Building AI models that understand chemical principles
Connor Coley is an MIT Associate Professor working at the intersection of chemistry and machine learning to discover new drug compounds. His research focuses on using AI to analyze vast numbers of chemical compounds and predict reaction pathways. Coley believes that this approach can significantly enhance small-molecule drug discovery.
- ▪Coley's research aims to identify potential drug candidates among an estimated 1020 to 1060 chemical compounds.
- ▪He combines chemical engineering and computer science to develop computational models for drug discovery.
- ▪Coley's background includes a strong family influence in science and a diverse educational path in chemical engineering and computer science.
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Story provenance
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Record
| Original publisher | MIT News |
| Canonical URL | https://news.mit.edu/2026/building-ai-models-with-chemical-principles-connor-coley-0520 |
| Publication time | Wed, 20 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-20T04:09:59.478Z |
| Last seen | 2026-05-20T04:09:59.478Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | ZLSL_LYq38zo |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds. Anne Trafton | MIT News Publication Date: May 20, 2026 Press Inquiries Press Contact: Sarah McDonnell Email: [email protected] Phone: 617-253-8923 Fax: 617-258-8762 MIT News Office Media Download ↓ Download Image Caption: “MIT is a very special place in terms of the resources and the fluidity across departments,” says Connor Coley. Credits: Photo: Gretchen Ertl *Terms of Use: Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license. You may not alter the images provided, other than to crop them to size.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at MIT News.