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Hey! I'm Matt

I'm a PhD Candidate at the University of North Carolina at Chapel Hill

Reach out here: mhh (at) cs (dot) unc (dot) edu

What Am I Doing These Days?

I study Computer Science at UNC, where I build interactive visualization tools that help people study complex datasets.


These tools are often augmented with human-in-the-loop ML algorithms and always developed following user-centered design principles.


I'm fortunate to be advised by Dr. Danielle Szafir, and to have held internships at NASA JPL as well as Tableau Research.

I've Written Some Papers About Human-Computer Interaction


  • Cieran: Designing Sequential Colormaps via In-Situ Active Preference Learning

    Summary

    We introduce Cieran, a tool that allows any data analyst to rapidly find quality colormaps while designing charts within Jupyter Notebooks. Our system employs an active preference learning paradigm to rank expert-designed colormaps and create new ones from pairwise comparisons, allowing analysts who are novices in color design to tailor colormaps to their data context.

  • Conversational AI Threads for Visualizing Multidimensional Datasets

    Summary

    Generative Large Language Models (LLMs) show potential in data analysis, yet their full capabilities remain uncharted. Our work explores the capabilities of LLMs for creating and refining visualizations via conversational interfaces.

  • Scholastic: Graphical Human-AI Collaboration for Inductive and Interpretive Text Analysis

    Summary

    Scholastic demonstrates how human-centered algorithm design and visualizations employing familiar metaphors can support inductive and interpretive research methodologies through interactive topic modeling and document clustering.

  • The Weighted Average Illusion: Biases in Perceived Mean Position in Scatterplots

    Summary

    Scatterplots can encode a third dimension by using additional channels like size or color (e.g. bubble charts). We explore a potential misinterpretation of trivariate scatterplots, which we call the weighted average illusion, where locations of larger and darker points are given more weight toward x- and y-mean estimates.

  • MiLa: An Audiovisual Instrument for Learning the Curwen Hand Signs

    Summary

    We present a novel musical system for learning the Curwen-Kodaly hand signs, which stand for solfege syllables and pitches (do, re, mi, etc.). These hand postures comprise a system of musical notation typically used in sight-singing training to familiarize with patterns of musical tones. Therefore, what concerns us is music literacy as opposed to practice with any particular instrument. Our system uses a Leap motion sensor to recognize the hand signs and produce corresponding user-recorded sounds.

I Like Designing with Data

Teaching

I was previously a TA for:


UNC Chapel Hill

COMP 790: Visualization Design Studies

data visualization
cognitive psychology
prototyping

University of Colorado Boulder

ATLS 1300: Computational Foundations 1

creative coding
computational thinking
object-oriented programming

Northwestern University

EECS 395: Tangible Interaction Design and Learning

tangible interaction
education exhibits
UX design

Service

I am a reviewer for:


IEEE VIS
2022
2023

ACM CHI
2024

IEEE TVCG
2024

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Music: I'm a classically trained singer who keeps track of my music listening history. I'm also a member of the UNC Ballroom Dance Club.



Sports: I'm a Brazilian Jiu-Jitsu and Muay Thai hobbyist; when it's sunny out, I'm often playing pickleball.