Nanotechnology×Convolutional neural network
This pair ranks in the top 0.1% of every collision candidate in the corpus. Across held-out years, pairs scoring that well went on to co-publish at 10.0× the base rate, typically within 2 years.
The Frontier Brief for this collision is still being written. The evidence below already reflects the current model run.
Pre-company space. No named players have staked this collision yet — an emerging pairing where the field, not a firm, is the story so far.
37 researchers publish on both sides of this collision without the fields themselves having met. Every name below is counted from papers in the corpus — not inferred.
- J. Joshua YangTorrington Hospital6/2
- Zhongrui WangInstitute for Basic Science7/1
- Xiaodong ChenRIKEN6/1
- Sjors H. W. ScheresNIHR Cambridge Biomedical Research Centre4/1
- Dirk EnglundPalacký University Olomouc4/1
- Huaqiang WuTsinghua University4/1
- Changjin WanSoochow University3/1
- Mingyi RaoFudan University3/1
- Sungwoo JungInha University2/1
- Ru HuangPeking University Shenzhen Hospital2/1
- Chinese Academy of SciencesCN524/22
- Stanford UniversityUS360/18
- Massachusetts Institute of TechnologyUS378/16
- Tsinghua UniversityCN353/15
- Nanyang Technological UniversitySG340/15
- Harvard UniversityUS352/11
- Fusion Deep Learning for Predicting Conductivity in Electron-Doped Organic Polymers2025 · 3 citations · DOI ↗2
- Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride2019 · 139 citations · DOI ↗1
- A Learning Framework for Atomic-Level Polymer Structure Generation2025 · 7 citations · DOI ↗3
- Rethinking the Inception Architecture for Computer Vision2016 · 31,365 citations · DOI ↗2
Counted from the corpus. Institution counts use best-effort affiliation (every author on a paper is paired with every institution on it), so read them as presence, not headcount.
A premium Deep-Dive is being generated for this collision — check back soon.