John Alexis Guerra Gomez
Assistant Teaching Professor
John Alexis Guerra Gomez is an assistant teaching professor in the Khoury College of Computer Sciences at Northeastern University. Based in San Francisco, he specializes in extracting insights from data through interactive information visualization and data science.
His research to date has focused on visual analytics, accessibility, big data, human-computer interaction, and web development. John Alexis holds a Ph.D in Computer Science from the University of Maryland, an MS in Mathematical Science and a BS in Computer Science. Both of these latter degrees were gained at the Universidad Tecnológica de Pereira in Colombia.
John Alexis has a significant amount of learned knowledge in computational science, including but not limited to 10 years as researcher in information visualization, 17 years as a full stack engineer, and 11 years of teaching at the university level. Prior to joining NU, he held faculty roles at UC Berkeley of Information and Uniandes Colombia. He also has non-academic experience to call on with PARC (a Xerox company) and Yahoo Labs both part of his post-doctorate journey.
He has 16 years of public speaking under his belt, and has spoken at events such as Openvis2017, TEDx, Singularity University Summit Colombia (2018), Ruta de la Ciencia Colombia (2016), CX Summit Colombia, and Halliburton’s STEPS Distinguished Lecture series on Big Data in Exploration and Production (2018). John Alexis has authored more than 30 research publications, all of which have been presented at industry conferences and events. Additionally, he was part of the program committee at IEEE VIS 2021 and 2022, and a reviewer for Computer-Human Interaction (CHI) papers, IEEE VIS and EuroVis conferences, among others.
An established entrepreneur, John Alexis has founded several companies. These include co-founding Columbia-based DUTO, KebSolutions, Tweetometro.co, and BTactile. This private sector activity has seen him receive more than 10 international entrepreneurship awards to date.