS, and JavaScript), which will be essential for creating and deploying interactive visualizations. You are encouraged to also have a basic understanding of statistics and probability, as well as notions of 2D geometry and linear algebra. For self-assessment, please, visit the following link: http://bit.ly/dvizselfassess (created by YY Ahn). Contact the instructor if you are uncertain about your background. More information: https://github.com/filipinascimento/dataviz

Lecture (LEC)

• Above class meets for the thirteen week session
• TOPIC: VISUAL DESIGN FOR THE WEB
• Above section meets with INFO-I 363

Topic: Visual design

Lecture (LEC)

• TOPIC: Health and AI: Human-Centered Design Perspectives