Fred Hohman

Data science + visualization researcher

I research how to enable machine learning interpretability at scale and for everyone, by designing and developing interactive interfaces to help people confidently understand data-driven systems. Besides building tools, I also create data visualizations and write interactive articles to simply communicate complex ideas.
I have collaborated with researchers, designers, developers, and artists while working at Apple, Microsoft Research, NASA Jet Propulsion Lab, and Pacific Northwest National Lab.
My research is supported by a NASA Space Technology Research Fellowship.

Education

Present — Aug. 2015
Ph.D. in Computational Science & Engineering
Georgia Institute of Technology, Atlanta, GA
Advisor: Duen Horng (Polo) Chau, Co-advisor: Alex Endert
Thesis: Interactive Scalable Interfaces for Machine Learning Interpretability
Committee: Duen Horng (Polo) Chau, Alex Endert, Chao Zhang, Nathan Hodas, Scott Davidoff, Steven Drucker
May 2018
M.S. in Computational Science & Engineering
Georgia Institute of Technology, Atlanta, GA
GPA: 4.00/4.00
May 2015 — Aug. 2011
B.S. in Mathematics, B.S. in Physics
University of Georgia, Athens, GA
Thesis: 3D Printing the Trefoil Knot and its Pages
Overall GPA: 3.84/4.00, Magna Cum Laude, Area of Emphasis in Applied Mathematics

Industry Research Experience

Summer 2019
Apple, Seattle, WA
Research Intern, Turi Human-centered Machine Learning Group
Mentor: Kanit Wongsuphasawat, Kayur Patel
Designed and developed interactive visualizations for data iteration in machine learning, published at CHI 2020.
Summer 2018
Microsoft Research, Redmond, WA
Research Intern, Human-Computer Interaction Group
Mentor: Steven Drucker
Designed, developed, and deployed interactive interface for operationalizing machine learning interpretability, published at CHI 2019.
Summer 2017
NASA Jet Propulsion Lab, Pasadena, CA
Creative Computer Scientist, Human Interfaces Group
Mentor: Scott Davidoff, Arun Viswanathan
Joint work between NASA JPL, Caltech, and Art Center creating interactive data visualizations for current scientific research. Prototype presented to lab leadership and secured funding to be incorporated into Mars 2020 mission.
Summer 2016
Pacific Northwest National Lab, Richland, WA
National Security Ph.D. Intern, Data Sciences & Analytics Group
Mentor: Nathan Hodas
Built interactive tools that generate synthetic images to explain deep learning classifiers, published at CHI 2017.

Academic Research Experience

Present — Aug. 2016
Georgia Institute of Technology, Atlanta, GA
Graduate Research Assistant, School of Computational Science and Engineering
Advisor: Duen Horng (Polo) Chau, Alex Endert
Member of the Polo Club of Data Science where we bridge and innovate at the intersection of data mining and human-computer interaction to synthesize scalable, interactive, and interpretable tools that amplify human’s ability to understand and interact with big data.
May 2016 — Aug. 2015
Georgia Institute of Technology, Atlanta, GA
Graduate Research Assistant, School of Computational Science and Engineering
Mentor: Surya Kalidindi
Conducted research in physical data science and material informatics by creating property-structure linkages using machine learning to predict material properties. Contributed to direction and code of PyMKS: Materials Knowledge Systems in Python.
May 2015 — Jan. 2013
University of Georgia, Athens, GA
Undergraduate Research Assistant, Department of Mathematics
Advisor: David Gay
Explored 3D printing and mathematical exposition in topology. Programmed, designed, and 3D printed 34-piece, color-coordinated, and magnetized 3D puzzle of the trefoil knot fibration. Led 3D printing research and education in mathematics department.
Summer 2014
REU in Mathematics and Computational Science, Fairfield, CT
Fairfield University, Department of Mathematics
Mentor: Shanon Reckinger
Directly compared numerical solutions from Navier-Stokes equations to designed lab-scale experiments to model specific ocean phoneme. Configured MIT General Circulation Model on CPU cluster to run parallel computational fluid dynamics simulations.

