Built on Research.
Driven by Impact.

SelfMinds AI was founded on a conviction that the most durable AI systems are the ones that learn, adapt, and improve through experience — not just at training time, but continuously in the real world.

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CVPR ACL Interspeech ICIP CVIU ReCALL

Machine Learning — ranked among Japan's top research universities

Our Mission

We create intelligence that works for people—not the other way around. Our mission is to build practical AI systems that solve meaningful problems, automate complex workflows, and enhance human decision-making. At SelfMinds AI, we develop intelligent systems that continuously learn, adapt, and improve through experience. By combining multimodal AI, agentic systems, computer vision, and large language models, we deliver reliable, scalable solutions that create measurable value. We believe AI should be powerful, trustworthy, and evolve alongside the people and organizations it serves.

Our Vision

From multi-agent robotics to self-supervised learning to agentic AI: we have been here for the arc, not just the moment. SelfMinds AI was founded on a simple conviction: the future of intelligence is collective and self-improving. We create intelligent communities where agents collaborate, share knowledge, learn from success and failure, and evolve—individually, collectively, and across generations.

Research Depth.
Production Scale.

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Chief Scientist

Kourosh Meshgi

Chief Scientist
PhD, Machine Learning · Kyoto University · 2015
h-index 10
CVPR · ACL · Interspeech · ICIP · CVIU · ReCALL

21+ Years at the Frontier

Kourosh Meshgi is a machine learning researcher and engineer who has spent over two decades advancing the state of the art across computer vision, natural language processing, and agentic AI. He earned his PhD in Machine Learning from Kyoto University in 2015 and conducted research at RIKEN AIP — Japan's flagship AI institute.

His work spans the full arc of modern AI: from classical probabilistic tracking and ensemble methods in the 2010s, through deep generative models and speech processing, to today's agentic and multimodal systems. He has published at CVPR, ACL, Interspeech, ICIP, CVIU, and ReCALL — and holds an h-index of 10.

At SelfMinds AI, Kourosh leads research direction and system architecture. His core conviction: that AI systems should be self-improving, trustworthy, and designed to work for the humans who depend on them.

Computer Vision Agentic AI NLP & Dialogue Generative Models Self-Learning Systems Multi-agent AI HIPAA-grade AI Workflow Automation

Key Publications

Peer-reviewed work at top venues — the research foundation behind SelfMinds AI systems.

ACL · 2023
Intent Classification for Spoken Dialogue Systems
Association for Computational Linguistics — NLP & speech understanding
CVPR · 2018
Ensemble Object Tracking with Adaptive Confidence
Computer Vision and Pattern Recognition — real-world tracking under uncertainty
ICIP · 2020
AnimGAN: Generative Animation Synthesis
IEEE International Conference on Image Processing — generative video models
CVIU · 2016
Occlusion-Aware Particle Filter Tracker
Computer Vision and Image Understanding — robust visual tracking
ReCALL · 2017
Partial Captioning for L2 Listening Comprehension
Language Learning & Technology — NLP applied to language acquisition
Full publication list on Google Scholar →

Researchers & Engineers

Senior applied scientists who have published at top venues and shipped production AI systems.

Kourosh Meshgi

Chief Scientist

PhD, Kyoto University. CVPR · ACL · Interspeech · ICIP. h-index 10. Expert in CV, NLP, generative AI, and agentic systems.

Maryam Mirzaei

Senior Applied Scientist

PhD, Kyoto University. ACL · Interspeech · WWW. h-index 8. Expert in NLP, ASR, generative AI, and agentic systems. Scholar →

Join the Team

Open Roles

Building the future of intelligent systems. If you think at the intersection of research and impact — let's talk.

Trusted by Teams Building Real AI

What the people and organizations we work with say about SelfMinds AI.

Let's Build Intelligent Systems Together.

Tell us about your problem. We'll tell you what's possible.