Hi! As you might have guessed, I'm Daniel Genkins and this is my personal website.

I'm currently a postdoc at Vanderbilt University, where I'm also the Executive Director of the Slave Societies Digital Archive (SSDA). I did my graduate work at Vanderbilt as well, studying the history of the early modern Atlantic World and completing my Ph.D. in 2018. Toward the end of my graduate career I started working on the SSDA project, and my interest in enhancing and expanding the archive quickly grew into a full pivot toward digital humanities and data science. I spent the 2018 - 2019 academic year as a CLIR/DLF Postdoctoral Fellow in Data Curation for Latin American and Caribbean Studies at Brown University's John Carter Brown Library before returning to Nashville in fall 2019 to become the Executive Director of SSDA.

These days I have my hands in any and all aspects of SSDA, which has grown over the past 15 years from a handful of one-off projects into a massive archive containing more than 700,000 digitized images of early modern records detailing the lives of people of African descent around the Atlantic. My early work revolved around programmatically reorganizing the archival data, developing a workflow to build searchable metadata for the entirety of the collection, and relaunching the archive using a modern content management system. Over the past year, we've moved all archival data to S3 and are in the final stages of reworking the archive to use cloud storage as a filesystem. You can learn more about my work up to now in a recent article in The Conversation.

In the months ahead, we'll be launching a revamped archival website that will include a portal allowing users to access more detailed data about people, places, and events extracted from our records using the Spatial Historian software suite. In partnership with Vanderbilt's Data Science Institute, we've begun developing machine learning-aided solutions to automate the extraction of this data from the collection at scale. Moving forward, I'm particularly excited about exploring how ML can help to unlock the wealth of information contained within collections like ours and make them more accessible and useful for researchers as well as the interested public!