Honors and Awards

2019
Best Paper at ACM CHI Conference
For "Managing Messes in Computational Notebooks"
2018
Best Paper, Honorable Mention at VISxAI Workshop at IEEE VIS
For "The Beginner's Guide to Dimensionality Reduction"
2018 — 2021
NASA Space Technology Research Fellowship
For my Ph.D. work on "Understanding Deep Neural Networks Through Attribution and Interactive Experimentation"
2018
Audience Appreciation Award, Runner Up at ACM SIGKDD Conference
For "Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression"
2017 — 2018
Microsoft Azure for Research Award: AI for Earth
For our work on "Deep Learning for Fine-scale Population Maps"
2017
Best Demo, Honorable Mention at ACM SIGMOD/PODS Conference
For "Visual Graph Query Construction and Refinement"
2015 — 2019
President's Fellowship at Georgia Institute of Technology
Select number of 1st year doctoral students who bring exemplary levels of scholarship and innovation to their academic departments
2015
Outstanding Poster at JMM Undergraduate Poster Session in Computational Math
For "Experimental and Numerical Comparison of Oceanic Overflow"
2015
UGA CURO Research Graduation Distinction
Awarded to undergraduates who write a thesis, present at the CURO Symposium, and complete 9 research credit hours
2014
UGA CURO Research Assistantship
Stipend awarded to outstanding undergraduates that actively participate in faculty-mentored research
2011 — 2015
Dean's List
Achieved at least a 3.5 GPA during a semester with minimum 14 credit hours
2011 — 2015
Georgia HOPE Scholarship
Merit-based award to Georgia residents providing tuition assistance for their undergraduate degree
2011
Mission of Blessed Trinity: Artistic Sensibility
One of two students to receive the Mission Statement award upon high-school graduation

Publications

Selected: Latest & Greatest

Understanding and Visualizing Data Iteration in Machine Learning
Fred Hohman, Kanit Wongsuphasawat, Mary Beth Kery, Kayur Patel
ACM Conference on Human Factors in Computing Systems (CHI). Honolulu, HI, USA, 2020.
Project PDF Video Preview Recording Slides BibTeX
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Fred Hohman, Haekyu Park, Caleb Robinson, Duen Horng (Polo) Chau
IEEE Transactions on Visualization and Computer Graphics (TVCG). Vancouver, Canada, 2020.
Project Demo PDF Video Recording Slides Code BibTeX
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
Angel Cabrera, Will Epperson, Fred Hohman, Minsuk Kahng, Jamie Morgenstern, Duen Horng (Polo) Chau
IEEE Conference on Visual Analytics Science and Technology (VAST). Vancouver, Canada, 2019.
Project Demo PDF Blog Recording Slides Code BibTeX
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLine, Steven Drucker
ACM Conference on Human Factors in Computing Systems (CHI). Glasgow, UK, 2019.
Project Demo PDF Blog Video Preview Slides BibTeX
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Fred Hohman, Minsuk Kahng, Robert Pienta, Duen Horng (Polo) Chau
IEEE Transactions on Visualization and Computer Graphics (TVCG). Berlin, Germany, 2018.
Project Demo PDF Blog Video Slides Code BibTeX

