I am a researcher, developer, and designer. My work centers on the intersection of technology, design, and critical software development. I am researcher at Duke University in Computational Media Arts and Cultures, and I teach classes and workshops in interaction design, machine learning, interface design and internet-of-things. My research areas include artificial intelligence, machine learning, computer vision and race, society and information.  I hold an Bachelors of Science from Cornell University and a Masters in New Media from Penn State University.

Education

Masters, New Media, Penn State University, University Park PA - May 2015

Bachelors of Science, Cornell University, Ithaca NY - May 2011

Teaching:

Co-Instructor - EGR 190-02/ EGR 590-02 - Machine Learning Methods and Practice - Duke University - Fall 2019

Data science, machine learning, and artificial intelligence are making inroads into many aspects of society, with numerous impacts across disparate disciplines with often surprising applications. The ability to understand the capabilities and limitations of these technologies and use them in an appropriate manner is already an important skill and is projected to be increasingly important in the future. The goal of this course is to provide an applied introduction to current techniques in machine learning and how they can be used to  make sense of large amounts of data, while allowing students to focus on how machine learning is impacting their discipline of study.

Instructor - ISS 294L - Interactive Graphics - Duke University - Spring, 2018

http://dukeinteractivegraphics.club/  

Introduction to interactive graphics programming for artists. Explores object oriented programming via the Processing programming environment as well as historical and theoretical appreciation of interactivity and computer graphics as artistic media. Combines discussions of key concepts from the readings with hands-on Processing projects and critiques. No previous programming experience.

Co-Instructor - CMAC 564S - Physical Computing - Duke University - Fall, 2018

https://cmac-duke.github.io/physical-computing/

Seminar in physical computing, creative coding, and the emerging artistic possibilities of the Internet of Things. Emphasis on the medial physicality of computation, and exploration of interfaces to the computational that depart from the keyboard, mouse, and screen. Discussion of the social implications of “smart” objects. Hands-on development of individual and group projects using Arduino, an extension of C/C++, internet-enabled microprocessors, and an array of analog and digital sensors and actuators. Topics also include networking, communication protocols, circuit design, and physical prototyping

Co-Instructor - MFAEDA 713-0 Computational Media - Duke University - Fall, 2018

http://compmedia.mfaeda2019.org/

This course will explore the intersection of computational interface design and documentary practice. Through physical computing workshops, collaborative projects, student presentations, associative drawing exercises, and group brainstorming sessions, the class will develop novel tools used to generate unforeseen forms of documentary fieldwork and design unique computational interfaces that facilitate experiential dialogues between users and emergent forms of research. Workshops include Wiimote hacking, natural language processing, gesture recognition, spherical panoramic photography, photogrammetry, spatial audio design, and 3D modeling/printing.

Workshops:

  • Text Generation with Transformer Networks - Duke University, Fall 2019
  • Creative Storytelling with Machine Learning - Duke University, Fall 2019
  • Deepfakes: Commodification, Consequences, And Countermeasures - Open Data Science Conference West, Fall 2019
  • AI for Visual Art - Duke University, Fall 2019
  • Creativity and Deep Learning with GANs- Duke University, Spring 2019
  • Creative Coding in P5js- Duke University, Fall 2018
  • Natural Language Processing for the Humanities with Spacy and Gensim- Co-Lab Duke University, Spring 2018.
  • Creativity and AI with ML5.js- NC State University, Spring 2018.
  • Data Visualization in Rails- Duke University, Spring 2017.
  • Data Analysis for the Humanities- Duke University, Fall 2017.
  • Creative Coding in Processing - Duke University, Spring 2017
  • Creative Coding p5.js - Duke University, Fall 2017