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Schedule Interview NowMy name is Yuldashev M. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, OpenCV, Deep Learning, PyTorch, TensorFlow, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I've worked on include: Prosthetic Leg Stair Navigation Analysis System, Smart Office Activity Monitoring System, AI-Powered Football Match Analysis System, Smart Face Recognition System with FAISS & Buffalo, Real‑Time Talking Avatar (≈1s Latency, OpenAI + Simli), etc.. I am based in Incheon, South Korea. I've successfully completed 13 projects while developing at Softaims.
Information integrity and application security are my highest priorities in development. I implement robust validation, encryption, and authorization mechanisms to protect sensitive data and ensure compliance. I am experienced in identifying and mitigating common security vulnerabilities in both new and existing applications.
My work methodology involves rigorous testing—at the unit, integration, and security levels—to guarantee the stability and trustworthiness of the solutions I build. At Softaims, this dedication to security forms the basis for client trust and platform reliability.
I consistently monitor and improve system performance, utilizing metrics to drive optimization efforts. I'm motivated by the challenge of creating ultra-reliable systems that safeguard client assets and user data.
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CAD-IT Korea co. Ltd
his advanced computer vision system analyzes the biomechanical performance of individuals with prosthetic legs navigating stairs through real-time video processing. The system employs deep learning mo
The Smart Office Monitoring System uses computer vision to track workplace activity through cameras, detecting actions like phone usage, desk presence, and inactivity. It aims to improve productivity
Developed a real-time football analytics system using computer vision and deep learning. The system automatically tracks all players and the ball, measures speed, distance, and positional data, and vi
Developed a high-performance face recognition system capable of storing and searching up to 10 million identities. Utilized the Buffalo (ArcFace) model for generating high-accuracy face embeddings, in
Built a production‑ready real‑time talking avatar with ~1s end‑to‑end latency. Speech is streamed to the OpenAI API for response generation; audio is rendered via Simli for expressive TTS and precise
Bachelor of Engineering (BEng) in Computer science
2019-01-01-2023-01-01