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Michelle Kim

dblp:41/1381 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0003-2577-6876ORCID · reported

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

Artificial intelligence and machine learning · 2 · 1 since 2021Software engineering, systems software and programming languages · 1Human-computer interaction and ubiquitous computing · 1 · 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.

Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 56% Human-AI interaction · 28% Design research and methods · 17%
Artificial intelligence
1 paper
Deep learning architectures and training · 100%
Theoretical computer science
1 paper
Computational complexity · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing
children's collaboration
1.012026
Generative AI in Children's Creative Collaboration: Impact, Perception, and Design Guidelines · CHI 2026
Collaborative and social computing
creative collaboration
1.012026
Generative AI in Children's Creative Collaboration: Impact, Perception, and Design Guidelines · CHI 2026
Human-AI interaction
generative AI
1.012026
Generative AI in Children's Creative Collaboration: Impact, Perception, and Design Guidelines · CHI 2026
Machine learning › Deep learning architectures and training
transformer
0.712023
Provable Memorization Capacity of Transformers · ICLR 2023
Design research and methods › participatory design
co-design with children
0.312026
Generative AI in Children's Creative Collaboration: Impact, Perception, and Design Guidelines · CHI 2026
Design research and methods
participatory design
0.312026
Generative AI in Children's Creative Collaboration: Impact, Perception, and Design Guidelines · CHI 2026

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

provable analysis · 1.3focus group interview · 1.0co-design sessions · 1.0
YearPublicationVenuePosition
2026 Generative AI in Children's Creative Collaboration: Impact, Perception, and Design Guidelines
abstract
The advent of Generative AI (GenAI) has raised discussions about its effects on individuals. However, little is known about its impact on children’s creative collaboration, despite its importance for social and cognitive development. We examined GenAI’s role in children’s creative collaboration through five co-design sessions with 28 children (ages 5-11) using diverse GenAI tools (text, image, video, voice); 17 parents participated in focus group interviews. Our findings show that GenAI can foster positive social dynamics by enabling “Human vs. AI” teaming and children’s co-creation with shared ownership. However, GenAI disrupted collaborations when roles between children were unclear, AI ignored group dialogue, and AI dominated children’s agency. Children and parents envisioned socially attuned AI that could play an “older sibling” role–scaffolding while allowing playful disagreement–while raising concerns about children’s overreliance on GenAI. This work advances understanding of GenAI in collaboration and proposes design implications for designing AI systems that support child-centered collaboration.
Daeun Yoo, Michele Newman, Caroline Pitt, Kevin Huu Vo, Michelle Zhang, Michelle Kim, Katie Davis 0001, Jason C. Yip 0001
CHI6
2023 Provable Memorization Capacity of Transformers
Michelle Kim, Barzan Mozafari
ICLR2
1996 Expertsheets: A Spreadsheet Paradigm for Authoring Expert Systems
Francisco Corella, Michelle Kim
SEKE2