arXiv subjects

Joohee Choi

Publications and source records attributed to Joohee Choi.

2 recordsLinked to original sources

arXiv2026

"A Space Where I Can Be Myself": Exploring Safe Visibility for Graduate Student Mothers in Mom Cafes

Graduate student mothers navigate intertwined demands of graduate study and caregiving, yet little is known about how they seek support through online communities. We examine this through Mom Cafes, locally based online parenting communities in South Korea. Drawing on focus group interviews and design workshops with 22 graduate student mothers, we identify a pattern of dual invisibility: caregiving circumstances were difficult to make legible in academic contexts, while academic circumstances were difficult to make legible in parenting contexts. Although Mom Cafes offered useful local information and emotional reassurance, concerns specific to graduate student motherhood were harder to articulate or safely disclose. Participants sought ways to make graduate student motherhood recognizable when relevant, but their designs highlighted tensions around identifiability, judgment, relational burden and accountability. We conceptualize these tensions as safe visibility and discuss infrastructures for selective recognition, low-obligation connection, and accountable pathways to practical care.

cs.SI↗

arXiv2026

A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

Coarse-grained (CG) molecular dynamics extends polymer simulation beyond the scales accessible to all-atom (AA) methods, but bottom-up CG modeling is laborious. The CG resolution is a design choice, so a transferable parameter set is generally not available and the potentials are derived anew for each polymer mapping. Here we present CGMas, a multi-agent framework that automates topology construction, equilibration, mapping, potential derivation, and validation from a natural-language specification of the polymer and target resolution. A large-language-model (LLM) reasoning agent infers the AA topology from polymer name, while layered self-correction resolves physical errors common to unsaturated, heteroatom-containing, and polar polymers. Downstream agents equilibrate the system, map it onto CG representation, derive potentials through Boltzmann inversion, and benchmark the model against its atomistic reference. CGMas completed all 27 homopolymer and copolymer tasks, matched the AA density to within 5% in 22, and reduced simulation from 38-88 min to 1 min, establishing agentic LLMs as a route to automated polymer coarse-graining.

cs.AI↗