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Sebastian Stein | Researcher on shared autonomy and intelligent agents, spanning HCI, ubiquitous computing and machine learning. — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
hsg.ai ↗	71 match 1 shared topics	HSG-AIML \| Research activities at the chair Artificial Intelligence & Machine Learning at the Institute of Computer Science of the University of St. Gallen.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
gburi.dev ↗	71 match 1 shared topics	H. Gburi \| AI/ML Researcher & Computational Intelligence	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
skimai.com ↗	70 match 1 shared topics	Skim AI - Machine Learning and Artificial Intelligence Solutions	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
sitianlu.com ↗	69 match 1 shared topics	Sitian Lu \| Staff Machine Learning Engineer	United States~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
bifold.berlin ↗	69 match 1 shared topics	BIFOLD Berlin - Big Data Management and Machine Learning	en	artificial-intelligence TYPO3	robotsllmsaihumans	emailphone	none
automl.info ↗	68 match 1 shared topics	Information about Automated Machine Learning (AutoML) - AutoML	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
causalmlbook.com ↗	68 match 1 shared topics	Causal Inference and Machine Learning: In Economics, Social, and Health Sciences	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
siteagentify.com ↗	68 match 1 shared topics	SiteAgentify - Build Intelligent AI Agents	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
gareginmazmanyan.com ↗	68 match 1 shared topics	Garegin Mazmanyan - AI/Machine Learning Engineer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
liuzhiyuan1225.com ↗	68 match 1 shared topics	The latest in Machine Learning \| Papers With Code	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vontobel.dev ↗	68 match 1 shared topics	Tobias Vontobel - Machine Learning Engineer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
autonomous-fox.ai ↗	68 match 1 shared topics	Autonomous-Fox Laboratories \| machine learning lab financial artificial intelligence	en	artificial-intelligence Wix	robots llmsaihumans	emailphone	none
atconversaai.com ↗	68 match 1 shared topics	AI Agents & Intelligent Automation for Every Industry \| Conversa	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
atconversa.com ↗	68 match 1 shared topics	AI Agents & Intelligent Automation for Every Industry \| Conversa	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
intellektai.com ↗	68 match 1 shared topics	Machine Learning Development Company - Intellekt AI	en	artificial-intelligence Sanity	robotsllmsaihumans	emailphone	none
intellica.ai ↗	68 match 1 shared topics	Intellica.AI – Enterprise AI \| Machine Learning Applications \| Unstructured Data Analytics	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
netgv.ai ↗	68 match 1 shared topics	NETGV AI — Agentic AI & Intelligent Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
inticore.ai ↗	67 match 1 shared topics	Inticore \| AI Integration, Custom Development & Machine Learning	en	artificial-intelligence	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.