All Publications

Understanding and Visualizing Data Iteration in Machine Learning
Fred Hohman, Kanit Wongsuphasawat, Mary Beth Kery, Kayur Patel
ACM Conference on Human Factors in Computing Systems (CHI). Honolulu, HI, USA, 2020.
Project PDF Video Preview Recording Slides BibTeX
The Future of Notebook Programming Is Fluid
Mary Beth Kery, Donghao Ren, Kanit Wongsuphasawat, Fred Hohman, Kayur Patel
Extended Abstracts on ACM Human Factors in Computing Systems (CHI). Honolulu, HI, USA, 2020.
Project PDF BibTeX
CNN 101: Interactive Visual Learning for Convolutional Neural Networks
Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, Duen Horng (Polo) Chau
Extended Abstracts on ACM Human Factors in Computing Systems (CHI). Honolulu, HI, USA, 2020.
Project PDF Video BibTeX
Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning
Nilaksh Das, Haekyu Park, Zijie J. Wang, Fred Hohman, Robert Firstman, Emily Rogers, Duen Horng (Polo) Chau
Extended Abstracts on ACM Human Factors in Computing Systems (CHI). Honolulu, HI, USA, 2020.
Project PDF BibTeX
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Fred Hohman, Haekyu Park, Caleb Robinson, Duen Horng (Polo) Chau
IEEE Transactions on Visualization and Computer Graphics (TVCG). Vancouver, Canada, 2020.
Project Demo PDF Video Recording Slides Code BibTeX
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
Angel Cabrera, Will Epperson, Fred Hohman, Minsuk Kahng, Jamie Morgenstern, Duen Horng (Polo) Chau
IEEE Conference on Visual Analytics Science and Technology (VAST). Vancouver, Canada, 2019.
Project Demo PDF Blog Recording Slides Code BibTeX
TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning
Fred Hohman*, Arjun Srinivasan*, Steven Drucker
IEEE Visualization Conference (VIS). Vancouver, Canada, 2019.
Project Demo PDF Preview Recording Slides Code BibTeX *Authors contributed equally
ElectroLens: Understanding Atomistic Simulations through Spatially-resolved Visualization of High-dimensional Features
Xiangyun Lei, Fred Hohman, Duen Horng (Polo) Chau, Andrew Medford
IEEE Visualization Conference (VIS). Vancouver, Canada, 2019.
Project PDF Code BibTeX
Launching the Parametric Press
Matthew Conlen, Fred Hohman
Visualization for Communication at IEEE VIS (VisComm). Vancouver, Canada, 2019.
Project Demo PDF Code BibTeX
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLine, Steven Drucker
ACM Conference on Human Factors in Computing Systems (CHI). Glasgow, UK, 2019.
Project Demo PDF Blog Video Preview Slides BibTeX
Managing Messes in Computational Notebooks
Andrew Head, Fred Hohman, Titus Barik, Steven Drucker, Robert DeLine
ACM Conference on Human Factors in Computing Systems (CHI). Glasgow, UK, 2019.
Project Demo PDF Video Preview Slides Code BibTeX Best Paper
Discovery of Intersectional Bias in Machine Learning Using Automatic Subgroup Generation
Angel Cabrera, Minsuk Kahng, Fred Hohman, Jamie Morgenstern, Duen Horng (Polo) Chau
Debugging Machine Learning Models Workshop at ICLR (Debug ML). New Orleans, LA, USA, 2019.
Project PDF BibTeX
NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions
Haekyu Park, Fred Hohman, Duen Horng (Polo) Chau
Poster, IEEE Pacific Visualization Symposium (PacificVis). Bangkok, Thailand, 2019.
Project Demo PDF Slides Poster BibTeX
Atlas: Local Graph Exploration in a Global Context
James Abello*, Fred Hohman*, Varun Bezzam, Duen Horng (Polo) Chau
ACM Conference on Intelligent User Interfaces (IUI). Los Angeles, CA, USA, 2019.
Project PDF Video Talk Slides Code BibTeX *Authors contributed equally
Scalable K-Core Decomposition for Static Graphs Using a Dynamic Graph Data Structure
Alok Tripathy, Fred Hohman, Duen Horng (Polo) Chau, Oded Green
IEEE International Conference on Big Data (Big Data). Seattle, WA, USA, 2018.
Project PDF BibTeX
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Fred Hohman, Minsuk Kahng, Robert Pienta, Duen Horng (Polo) Chau
