Han Xiao Research by SuperAGI

Executive Summary

Dr. Han Xiao is the Founder and CEO of Jina AI, a Berlin-based technology company specializing in open-source neural search, multimodal AI, and scalable embedding solutions. Recognized as an influential open-source evangelist and AI thought leader, Xiao is renowned for his hands-on technical vision, entrepreneurial acumen, and strong presence in global AI and open-source communities.

Professional Background

Current Role: CEO & Founder, Jina AI

Position: Chief Executive Officer & Founder (2020–present)

Company: Jina AI – Berlin, Germany

LinkedIn: [Han Xiao](http://www.linkedin.com/in/hxiao87)

Mission: Deliver an open-source neural search ecosystem supporting state-of-the-art AI applications, ranging from text, image, voice, and multimodal search to large-scale retrieval-augmented generation (RAG), leveraging robust embeddings and reranking models.

Previous Experience

Tencent AI Lab (Shenzhen, China): Led the neural information retrieval team, building next-generation search infrastructure for WeChat, a widely used application in China.

Zalando Research (Berlin, Germany): Senior Research Scientist (2014–2018), focused on distributed machine learning and data mining.

Education

Ph.D., Computer Science – Technische Universität München, 2014

M.Sc., Computer Science – Technische Universität München, 2011

Achievements & Thought Leadership

Company Growth & Fundraising

Founded Jina AI in 2020; since then, has raised over $38 million in funding ([TechCrunch](https://techcrunch.com/2021/11/22/jina-ai-raises-30m-for-its-for-its-neural-search-platform/), [Eventible](https://www.eventible.com/speakers/profile/han-xiao-5916)), including a $30 million funding round in late 2021.

Built Jina AI into a platform with an extensive open-source footprint, evidenced by 247+ public repositories, a large developer community, and strong advocacy within the AI open-source ecosystem.

Technical Innovations & Open Source

jina-embeddings-v2 & v3: Led Jina AI to launch the world’s first open-source 8,192-token text embedding models ("jina-embeddings-v2" in 2023), directly rivaling proprietary offerings from leading AI companies ([Marktechpost](https://www.marktechpost.com/2023/11/01/jina-ai-introduces-jina-embeddings-v2-the-worlds-first-8k-open-source-text-embedding-models/), [Analytics India Mag](https://analyticsindiamag.com/ai-news-updates/jina-ai-launches-open-source-8k-text-embedding-rivalling-openai/)).

DocumentArray: Pioneered this library for handling unstructured, multimodal data, now integrated with industry document stores (e.g., Weaviate).

Prompt-based and embedding-based innovations: Jina’s 2023/2024 strategy has focused on these as dual pillars—reflected in technical yearbooks and product releases.

Fashion-MNIST & bert-as-service: Xiao’s open-source projects have gained widespread adoption (listed among the most popular global AI projects in 2017–2018).

DALL-E Flow: Developed human-in-the-loop AI workflows for high-definition text-to-image generation.

Industry Recognition

Open Source Community Leadership: Active contributor to the Linux Foundation, program committee member for Open Source Summit North America (2023).

Featured in "TensorFlow Titans: Best Developers in 2025," highlighting persistent involvement in deep learning frameworks and open-source tooling.

Regular speaker, podcast guest, and interviewee at leading AI forums (AI Berlin, MIT Technology Review, Rise of AI, Weaviate Podcast, etc.).

Media presence as an authority on multimodal AI, scalable search, and the intersection of open source & enterprise AI.

Product & R&D Focus

Jina AI’s flagship offerings under Han Xiao’s leadership:

Neural/semantic search platforms: Cloud-native, open source, and designed for multimodal data (text, images, etc.). Emphasis on high performance, developer-friendliness, and rapid prototyping.

Large-scale embedding models: Open-source alternatives for long-context (8K token and above) requirements, supporting retrieval-augmented generation and enterprise-scale use cases.

Tools for developers: More than 247 open-source projects, including end-to-end pipelines for prompt engineering, embedding finetuning, and human-in-the-loop workflows.

Active Research and Replication: Demonstrated capability to quickly replicate and release open-source versions of proprietary research (e.g., replicating OpenAI’s Deep Research within hours of release in February 2025).

Strategic Vision and Market Position

Transformative Value Creation: Focused on using AI to generate business value via cost optimization and innovation acceleration.

Open-Source First Approach: Positions Jina AI as a democratizing force in AI, lowering barriers for enterprises and the developer community.

Multimodal & Multilingual: Products are designed to work across text, images, and other data types—recognized as an emerging imperative for next-gen enterprise AI.

Technical & Commercial Agility: Proactive response to leading market trends is evident—e.g., adopting LLMs/RAG, scaling models for industrial performance, and supporting latest prompt/embedding techniques.

Global Outreach: While headquartered in Berlin, Jina AI's work—mirroring Xiao’s career—straddles European and Chinese ecosystems. There are indications of possible US expansion due to regulatory reasons.

Selected Publications & Technical Content

A prolific writer and curator, Han Xiao has contributed to:

Jina AI’s Yearbooks: Annual technical curations summarizing key models, achievements, and technical deep-dives (2024 yearbook: 14 flagship technical articles, 160+ pages).

Peer-reviewed contributions: Publications and cited work in information retrieval, NLP, and AI (Google Scholar, arXiv, OpenReview).

Industry Articles: Thought pieces on prompt engineering, AGI prospects, and practical R&D (e.g., insights into ColBERT, late interaction techniques, prompt/embedding scalability).

Notable Activities, Interests, and Engagement

Community-building: Coordinates all-hands meetings, hackathons, and open community events to foster rapid collaboration and new project launches.

Mentorship & Recruitment: Frequently posts about hiring research interns/fellows focused on embeddings, retrieval, and lightweight LLMs.

Continuous Technical Visibility: Regularly publishes benchmarks, blog posts, and LinkedIn/X threads explaining AI concepts, industry trends, and practical deployment experiences.

Contact & Additional Profiles

LinkedIn: [linkedin.com/in/hxiao87](http://www.linkedin.com/in/hxiao87)

Personal Blog: [hanxiao.io](https://hanxiao.io/about/)

Jina AI Website: [jina.ai](https://jina.ai/)

Google Scholar: [Han Xiao](https://scholar.google.com/citations?user=jp7swwIAAAAJ&hl=en)

OpenReview: [Han Xiao's profile](https://openreview.net/profile?id=~Han_Xiao8)

Key Takeaways for Strategic Outreach

Dr. Han Xiao is an engineering-centric executive with hands-on technical orientation, proven open-source community leadership, and a commitment to transformative AI innovation.

Jina AI is at the convergence of enterprise search, LLM-based retrieval, embeddings, and multimodal AI—actively competing with and responding to industry leaders.

Xiao’s interests and strategy signal high receptivity to collaborations in AI infrastructure, enterprise RAG/developer tooling, open research, and AI democratization.

For engagement, frame value in terms of engineering excellence, technical partnership, R&D collaboration, and a mutual drive to push the boundaries of open, scalable, and real-world AI.