Sangho Suh

200 University Avenue

Waterloo, ON, Canada

I am a postdoctoral researcher in the Design Lab and Creativity Lab at the University of California, San Diego. I earned my Ph.D. in Computer Science from the University of Waterloo where I was advised by Edith Law and was a member of the Human-Computer Interaction Lab.

With programming, data, and AI permeating every aspect of our lives and the tools we use, literacy in these fields is becoming a critical part of our training and education in the 21st century. My research aims to support this need by augmenting our intelligence in areas such as learning, creativity, and sensemaking. I am particularly interested in creating new techniques, tools, and systems that leverage dynamic, layered representations and computational methods/AI.

During my Ph.D., I investigated this in the context of teaching programming, exploring how we can learn and make sense of abstract concepts, languages, and procedures in programming with comics. Specifically, I introduced a new concept called coding strip, a form of comic strip with corresponding code, and developed tools for designing, creating, and using coding strips—design methods, creativity support tools, and visual programming environment.

Research Interests:
Human-Computer/AI Interaction, Computing Education, Creativity Support, Concept-driven/Collaborative Storytelling, Creative Coding, Learning Analytics

Previously:
I received B.S. in Computer Science from Korea University where I worked with Jaegul Choo to develop data mining algorithm and visual analytics for convolutional neural network.

For more details, check my cv.

highlights [archive]

Jun 30, 2022 “CodeToon: Authoring Tool for Creating Comics from Code with Story Ideation and Automatic Comic Generation” is conditionally accepted at UIST 2022!
Jun 13, 2022 Our DIS 2022 paper received Best Paper Honorable Mention Award!🎖
Jun 8, 2022 Taught Experiment Design at Toronto Human-AI Interaction Summer Research School
Apr 30, 2022 Accepted offer to join Design Lab @ UC San Diego as Postdoc!
Apr 29, 2022 @ CHI 2022 (New Orleans) until May 6 (Fri) - Let’s connect!
Apr 27, 2022 Talk @ Google - “Creating Opportunities to Move Up and Down the Ladder of Abstraction”: Generating Comics from Code with Story Ideation, Auto Comic Generation, and Generative AI

selected publications [full list]

  1. DIS Best Paper
    Honorable
    Mention Award
    PrivacyToon: Concept-driven Storytelling with Creativity Support for Privacy Concepts 🎖
    Suh, Sangho, Lamorea, Sydney, Law, Edith, and Zhang-Kennedy, Leah
    In ACM SIGCHI Conference on Designing Interactive Systems (DIS) 2022
  2. IUI
    Leveraging Generative Conversational AI to Develop a Creative Learning Environment for Computational Thinking
    Suh, Sangho, and Pengcheng, An
    In 27th Annual Conference on Intelligent User Interfaces (IUI) 2022
  3. SIGCSE
    Using Comics to Introduce and Reinforce Programming Concepts in CS1
    Suh, Sangho, Latulipe, Celine, Lee, Ken Jen, Cheng, Bernadette, and Law, Edith
    In ACM Technical Symposium on Computer Science Education SIGCSE 2021
  4. VL/HCC
    Coding Strip: A Pedagogical Tool for Teaching and Learning Programming Concepts through Comics
    Suh, Sangho, Lee, Martinet, Xia, Gracie, and Law, Edith
    In IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) 2020
  5. CHI
    Curiosity Notebook: A Platform for Learning by Teaching Conversational Agents
    Law, Edith, Baghaei Ravari, Parastoo, Chhibber, Nalin, Kulic, Dana, Lin, Stephanie, Pantasdo, Kevin D, Ceha, Jessy, Suh, Sangho, and Dillen, Nicole
    In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems 2020
  6. NIPS
    Re-VACNN: Steering Convolutional Neural Network via Real-time Visual Analytics
    Chung, Sunghyo, Park, Cheonbok, Suh, Sangho, Kang, Kyeongpil, Choo, Jaegul, and Kwon, Bum Chul
    In Future of interactive learning machines workshop at the 30th annual conference on neural information processing systems (NIPS) 2016
  7. ICDM Best Student
    Paper Award
    L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization 🏆
    Suh, Sangho, Choo, Jaegul, Lee, Joonseok, and Reddy, Chandan K
    In 2016 IEEE 16th International Conference on Data Mining (ICDM) 2016