Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
3Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5048975423
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- A. B. Kahng (openalex, provider refresh)
- Andrew B. Kahng (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Innovation: 1 paper
- Productivity: 1 paper
Claim outcomes
- Research Productivity: 1 paper
- Adoption Rate: 1 paper
- Developer Productivity: 1 paper
- Innovation Output: 1 paper
- Organizational Efficiency: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Agentic AI could speed chip and physical-design R&D by automating workflow, heuristic discovery and tool use; current evidence is promising but largely limited to prototypes, benchmark fragments and lab demonstrations.semantic_scholar | Andrew B. Kahng provider id |
Fetched 2026-04-23 | 1 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.