IEEE Transactions on Visualization and Computer Graphics (TVCG). Berlin, Germany, 2018.
Project Demo PDF Blog Video Slides Code BibTeX
The Beginner's Guide to Dimensionality Reduction
Matthew Conlen, Fred Hohman
Workshop on Visualization for AI Explainability at IEEE VIS (VISxAI). Berlin, Germany, 2018.
Project Demo Slides Code BibTeX Best Paper, Honorable Mention
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression
Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng (Polo) Chau
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). London, UK, 2018.
Project PDF Video Code BibTeX Audience Appreciation Award, Runner Up
Compression to the Rescue: Defending from Adversarial Attacks Across Modalities
Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng (Polo) Chau
Project Showcase, ACM SIGKDD Conference on Knowledge Discovery and Data Mining. London, UK, 2018.
Project PDF Code BibTeX
Interactive Classification for Deep Learning Interpretation
Angel Cabrera, Fred Hohman, Jason Lin, Duen Horng (Polo) Chau
Demo, Conference on Computer Vision and Pattern Recognition (CVPR). Salt Lake City, UT, USA, 2018.
Project Demo PDF Video Code BibTeX
VIGOR: Interactive Visual Exploration of Graph Query Results
Robert Pienta, Fred Hohman, Alex Endert, Acar Tamersoy, Kevin Roundy, Chris Gates, Shamkant Navathe, Duen Horng (Polo) Chau
IEEE Transactions on Visualization and Computer Graphics (TVCG). Phoenix, AZ, USA, 2018.
Project PDF Video Preview BibTeX
3D Exploration of Graph Layers via Vertex Cloning
James Abello*, Fred Hohman*, Duen Horng (Polo) Chau
Poster, IEEE Conference on Visual Analytics Science and Technology (VAST). Phoenix, AZ, USA, 2017.
Project PDF Video Poster BibTeX *Authors contributed equally
A Viz of Ice and Fire: Exploring Entertainment Video Using Color and Dialogue
Fred Hohman, Sandeep Soni, Ian Stewart, John Stasko
2nd Workshop on Visualization for the Digital Humanities at IEEE VIS (VIS4DH). Phoenix, AZ, USA, 2017.
Project Demo PDF Slides Code Data BibTeX
A Deep Learning Approach for Population Estimation from Satellite Imagery
Caleb Robinson, Fred Hohman, Bistra Dilkina
1st ACM SIGSPATIAL Workshop on Geospatial Humanities (GeoHum.). Redondo Beach, CA, USA, 2017.
Project Demo PDF Code BibTeX Microsoft AI for Earth Award
mHealth Visual Discovery Dashboard
Dezhi Fang, Fred Hohman, Peter Polack, Hillol Sarker, Minsuk Kahng, Moushumi Sharmin, Mustafa al'Absi, Duen Horng (Polo) Chau
Demo, ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp). Maui, HI, USA, 2017.
Project PDF Video Poster BibTeX
Visual Graph Query Construction and Refinement
Robert Pienta, Fred Hohman, Acar Tamersoy, Alex Endert, Shamkant Navathe, Hanghang Tong, Duen Horng (Polo) Chau
Demo, ACM International Conference on Management of Data (SIGMOD/PODS). Chicago, IL, USA, 2017.
Project PDF Video Poster BibTeX Best Demo, Honorable Mention
ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation
Fred Hohman, Nathan Hodas, Duen Horng (Polo) Chau
Extended Abstracts on ACM Human Factors in Computing Systems (CHI). Denver, CO, USA, 2017.
Project PDF Video Poster Code BibTeX
Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression
Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng (Polo) Chau
arXiv:1705.02900. 2017.
Project PDF Code BibTeX
The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study
Shanon Reckinger, Thomas Gibson, Fred Hohman, Theresa Morrison, Scott Reckinger, Mateus Carvalho
International Journal of Computational Methods and Experimental Measurements (CMEM). 2019.
Project PDF BibTeX
Experimental and Numerical Comparison of Oceanic Overflow
Thomas Gibson, Fred Hohman, Theresa Morrison, Shanon Reckinger, Scott Reckinger
Abstract, American Physical Society Division of Fluid Dynamics (APS DFD). San Francisco, CA, USA, 2014.
Project Blog Poster

