Eli T. Brown

ebrown @ cs tufts edu

PhD Candidate @ Tufts University
Department of Computer Science

See my C.V.


I have just finished my Ph.D.! I was a student of Remco Chang at VALT (the Visual Analytics Laboratory at Tufts), and I defended successfully on July 20th, 2015, and now the paperwork is in and I'm done :). I'm also proud to announce that I've accepted a position: Assistant Professor at DePaul University! I have deferred my start until January 2016 because my wife and I just had our first child. I have a number of things on my plate already, but if you are interested in consulting/contracting, get in touch.

Background - in 2005 I received my B.A. from Cornell University in Computer Science and Mathematics. I worked for 5 years in industry as a software engineer before starting graduate school. For 2 years I worked on government research contracts in software security at GrammaTech in Ithaca, NY. Following that I moved to Cambridge, MA where I worked for Xcitex for 3 years on software for motion analysis in high-speed video, and developed a product line based on data collection and synchronization with high-speed video.


My work is at the intersection of visualization and machine learning. I'm interested in using interactive visualization to help users work with machine learners, and conversely using machine learning to improve visualizations of complex data. More specifically, I've been working with high-dimensional data projections and semi-supervised machine learning techniques. My published work has so-far focused on learning distance functions with domain expert input, but my further projects are focused on the more general problem of how learning models from human interactions with visualizations such that we improve analytic results with the data and learn about the users at the same time. Starting with my internship at Microsoft Research, I'm increasingly interested in the related field of Interactive Machine Learning, which uses machine learning algorithms with input based on user interactions for a wide variety of purposes.


Wang, Helen J., Moshchuk, A., Gamon, M., Haraty, M., Iqbal, S, Brown, Eli T., et al. The Activity Platform. 15th Workshop on Hot Topics in Operating Systems (HotOS XV). USENIX Association.

Eli T. Brown, Alvitta Ottley, Helen Zhao, Quan Lin, Richard Souvenir, Alex Endert, Remco Chang. Finding Waldo: Learning about Users from their Interactions. Transactions on Visualization and Computer Graphics (TVCG), 2014. (Presented at VAST 2014)

Eli T. Brown, Remco Chang. EigenSense: Saving User Effort with Active Metric Learning. KDD 2014 Workshop on Interactive Data Exploration and Analytics (IDEA).

Eli T. Brown, Jingjing Liu, Carla E. Brodley, Remco Chang. Dis-Function: Learning Distance Functions Interactively. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), 2012.

Daniel Afergan, Evan M. Peck, Erin T. Solovey, Andrew Jenkins, Samuel W. Hincks, Eli T. Brown, Remco Chang, Robert J.K. Jacob. Dynamic Difficulty Using Brain Metrics of Workload. CHI 2014, with Honorable Mention for Best Paper.

Jingjing Liu, Eli T. Brown, Remco Chang. Find Distance Function, Hide Model Inference. Poster at IEEE Conference on Visual Analytics Science and Technology, 2011.

Eli T. Brown. Presentation: Human in the Loop: Iterative, Interactive Visual Model Refinement for a workshop at the American Statistical Association's Joint Statistical Meetings


Summer 2014: Microsoft Research, Mentor: Helen Wang
Summer 2013: Visual Analytics group at Pacific Northwest National Lab, Mentor: Alex Endert


Our paper Afergan et al. from CHI 2014 received Best Paper Honorable Mention.

I was honored to take part in the VIS 2013 Doctoral Colloquium, where I presented my work on leveraging user interaction with analytic systems to learn analytic results as well as learn about users.

In June of 2014 I finished the first phase of the GIFT Program (Graduate Institute for Teaching ), a fellowship for doctoral students to become great teachers.

Since 2013, it has been my honor to have been chosen and to serve as the Graduate Student Representative on the Curriculum Task Force of the Engineering School at Tufts University.


2014 November: Tufts Data Science Club, "Experience in Visual Analytics Research", Medford, MA. Invited presentation.
2014 October: BostonVIS Labs, "Finding Waldo: Learning about Users from their Interactions", Medford, MA. Invited presentation.
2014 September: IBM Human Computer Decision-Making Workshop, "Learning about Data and Users from Interactions", Cambridge, MA. Invited workshop presentation.
2014 September: Microsoft Research, "Internship Research Overview", Redmond, WA. Internship talk.
2014 June: Graduate Institute for Teaching, "Visualization", Medford, MA. Teaching sample.
2014 May: Tufts University Machine Learning Course, "Semisupervised and Metric Learning", Medford, MA. Guest Lecture.
2013 August: Pacific Northwest National Lab, "Internship Research Overview", Richland, WA. Internship talk.
2013 July: American Statistical Association's Joint Statistical Meetings, "Human In the Loop: Iterative, Interactive Visual Model Refinement", Montreal, QC. Invited workshop talk.
2012 December: Virginia Polytechnic Institute (Virginia Tech), "Metric Learning with Experts for High-Dimensional Data: Progress, Problems and Possibilities", Blacksburg, VA. Invited talk.
2012 October: "Qualifying Exam Research Talk", Tufts University, October 2012.

Teaching Assistant Experience:

In June of 2014 I finished the first phase of the GIFT Program (Graduate Institute for Teaching ), a fellowship for doctoral students that trains us to be great teachers. For phase two of this program, I will be co-teaching Visualization with Remco Chang in the Fall.

Graduate Coursework: