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Hansol Lim

dblp:371/5685 · DBLP profile ↗
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5ranked-venue papers
5as first author
5since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 4 · 4 first-author · 4 since 2021Artificial intelligence and machine learning · 3 · 3 first-author · 3 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Computing education · 100%
Artificial intelligence
1 paper
Face, body and person analysis · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education › AI education
K-12 AI education
1.622025
Shaping AI Interest in Rural Middle Schools with Unplugged Learning: Gender Differences and Teacher Insights · AAAI 2025
Unplugged K-12 AI Learning: Exploring Representation and Reasoning with a Facial Recognition Game · AAAI 2024
Computer vision › Face, body and person analysis
face recognition
0.212024
Unplugged K-12 AI Learning: Exploring Representation and Reasoning with a Facial Recognition Game · AAAI 2024

Methods — techniques the papers use, named apart from their topics

survey study · 0.9classroom study · 0.9
YearPublicationVenuePosition
2026 PRISM: Color-Stratified Point Cloud Sampling
Hansol Lim, Minhyeok Im, Jongseong Choi 0001
ICPR (10)1
2025 Shaping AI Interest in Rural Middle Schools with Unplugged Learning: Gender Differences and Teacher Insights
abstract
Adoption of artificial intelligence (AI) is at an inflection point. With daily use of AI escalating due to widely available software tools, educators, researchers, and policymakers must adapt swiftly to changing educational needs. While think tanks and Big Tech companies often promote the notion that AI serves as a powerful tool for democratizing access to knowledge and opportunities, our work in rural communities underscores the disparity in access to AI education and related opportunities. In this paper, we report on our experience introducing foundational AI concepts to rural middle school students using an unplugged game-based learning activity. By providing engaging learning experiences to rural populations, we hope to broaden interest in and understanding of AI technologies. To this end, we conducted a classroom study in which two middle school teachers implemented our unplugged AI learning activity with their students. Analyzing survey data from 60 of the participating students, we explore the impact of the activity on their interest in AI, their conceptual understanding, and examine potential gender differences. Additionally, we share insights from the teachers who participated in our professional development sessions in preparation for the classroom implementations.
Hansol Lim, Danielle Boulden, Jessica Vandenberg, Veronica Cateté, Wookhee Min, Bradford W. Mott
AAAI1
2025 LiDAR-3DGS: LiDAR reinforcement for multimodal initialization of 3D Gaussian Splats
Hansol Lim, Hanbeom Chang, Jongseong Choi 0001, Chul Min Yeum
Comput. Graph.1
2024 Unplugged K-12 AI Learning: Exploring Representation and Reasoning with a Facial Recognition Game
abstract
With the growing prevalence of AI, the need for K-12 AI education is becoming more crucial, which is prompting active research in developing engaging and age-appropriate AI learning activities. Efforts are underway, such as those by the AI4K12 initiative, to establish guidelines for organizing K- 12 AI education; however, effective instructional resources are needed by educators. In this paper, we describe our work to design, develop, and implement an unplugged activity centered on facial recognition technology for middle school students. Facial recognition is integrated into a wide range of applications throughout daily life, which makes it a familiar and engaging tool for students and an effective medium for conveying AI concepts. Our unplugged activity, “Guess Whose Face,” is designed as a board game that focuses on Representation and Reasoning from AI4K12’s 5 Big Ideas in AI. The game is crafted to enable students to develop AI competencies naturally through physical interaction. In the game, one student uses tracing paper to extract facial features from a familiar face shown on a card, such as a cartoon character or celebrity, and then other students try to guess the identity of the hidden face. We discuss details of the game, its iterative refinement, and initial findings from piloting the activity during a summer camp for rural middle school students.
Hansol Lim, Wookhee Min, Jessica Vandenberg, Veronica Cateté, Bradford W. Mott
AAAI1
2024 Supporting Student Engagement in K-12 AI Education with a Card Game Construction Toolkit
abstract
With the growing prevalence of AI, the need for K-12 AI education is becoming more crucial, which is prompting active research in developing engaging AI learning activities. In this paper, we present our work on a game construction toolkit for middle school students and educators that enables them to tailor an AI-focused unplugged card game activity. In our prior work, we designed, developed, and piloted an unplugged card game activity where players predict the identity of a person based on hand-drawn features extracted from a set of facial cards. The activity aims to teach AI concepts aligned with one of the big ideas in AI utilizing techniques from facial recognition. During our pilot testing of the activity, we discovered that creating face cards that capture students' interest is a crucial factor in promoting student engagement. As a result, we designed a card game construction toolkit that allows students and educators to craft their own face card decks using photos that are personally interesting to them, looking to foster engagement and improve replayability of the activity. The toolkit's design is focused on ensuring easy accessibility and features a simple web-based interface that allows users to download and print their customized cards. We expect this toolkit will enhance the usability and educational effectiveness of our unplugged K-12 AI education activity.
Hansol Lim, Wookhee Min, Jessica Vandenberg, Veronica Cateté, Judith Uchidiuno, Bradford W. Mott
SIGCSE (2)1