Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to nihalpotdar.com

Nihal Potdar - Research Engineer · ranked by shared content topics & relevance
76match
nflei.com
Noah Fleischmann — Research Engineer
2 shared topicsartificial-intelligence
76match
dlobaton.com
Daniel Lobaton — Research Engineer
2 shared topicsartificial-intelligence
73match
adrianlaynez.dev
Adrián Laynez | Research & Engineering
2 shared topicsartificial-intelligence
72match
rohanmitra.dev
Rohan Mitra | ML Engineer & Researcher
2 shared topicsartificial-intelligence
71match
abdullahchoudhry.com
Abdullah Tariq Choudhry | Software Engineer & ML Researcher
2 shared topicsartificial-intelligence
71match
ashfakshibli.com
Ashfak Md Shibli - Software Engineer & Researcher
2 shared topicstechnology-and-computing
71match
rohitraju.com
Rohit Raju, AI Engineer, researcher & creator
2 shared topicsartificial-intelligence
70match
anirudh.me
Anirudh Sharma — Inventor, Researcher, Engineer
2 shared topicstechnology-and-computing
70match
gtparag.com
Parag Ambildhuke | Software Engineer & ML Researcher
2 shared topicsartificial-intelligence
70match
rominur.com
Romi Nur Ismanto — AI Engineer & Researcher | Jakarta
2 shared topicsartificial-intelligence
70match
aspectresearch.org
Aspect Research
2 shared topicsartificial-intelligence
70match
ahrensalazar.dev
Ahren Salazar | Software Engineer & Researcher
2 shared topicsartificial-intelligence
70match
kuriko-iwai.com
Kernel Labs by Kuriko IWAI - ML Engineering & Research
2 shared topicsartificial-intelligence
69match
rohanmarwaha.com
Rohan Marwaha | Research Software Engineer at NCSA | AI Engineer
2 shared topicsartificial-intelligence
69match
aiengineerhq.org
AI Engineer HQ
2 shared topicsartificial-intelligence
69match
felisawiley.com
Felisa "Fee" Wiley | Data Engineer, Researcher & Author
2 shared topicstechnology-and-computing
69match
ai-researchstudies.com
AI Researcher
2 shared topicsartificial-intelligence
69match
bencevans.io
Ben Evans - Software Engineer and Machine Learning Researcher
2 shared topicsartificial-intelligence

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:

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.