Talks

Interactive Scalable Interfaces for Machine Learning Interpretability
May 2020
IBM Research
Apr. 2020
Microsoft Research
Apr. 2020
Apple
Apr. 2020
Autodesk Research
Dec. 2019
Georgia Tech Thesis Proposal
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Mar. 2020
NVIDIA GTC
Oct. 2019
IEEE Visualization
TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning
Oct. 2019
IEEE Visualization
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
June 2019
Microsoft Machine Learning and Data Science Summit
May 2019
ACM Conference on Human Factors in Computing Systems
Explaining Machine Learning Models Using Interactive Visualization
Mar. 2019
Georgia Tech School of CSE Strategic Partnership Program Summit
Apr. 2019
Georgia Tech CSE 6242 Data and Visual Analytics
Mar. 2019
Symantec Research Labs
Mar. 2019
NASA Jet Propulsion Laboratory
Atlas: Local Graph Exploration in a Global Context
Mar. 2019
ACM Intelligent User Interfaces
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Jan. 2019
Carnegie Mellon University
Oct. 2018
University of Georgia
Oct. 2018
IEEE Visualization
The Beginner's Guide to Dimensionality Reduction
Oct. 2018
VISxAI Workshop at IEEE Visulization
Comparing Interactive Local and Global Explanation Paradigms for Human-assisted Machine Learning Tasks
July 2018
Microsoft Research
Graph Playgrounds: 3D Exploration of Graph Layers via Vertex Cloning
Dec. 2017
AT&T Research Labs Graduate Student Symposium
A Viz of Ice and Fire: Exploring Entertainment Video Using Color and Dialogue
Oct. 2017
2nd Workshop on Visualization for the Digital Humanities at IEEE Visualization
Constellation: Visualizing Cybersecurity in Real Time
Aug. 2017
NASA Jet Propulsion Laboratory
Aug. 2017
California Institute of Technology
Visualizing Learned Semantics with Deep Learning
Nov. 2016
Georgia Tech Ph.D. Qualifying Oral Exam
Drawing Semantics with Deep Learning
2016
Pacific Northwest National Laboratory
3D Printing The Trefoil Knot And Its Pages
Mar. 2015
UGA Center for Undergraduate Research Symposium, included hands-on demo
Experimental and Numerical Studies of Oceanic Overflow
June 2015
AMS Conference on Atmospheric and Oceanic Fluid Dynamics
Jan. 2015
Joint Mathematics Meeting
Nov. 2014
APS Division of Fluid Dynamics
Aug. 2014
Invited and presented on behalf at Brown University, Los Alamos National Lab
July 2014
Northeast REU Mini-Conference at Yale University
July 2014
University of Rhode Island Bay Campus
3D Printing in Topology
Mar. 2014
UGA Center for Undergraduate Research Symposium, included hands-on demo

Press

June 2020
"How Do Neural Networks Learn?", Two Minute Papers
Mar. 2020
"Visualizing Fairness in Machine Learning", Data Stories Podcast
Nov. 2019
"The Interactive News Platform for Everyone", Stack Overflow Blog
Oct. 2019
"Is this the dynamic web we were promised?", Hanselminutes Podcast
May 2019
"The Secret Life of a JPEG", Fast Company
Dec. 2018
"'Human Rights' May Help Shape Artificial Intelligence in 2019", Georgia Tech, College of Computing
Dec. 2018
"Designers, Programmers, and Researchers Join Forces to Create a New Kind of Digital Magazine Called the Parametric Press", Georgia Tech, College of Computing
June 2018
"Georgia Tech Teams up with Intel to Protect Artificial Intelligence from Malicious Attacks Using SHIELD", Georgia Tech, College of Computing
Dec. 2017
"Georgia Tech Team To Use Microsoft Grant to Study Human Migration Dynamics", Georgia Tech, College of Computing
Sept. 2015
"Georgia Tech PhD Student Puts Finishing Touches on 3D Printed Trumpety Trefoil", 3dprint.com
Spring 2015
"Student Profile: Fred Hohman", 2015 UGA Mathematics Department Newsletter
Feb. 2015
"Falling Water", MITgcm.org
Dec. 2014
"Mathematics/Physics Student Creates 3D Printed Puzzle of Trefoil Knot, Catches Mathematical Community's Interest", 3dprint.com
July 2014
"Day 311 - Trefoil Trumpet", Makerhome.com
Apr. 2014
"Mathematics with 3D Printing", Sketches of Topology

Teaching

Spring 2019
Graduate Teaching Assistant
Georgia Institute of Technology, Atlanta, GA
Information Visualization (CS 4460), Instructor: Alex Endert
Designed homeworks, held weekly office hours, and mentored student team projects for Information Visualization (CS 4460), an undergraduate course with 134 students enrolled.
Spring 2017
Graduate Teaching Assistant
Georgia Institute of Technology, Atlanta, GA
Data and Visual Analytics (CSE 6242 / CX 4242), Instructor: Duen Horng (Polo) Chau
Designed homeworks, held weekly office hours, and mentored student team projects for Data and Visual Analytics (CSE 6242 / CX 4242), a graduate course with 214 students enrolled.
2014 — 2015
Student Notetaker
University of Georgia, Athens, GA
Generated notes for undergraduate mathematics and physics courses for students with disabilities.
2012
Tutor
University of Georgia, Athens, GA
Specialized in tutoring calculus to undergraduates.

