Alison M Smith-Renner

interactive machine learning, human-in-the-loop, information visualization, hci
Research scientist & engineer who designs, builds, and evaluates intelligent systems and interactive visualizations for data exploration, analysis, and augmented decision making. My research lies at the intersection of AI/ML and human-computer interaction, building explainable and interactive AI/ML systems to engender trust, improve performance, and support human-machine collaboration.

Publications

I live at the intersection of AI/ML and HCI.
Alison Renner. Designing for the Human in the Loop: Transparency and Control in Interactive Machine Learning. PhD Dissertation, Computer Science, University of Maryland, College Park,, 2020. [pdf]
Alison Smith-Renner, Ron Fan, Melissa Birchfield, Sherry Wu, Jordan Boyd-Graber, Dan Weld, Leah Findlater. No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML. CHI, 2020. [pdf]
Alison Smith-Renner, Varun Kumar, Jordan Boyd-Graber, Kevin Seppi, Leah Findlater. Digging into User Control: Perceptions of Adherence and Instability in Transparent Models. IUI, 2020. [pdf]
Varun Kumar, Alison Smith-Renner, Leah Findlater, Kevin Seppi, Jordan Boyd-Graber. Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models. ACL, 2019. [pdf]
Bran Knowles, Alison Smith, Forough Poursabzi-Sangdeh, Di Lu, Halmit Alabi. Uncertainty in Current and Future Health Wearables. Communications of the ACM, 2018. [pdf]
Alison Smith, Varun Kumar, Jordan Boyd-Graber, Kevin Seppi, Leah Findlater. Closing the Loop: User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System. Intelligent User Interfaces, 2018. Best Student Paper Honorable Mention. [pdf]
Alison Smith and James J. Nolan. The Problem of Explanations without User Feedback. IUI Workshop on Explainable Smart Systems, 2018. [pdf]
Tak Yeon Lee, Alison Smith, Kevin Seppi, Niklas Elmqvist, Jordan Boyd-Graber, Leah Findlater. The Human Touch: How Non-Expert Users Perceive, Interpet, and Fix Topic Models. International Journal of Human-Computer Studies, 2017. [pdf]
Alison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Niklas Elmqvist, Leah Findlater. Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels. Transactions of the Association of Computational Linguistics, 2017. [pdf]
Alison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Niklas Elmqvist, Kevin Seppi, Leah Findlater. Human-Centered and Interactive: Expanding the Impact of Topic Models. CHI 2016 Workshop on Human-Centered Machine Learning, 2016. [pdf]
Alison Smith, Sana Malik, and Ben Shneiderman. Visual Analysis of Topical Evolution in Unstructured Text: Design and Evaluation of TopicFlow. Applications of Social Media and Social Network Analysis. Springer International Publishing, 2015. [pdf]
Alison Smith, Timothy Hawes, Jim Nolan. Towards an Automated Intelligence Product Generation Capability. SPIE Sensing Technology + Applications. International Society for Optics and Photonics, 2015. [proceedings]
Alison Smith, Timothy Hawes, and Meredith Myers. Hierarchie: Interactive Visualization for Hierarchical Topic Models. ACL 2014 Workshop on Interactive Language Learning, Visualization, and Interfaces, 2014. [pdf]
Alison Smith, Jason Chuang, Yuening Hu, Jordan Boyd-Graber, and Leah Findlater. Concurrent Visualization of Relationships between Words and Topics in Topic Models. ACL 2014 Workshop on Interactive Language Learning, Visualization, and Interfaces, 2014. [pdf]
Sana Malik, Alison Smith, Timothy Hawes, Panagis Papadatos, Jianyu Li, Cody Dunne, Ben Shneiderman. TopicFlow: Visualizing Topic Alignment of Twitter Data over Time. Proceedings of 2013 IEEE/ACM ASONAM. ACM, 2013.
Yuening Hu, Jordan Boyd-Graber, Brianna Satinoff, and Alison Smith. Interactive Topic Modeling. Machine Learning Journal. Springer International Publishing, 2013. [journal]
Yuening Hu, Alison Smith, Jordan Boyd-Graber. User Study for Interactive Topic Modeling. Women in Machine Learning. NIPS, 2013. [poster]

