Connor Shorten
Connor Shorten is an AI researcher whose work spans deep-learning education, data augmentation, and information retrieval. In 2019, he studied AI at Florida Atlantic University and created Henry AI Labs videos that explained deep-learning papers. By 2022, he was a Product Researcher at Weaviate and coauthored an FAU paper on consistency learning with data augmentation. In January 2023, he hosted the Weaviate Podcast with 34 published episodes; his 2024–2026 papers examined structured language-model outputs, database queries, and visual retrieval over scientific papers. As of October 2026, he is a Product Researcher at Weaviate.
Timeline
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2019
PhD research at FAU
In 2019, he studies AI at Florida Atlantic University as a PhD researcher.
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2019
Henry AI Labs explainers
In 2019, he creates Henry AI Labs videos that explain deep-learning papers.
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2022
Product research and augmentation
In 2022, he is a Product Researcher at Weaviate and coauthors an FAU paper on consistency learning with data augmentation.
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January 2023
Hosting the Weaviate Podcast
In January 2023, he hosts the Weaviate Podcast, which has 34 published episodes.
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August 2024
StructuredRAG benchmark
In August 2024, he coauthors StructuredRAG, a six-task benchmark that tests whether language models follow structured response formats such as JSON.
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January 2025
Database function calling
In January 2025, he coauthors a paper that defines a tool interface for language models to query databases with search, filters, aggregation, and groupby operations.
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February 2026
IRPAPERS retrieval benchmark
In February 2026, he coauthors IRPAPERS, a benchmark of 3,230 pages from 166 scientific papers for comparing image-based and text-based retrieval and question-answering systems.
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As of October 2026
Product Researcher at Weaviate
As of October 2026, he is a Product Researcher at Weaviate. In August 2026, he writes about scaling test-time compute for retrieval and Query Agent Search Mode.
Career
- Since 2022WeaviateProduct Researcher
Education
- From 2019Florida Atlantic UniversityPhD
Sources and credits
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- GANs, CNN Architectures, Deep Learning on Graphs and Henry AI Labs with Connor Shorten || TAIWS #6
- Weaviate 1.15 release
- An Exploration of Consistency Learning with Data Augmentation
- Weaviate Podcast Search
- StructuredRAG: JSON Response Formatting with Large Language Models
- Querying Databases with Function Calling
- IRPAPERS: A Visual Document Benchmark for Scientific Retrieval and Question Answering
- Authors | Weaviate
- Scaling Test-Time Compute in Search Mode