Mentoring

Present — Fall 2019
Omar Shaikh
B.S. in Computer Science, Georgia Institute of Technology
Visualization for machine learning education
Present — Fall 2019
Robert Turko
B.S. in Computer Science, Georgia Institute of Technology
Visualization for machine learning education
Present — Fall 2019
Rob Firstman
B.S. in Computer Science, Georgia Institute of Technology
Visualization for deep learning interpretability
Spr. 2020 — Spr. 2019
Will Epperson
B.S. in Computer Science, Georgia Institute of Technology
Visualization for machine learning fairness
Stamps President's Scholar
Now: PhD Student (HCI) at Carnegie Mellon University
Spr. 2020 — Spr. 2019
Siwei Li
B.S. in Computer Science, Georgia Institute of Technology
Visual graph analytics
Outstanding Undergraduate Researcher, College of Computing, Georgia Institute of Technology
President's Undergraduate Research Award
Now: Software Engineer II at Google
Spr. 2019 — Spr. 2018
Angel Alexander Cabrera
B.S. in Computer Science, Georgia Institute of Technology
Visualization for machine learning fairness, interactive classification for deep learning
National Science Foundation Graduate Research Fellowship Program (NSF GRFP)
Love Family Foundation Scholarship (most outstanding graduating senior), Georgia Institute of Technology
Stamps President's Scholar
Now: PhD Student (HCI) at Carnegie Mellon University
Spr. 2018 — Fall 2016
Dezhi Fang
B.S. in Computer Science, Georgia Institute of Technology
Visual motif discovery
Outstanding Undergraduate Researcher, College of Computing, Georgia Institute of Technology
Faculty Materials, Supplies, and Travel Grants for Undergraduate Research
Awarded President's Undergraduate Research Travel Award
Now: Software Development Engineer at Airbnb
Spr. 2018 — Fall 2017
Prasenjeet Biswal
M.S. in Computer Science, Georgia Institute of Technology
Deep learning attribution
Now: Software Development Engineer at Oath

Grants and Funding

2018 — 2021
Understanding Deep Neural Networks Through Attribution and Interactive Experimentation
NSTRF: NASA Space Technology Research Fellowship
Co-PIs: Duen Horng (Polo) Chau
Funded $80,000/year for 3 years
2017 — 2018
Deep Learning for Fine-scale Population Maps
Microsoft Azure for Research Award: AI for Earth
Co-PIs: Caleb Robinson, Bistra Dilkina
Funded $15,000
Fall 2014
3D Printing the Trefoil Knot and its Pages
UGA CURO Research Assistantship
Co-PIs: David Gay
Funded $1,000

Interactive Articles

Present — Dec. 2018
Parametric Press
Matthew Conlen, Fred Hohman, Sara Stalla, Victoria Uren, Andrew Sass
An experimental, born-digital magazine dedicated to showcasing the expository power that’s possible when the audio, visual, and interactive capabilities of dynamic media are effectively combined
May 2019
The Myth of the Impartial Machine on Parametric Press
Alice Feng, Shuyan Wu, Fred Hohman, Matthew Conlen, Victoria Uren
Wide-ranging applications of data science bring utopian proposals of a world free from bias, but in reality, machine learning models reproduce the inequalities that shape the data they’re fed. Can programmers free their models from prejudice?, Top of Hacker News
May 2019
On Particle Physics on Parametric Press
Riccardo Maria Bianchi, Fred Hohman, Matthew Conlen
A CERN particle physicist walks through the history and science of particle physics, and why you should care about it—even outside of the laboratory
May 2019
Data Science for Fair Housing on Parametric Press
Alyson Powell Key, Fred Hohman, Matthew Conlen, Sara Stalla
Cities across America covertly exclude racial minorities from majority-white residential neighborhoods, while gentrification drives people of color out of their homes. In Atlanta, a new nonprofit seeks to resist displacement by supporting the city’s most vulnerable residents—but how effective is their project?
Nov. 2018
Blueberry Pancakes
Caleb Robinson, Fred Hohman
A toy algorithms problem
July 2018
The Beginner's Guide to Dimensionality Reduction
Matthew Conlen, Fred Hohman
Explore the methods data scientists use to visualize high-dimensional data, VISxAI Best Paper, Honorable Mention
June 2018
The Math of Card Shuffling
Fred Hohman
Riffling from factory order to complete randomness, Top of Hacker News
Oct. 2017
A Viz of Ice and Fire
Fred Hohman, Sandeep Soni, Ian Stewart, John Stasko
Exploring and visualizing Game of Thrones using color and dialogue

