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James Stevens, Ph.D. | Researcher | Computer Scientist | Applied Mathematician | Retail Investor at large — 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 Technology And Computing →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
csiseverywhere.org ↗	66 match 1 shared topics	csiseverywhere (@csiseverywhere) \| Computer Science is Everywhere	en	technology-and-computing	robots llmsaihumans	emailphone	none
bpbonline.com ↗	66 match 1 shared topics	Buy Information Technology, Coding & Computer Science Books Online – BPB Online	en	technology-and-computing Shopify	robots llmsaihumans	emailphone	none
csse-journal.org ↗	66 match 1 shared topics	International Journal of Computer Systems Science and Engineering	en	technology-and-computing	robotsllmsaihumans	emailphone	none
cshdevs.org ↗	66 match 1 shared topics	Computer Science Hub \| CSH	en	technology-and-computing	robotsllmsaihumans	emailphone	none
sciconvertpro.com ↗	65 match 1 shared topics	SciConvert Pro \| Free Scientific Document Conversion Tools for Researchers	en	technology-and-computing	robotsllmsaihumans	emailphone	none
ctang.dev ↗	65 match 1 shared topics	Charles Tang \| Software Engineer & Computer Science Student	en	technology-and-computing	robotsllmsaihumans	emailphone	partial · 8
sayemsarkar.com ↗	65 match 1 shared topics	Sayem Sarkar – CEO at AIEDGE \| Researcher \| Entrepreneur \| Writer \| Science Communicator \| Web Developer \| Domain Investor \| Cybersecurity Consultant \| Voice Artist \| Shaping the Future of the World	en	technology-and-computing WordPress WooCommerce	robotsllmsaihumans	emailphone	none
cyberia.club ↗	65 match 1 shared topics	Cyberia Computer Club	en	technology-and-computing	robotsllmsaihumans	emailphone	none
larrywigington.com ↗	65 match 1 shared topics	Larry Wigington \| Operations Research Scientist & USMC Lieutenant Colonel	en	technology-and-computing	robotsllmsaihumans	emailphone	none
felixdietrich.com ↗	65 match 1 shared topics	Felix T.J. Dietrich \| Researcher & Software Engineer	Germany~ en	technology-and-computing	robots llmsaihumans	emailphone	full · 18
sangammulmi.com ↗	65 match 1 shared topics	Dr. Sangam Mulmi \| Homepage	en	technology-and-computing	robotsllmsaihumans	emailphone	none
mcglo.dev ↗	65 match 1 shared topics	Neil McGlohon - Research Scientist	United States~ en	technology-and-computing	robotsllmsaihumans	emailphone	none
cschamp.com ↗	65 match 1 shared topics	Master computer science step by step	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
frankrobben.be ↗	65 match 1 shared topics	Frank Robben – computer scientist, lawyer, civil servant & lecturer	Belgium en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
cscs.dev ↗	65 match 1 shared topics	College Station Computer Science	en	technology-and-computing	robotsllmsaihumans	emailphone	none
scotherd.com ↗	65 match 1 shared topics	ScotHERD – The Community of Practice for HE Researcher Developers in Scotland	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
blackincomputing.org ↗	65 match 1 shared topics	An Open Letter & Call to Action to the Computing Community from Black computer scientists and our allies	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
blocksquawk.io ↗	64 match 1 shared topics	BlockSquawk - Quantum Computing & Blockchain Research	en	technology-and-computing	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.