samples

img01
visualign
interface and visualization of genomic sequence alignment
{d3, javascript, html5, css3} @ 2013
img01
Termite UI
interface and visualization to support interactive topic modeling
{angular, d3, javascript, html5, css3} @2014
heat map of road races in the DC area
Race Map
visualization of road race metadata
leaflet, javascript, html5, css3 @ 2014
img01
Hierarchie
data visualization of the results of hierarchical topic modeling
{angular, d3, javascript, html, css} @ 2014
img01
Topic Flow
user interface and data visualization for exploring the evolution of topics in text
{d3, javascript, html, css} @ 2012
img01
CHART UI
coordinated views for exploring text data by time, location, and discovered topics
{d3, leaflet, javascript, html, css} @ 2013

Academic Experience

I am active in the interactive machine learning, explainable artificial intelligence, and human-centered machine learning research communities.
Invited Talks
Gave talk on "unpredictable controls in interactive ML" to the Interactive Adaptive Learning (IAL) Workshop collocated with the ECML PKDD Conference, September 2021.
Gave talk on "transparency and control in interactive ML" at the Bristol Interactive AI Summer School (BIAS), September 2021.
Invited panelist at the Interactive Learning for Natural Language Processing (InterNLP) Workshop collocated with the ACL Conference, August 2021.
Gave talk on "unpredictable controls in interactive ML" to the Google PAIR lab, March 2021.
Gave talk on "transparency, control, and input uncertainty in interactive ML" to the Ohio State University, CSE Department, AI group, January 2021.
Workshop and Journal Organization
Journal Special Issue AI for (and by) the People in Multimodal Technologies and Interaction (MDPI), 2021. editors: Alison Smith-Renner, Gagan Bansal, Gonzalo Ramos
From "Explainable AI" to "Graspable AI" at Conference on Tangible Embedded and Embodied Interaction (TEI), 2021. organizers: Jeffrey Bardzell, Laurens Boer, David Cuartielles, Maliheh Ghajargar, Kristina Höök, Peter Gall Krogh, Alison Smith-Renner, and Mikael Wiberg.
Transparency and Explanations in Smart Systems: Expainable AI for Fairness and Social Justice at ACM Conference on Intelligent User Interfaces (IUI), 2021. organizers: Jonathan Dodge, Casey Dugan, Styliani Kleanthous, Tsvi Kuflik, Min Kyung Lee, Brian Lim, Advait Sarkar, Avital Shulner-Tal, Alison Smith-Renner, and Simone Stumpf.
Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies at ACM Conference on Intelligent User Interfaces (IUI), 2020. organizers: Casey Dugan, Styliani Kleanthous, Tsvi Kuflik, Brian Lim, Jahna Otterbacher, Advait Sarkar, Avital Shulner, Alison Smith-Renner, and Simone Stumpf; keynote: Carrie Cai.
Human-Centered Machine Learning Perspectives at ACM CHI Conference on Human Factors in Computing Systems, 2019. organizers: Saleema Amershi, Richard Banks, Gagan Bansal, Rebecca Fiebrink, Soroush Ghorashi, Christopher Meek, Gonzalo Ramos, Alison Smith-Renner, and Jina Suh.
2nd Workshop on Explainable Smart Systems at ACM Conference on Intelligent User Interfaces (IUI), 2019. organizers: Brian Lim, Advait Sarkar, Alison Smith, and Simone Stumpf; keynote: Margaret Burnette.
Workshop on Explainable Smart Systems at ACM Conference on Intelligent User Interfaces (IUI), 2018. organizers: Brian Lim, Alison Smith, and Simone Stumpf; keynote: Dave Gunning.

Program Committees
Conferences and journals: CHI (2017-2022); IUI PC (2018-2021), SPC (2022), organizing committee--workshops and tutorials (2022); ACL (2018-2020); CSCW (2020, 2021); UIST (2018); IEE AIVR (2018); VIS (2019); TIIS PC (2020), editorial board--distinguished reviewer (2021); IJHC (2020), TSC (2020)
Workshops: MASES (2018), CD-MAKE (2019), DebugML (2019), VizSec (2019, 2020), InterNLP@ACL (2021), Bridging HCI and NLP@EACL (2021), Human-Centered XAI@CHI (2021)

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