Trustworthy artificial intelligence

Reliable AI beyond the benchmark.

I am an Associate Professor at New Uzbekistan University and a Visiting Researcher at OIST, Japan. I study how AI behaves when inputs are unfamiliar, shifted, or adversarial, and advise industry teams on reliable evaluation and computer vision.

Portrait of Mohammad Sabokrou
Associate ProfessorNew Uzbekistan University
Visiting ResearcherOIST, Japan
Principal InvestigatorJSPS-funded AI research
Area ChairICLR · NeurIPS · BMVC

Selected research

Contributions spanning video intelligence, self-supervised learning, and trustworthy open-world AI.

Illustration of a cascading video anomaly-detection system
Video intelligence

Deep-Cascade

A fast cascade of 3D neural networks for detecting and localizing anomalies in crowded video.

Illustration of neighborhood-relational self-supervised representation learning
Learning foundations

Neighborhood-Relational Encoding

Self-supervised representations that preserve relationships between neighboring samples without intensive annotation.

Illustration unifying anomaly, novelty, open-set, and out-of-distribution detection
Trustworthy AI

Unified Anomaly & OOD Survey

A cross-domain framework connecting anomaly, novelty, open-set, and out-of-distribution detection.

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AI consulting for industry

Independent technical advice, robustness audits, computer vision and anomaly-detection strategy, due diligence, workshops, and focused proofs of concept.

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Latest updates

Top Area Chair — NeurIPS 2026 Main Track

Invited Talk — Keimyung University AI Week 2026, Daegu (28 October)

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