I'm a research data scientist at RTI International where I currently build imaging software using computer vision techniques. I have experience in applied machine learning research and development, working largely in healthcare and education. I enjoy making mixed and multimedia art.
I'm interested in machine (and biological) learning, realtime multi-modal sensor networks, image and signal processing, generative systems, and human-computer interaction.
For more information see below or my professional CV.
Applied machine learning research
Kim A., Miano T., Chew R., Eggers M., Nonnemaker J.. Classification of Twitter Users Who Tweet About E-Cigarettes. JMIR Public Health Surveillance 2017;3(3):e63. DOI: 10.2196/publichealth.8060
Charles, M., Miano, T. N., Zhang, X., Barnes, L. E., & Lobo, J. M. (2015). Monitoring quality indicators for screening colonoscopies. In Systems and Information Engineering Design Symposium (SIEDS), 171–175.
Software and app development
Artificial intelligence 2017
This was presented to about 150 people at RTI International. My goal was to provide a high-level introduction to artificial intelligence. Some of the questions addressed:
- What are factors driving the revitalization of "AI"?
- What is AI?
- What is deep learning?
- When is machine learning appropriate?
Ethics in data science and artificial intelligence 2015
This was an open-forum where we discussed ethical dilemmas in data science and machine learning. This was presented to about 30 people at RTI International. Some of the topics addressed:
- Data vs ethics
- Design thinking in algorithms
- Bias in data, consent, and privacy
- Machine learning and artificial intelligence
Case studies in design thinking, visualization, and communication 2017
This was held for the 2017 data visualization class in the University of Virginia School of Architecture.
Workshop in building interactive data visualizations for the web 2016
This was held for the 2016 data visualization class in the University of Virginia School of Architecture. We discussed the following:
- Foundations: use of physical media, importance of play, color theory, and perception of space
- Data: ethics, interpretability, vision, and storytelling
- Coding: web development overview and coding exercise
Getting started with GPU-driven deep learning 2016
This is a three-part tutorial targeted at folks interested in getting started with deep learning but not quite sure where to begin.
- How to build a GPU deep learning machine
- Setting up Ubuntu and Docker for deep learning
- Using deep learning with style transfer
Immersive art in virtual reality 2016
This was part of the 2016 Datapalooza hosted by the Data Science Institute at the University of Virginia. I set up an HTC Vive and introduced dozens of people to Google Tilt Brush, giving participants an opportunity to experience 3D painting (many for the first time), with a live feed of their work being displayed on a monitor for all to see.
On nature, form, and aesthetics
Studies using physical and computational media. Explore by clicking a thumbnail below!
It would obviously take some getting accustomed, I think, if it should be a matter of taking into one’s eyes that which is up there outside the cave, in the light of the sun.