Service

Organizer
Workshop on Visualization for AI Explainability (VISxAI) at IEEE VIS 2020, 2019
Program Commitee
Debugging Machine Learning Models Workshop (DebugML) at ICLR 2019
ACM International Conference on Intelligent User Interfaces (IUI) 2019
Symposium on Visualization in Data Science (VDS) at IEEE VIS 2018
Workshop on Visualization for AI Explainability (VISxAI) at IEEE VIS 2018
Workshop on Interactive Data Exploration and Analytics (IDEA) at KDD 2018
Reviewer
IEEE Visualization (VIS) 2020, 2019, 2018, 2017
ACM Conference on Human Factors in Computing Systems (CHI) 2020, 2019, 2018, 2017
ACM User Interface Software and Technology Symposium (UIST) 2020
Distill Research Journal (Distill) 2019
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2019, 2017
ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW) 2019
Human-Centered Machine Learning Perspectives Workshop (HCMLP) 2019
1st Deep Learning and Security Workshop (DLS) at IEEE SP 2018
Symposium on Visualization in Data Science (VDS) at IEEE VIS 2017
IEEE International Conference on Distributed Computing Systems (ICDCS) 2017
SIAM International Conference on Data Mining (SDM) 2017
Institutional
Georgia Tech CSE Graduate Student Association, Vice President, 2018 - 2020
Georgia Tech CSE Chair Search Committee, 2019 - 2020
Member
Present — 2016
Association for Computing Machinery (ACM)
Present — 2016
Institute of Electrical and Electronics Engineers (IEEE)
2012 — 2015
UGA Mathematics Club
2012 — 2013
Society of Physics Students, UGA Chapter (SPS)
2011 — 2015
National Society of Collegiate Scholars (NSCS)

Design

2017 — 2018
IDEA Workshop Proceedings Cover (2017, 2018)
ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA)
Designed workshop poster and conference proceedings cover
2017
Brad Myers Advisee Tree
ACM Conference on Human Factors in Computing Systems (CHI), Denver, USA
Designed and implemented an interactive visualization of Brad Myers's advisee tree shown during his CHI 2017 Lifetime Research Award talk; designed accompanying ribbon worn by attendees at the conference
Aug. 2014
3D Printed Cube Decomposition Trophy
University of Georgia Mathematics Department, Athens, USA
Designed, modeled, and 3D printed cube decomposition trophy for annual UGA High School Math Tournament that was given to the top scoring teams and participants
Aug. 2014
3D Printed UGA Keychain
University of Georgia Lamar Dodd School of Art, Athens, USA"
Created 3D printed UGA keychain and presentation notes given at Experience UGA: a interdisciplinary event that exposes middle-school and high-school students to hands-on learning activities

References

Dr. Polo Chau, Associate Professor
School of Computational Science and Engineering
Georgia Institute of Technology
Dr. Alex Endert, Associate Professor
School of Interactive Computing
Georgia Institute of Technology
Dr. Scott Davidoff, Senior Manager
Human-Centered Design Group
NASA Jet Propulsion Lab
Dr. Steven Drucker, Partner and Research Manager
Visualization and Interactive Data Analysis Group
Microsoft Research
Dr. Nathan Hodas, Senior Research Scientist
Data Sciences and Analytics Group
Pacific Northwest National Laboratory