Cristian Felix

Cristian Felix is a Ph.D. Candidate in the Computer Science and Engineering department at NYU Tandon School of Engineering. He has assisted in courses on visualization for the last 4 years. Before his Ph.D., Felix worked in the industry for 12 years working with networks, databases and software development. Felix research focuses on the creation of visual systems that allow users to explore large text collections through interactive visualizations. He has publications in top visualization conferences and also was the winner of the VisualizeChange challenge promoted by United Nations.

Sort options

Information Visualization: Programming with D3.js (Coursera)

May 13th 2024
Information Visualization: Programming with D3.js (Coursera)
Course Auditing
Categories
Effort
Languages
In this course you will learn how to use D3.js to create powerful visualizations for web. Learning D3.js will enable you to create many different types of visualization and to visualize many different data types. It will give you the freedom to create something as simple as a bar [...]

Information Visualization: Foundations (Coursera)

The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization and to design and develop advanced applications for visual data analysis. This course aims at introducing fundamental knowledge for information visualization. The main goal is to [...]

Information Visualization: Applied Perception (Coursera)

This module aims at introducing fundamental concepts of visual perception applied to information visualization. These concepts help the student ideate and evaluate visualization designs in terms of how well they leverage the capabilities of the human perceptual machinery.

Information Visualization: Advanced Techniques (Coursera)

This course aims to introduce learners to advanced visualization techniques beyond the basic charts covered in Information Visualization: Fundamentals. These techniques are organized around data types to cover advance methods for: temporal and spatial data, networks and trees and textual data. In this module we also teach learners how [...]