Digital Humanities Research
In 2013 I started publishing research on using technology to improve humanities research and study. Primarily I’ve been interested in applying computer vision techniques to improve art history study.
At the moment, beyond my work on Ukiyo-e.org, my primary area of research is in using computer vision techniques to improve art history photo archives, especially those specializing in Italian art. More information on that ongoing project can be found here:
Press, Papers, and Talks
- A beacon of digitised art: Pharos consortium builds massive digital database (The Art Newspaper, 2017)
- Millions of Objects at 14 Art Institutions to Be Digitized for Online Database (Hyperallergic, 2017)
- All-Star Museums Team Up to Digitize 25 Million Images, Putting Art History Online (artnet news, 2017)
- ‘Photo Archives Are Sleeping Beauties.’ Pharos Is Their Prince. (NYTimes, 2017)
- “An Ukiyo-e Database for Everyone” (Impressions, The Journal of the Japanese Art Society of America, Number 38, 2017)
- Computer Vision Analysis of Japanese Prints, DPLAFest 2016, Washington D.C.
- Keynote talk, “Paper: The Place of Discovery” symposium, University Wisconsin-Madison 2015
- Using Computer Vision to Improve Image Metadata, Rochester Institute of Technology 2015
- Computer Vision technology and art history (presented at CAA ThatCamp 2015)
- The Floating World at Your Finger Tips: Using the Ukiyo-e.org Search Engine (Japanese Art Society of America, 2014)
- IDPAC 2014 Annual Meeting
- Princeton: The Digital World of Art History: Standards and Their Application
- NYARC 2014 Annual Meeting
- Using Computer Vision to Increase the Research Potential of Photo Archives (Journal of Digital Humanities, 2014)
- Using Computer Vision to Improve Image Metadata (presented at DH 2014)
- Using Computer Vision to Increase the Research Potential of Photo Archives (Self-published, 2013)
- Aggregating and Analyzing Digitized Japanese Woodblock Prints (2013) (Video) (JADH 2013)
Data Mining Research
The majority of my research was into data mining instant messaging networks (Project: IMSCAN).