28 Google search and ranking patents by Trystan Upstill. Co-inventor on the Panda patent (US 9,135,307 = 65gp pat-39) and lead inventor on the HCU-era follow-up US App 2019/0155948 "Re-ranking resources based on categorical quality" — the patent that anchors the post-Panda site-quality lineage. Also covers authoritative-results discovery, search-result ranking and re-scoring, affiliated-domains detection, resource-attribute extraction from site address, local search and POI identification, synonyms and query rewriting, navigational-intent resources, language identification from link context, and the recent LLM-era UI components patent. Filings 2012-2026.
About the Trystan Upstill, Google Site-Quality & HCU-Era Search Patents track
28 Google search and ranking patents by Trystan Upstill. Co-inventor on the Panda patent (US 9,135,307 = 65gp pat-39) and lead inventor on the HCU-era follow-up US App 2019/0155948 "Re-ranking resources based on categorical quality" — the patent that anchors the post-Panda site-quality lineage. Also covers authoritative-results discovery, search-result ranking and re-scoring, affiliated-domains detection, resource-attribute extraction from site address, local search and POI identification, synonyms and query rewriting, navigational-intent resources, language identification from link context, and the recent LLM-era UI components patent. Filings 2012-2026.
Site Quality & Authority (HCU Lineage)
- Selectively Generating Alternative Queries (Panda) (US 9,135,307 · September 15, 2015)
- Re-ranking Resources Based on Categorical Quality (US App 2019/0155948 · May 23, 2019)
- Obtaining Authoritative Search Results (US 9,659,064 · May 23, 2017)
- Ranking Search Results (US 9,454,582 · September 27, 2016)
- Selectively Ranking Search Results (US 9,442,990 · September 13, 2016)
- Resource Identification from Organic and Structured Content (US 9,589,028 · March 7, 2017)
- Search Operation Adjustment and Re-Scoring (US 10,339,144 · July 2, 2019)
- Identifying Affiliated Domains (US 9,178,848 · November 3, 2015)
- Determining Resource Attributes from Site Address Attributes (US 8,600,993 · December 3, 2013)
Navigational, Language ID & Local Search
- Navigational Resources for Queries (US 9,213,774 · December 15, 2015)
- Navigational Resources for Queries (continuation 2019) (US 10,204,138 · February 12, 2019)
- Identifying Document Languages Using Link Context (US 9,098,582 · August 4, 2015)
- Identifying Document Languages (continuation 2019) (US 10,223,461 · March 5, 2019)
- Identifying Points of Interest (US 8,239,130 · August 7, 2012)
- Identifying Points of Interest (2013) (US 8,433,512 · April 30, 2013)
- Identifying Points of Interest (2013b) (US 8,620,579 · December 31, 2013)
- Identifying Implicitly Local Queries (US 8,200,694 · June 12, 2012)
- Encoding Distances Between Locations (US 8,495,046 · July 23, 2013)
- Geographic Synonyms (US 8,417,721 · April 9, 2013)
Synonyms, Query Rewriting & LLM-Era UI
- Restricted-Locality Synonyms (US 8,719,282 · May 6, 2014)
- Lexical Synonyms (US 9,183,297 · November 10, 2015)
- Query Correction (US 9,378,272 · June 28, 2016)
- Related Terms Across Languages (US 8,798,988 · August 5, 2014)
- Phrase Restricted Substitute Terms (US App 2015/0205866 · July 23, 2015)
- Locally Significant Queries (US App 2014/0172843 · June 19, 2014)
- Co-Occurrence Based List Extraction (US 8,285,738 · October 9, 2012)
- Co-Occurrence List Extraction (2016) (US 9,239,823 · January 19, 2016)
- Using Language Models to Generate User Interface Components (WO 2026/072958 · April 2, 2026)
Why this inventor matters
Each inventor track inside the Nizam SEO War Room patents archive isolates one engineer's research arc — typically a decade or more of continuations, divisionals, and follow-up patents on a coherent research thread. Reading by inventor (rather than by topic) recovers the narrative: how the original disclosure evolved, what the continuations added, which claims got carved out into divisional applications, and how the thread eventually intersected with other research lines at Google or Microsoft. This is how working SEOs build durable intuition about search-engine internals — not by memorizing claim language, but by following the research bibliography that shipped the algorithms we now optimize against.
How to read this track
Start with the earliest filing — it sets the foundational disclosure. Continuations refine the claims; divisional applications split out separable inventions; the follow-up patents tend to introduce performance optimizations, edge-case handling, or downstream integration with other systems. Each patent on this site is annotated with the ranking surface it touches — query understanding, document retrieval, ranking, behavioral signals, knowledge graph, or AI search — so the practitioner can map the research back to the algorithm output observed on live SERPs.