Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-En
Machine learning (ML) models deployed in sensitive domains such as healthcare, law enforcement, and finance must satisfy not only utility requirements but also fairness and privacy guarantees. While prior work has largely examined how priva
https://arxiv.org/abs/2607.14607v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
None
How close the company’s idea is to your thesis statement
Sector
ai
Overlap with sectors you care about
Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market → stable
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Correct facts used on the next screening or memo.
People
U
Umid Suleymanov
2.0
low confidence
I
Ilhama Novruzova
2.0
low confidence
K
Khalid Mammadov
2.0
low confidence
N
Natavan Hasanova
2.0
low confidence
M
Murat Kantarcioglu
2.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
Sarus
· Acquired
Use personal data for analytics and ML, safely and seamlessly
Maxime Agostini
Nicolas Grislain
Vincent Lepage