ACM CHI Topic Selection & Subcommittee Routing

•
1.1k
•

Evaluates research projects for ACM CHI scope, identifies primary contribution types, and recommends optimal PCS reviewing subcommittees and alternative HCI venues.

CHI Topic Selection is a strategic research framing skill designed to help HCI authors evaluate paper fit before drafting starts. By auditing human-centered stakes, classifying research into standard ACM CHI contribution types, and applying a rigorous 3-point subcommittee fit test, it helps researchers avoid desk rejects and misaligned reviewer assignments. The skill also analyzes paper scope to recommend targeted sibling venues—including UIST, CSCW, DIS, IUI, ASSETS, IMWUT, and TOCHI—saving researchers from costly 12-month review cycle delays.

主な機能

01Runs structured fit tests to recommend primary and secondary PCS reviewing subcommittees
021,074 GitHub stars
03Detects early rejection anti-signals including missing community context and decorated studies
04Evaluates alternative HCI venue routing (UIST, CSCW, DIS, IUI, ASSETS, IMWUT, TOCHI)
05Identifies and validates the human-centered stake and primary CHI contribution type
06Provides standardized decision briefs with target word counts and blocking gap resolutions

ユースケース

01Deciding whether an early-stage HCI project belongs at ACM CHI or a specialized sibling conference
02Selecting primary and secondary PCS subcommittees to ensure aligned reviewer expertise
03Reframing system or empirical research to prevent scope mismatches and desk rejection