Open to opportunities

Rakhat Ospanov

@rakhatospanov

Message

Innovative CEO specializing in Computer Vision and Machine Learning.

Kazakhstan

Message

What I'm looking for

I am seeking opportunities that foster innovation, collaboration, and growth in technology-driven environments.

I am a passionate entrepreneur and robotics engineer currently leading SmartView Innovations, a startup dedicated to revolutionizing the mining and metallurgical industries through advanced Computer Vision and Machine Learning solutions. My journey began at Nazarbayev University, where I honed my skills and developed a strong foundation in robotics engineering, achieving a GPA of 3.62/4.0.

At SmartView Innovations, I successfully built a multidisciplinary team and spearheaded the development of groundbreaking products that optimize operational efficiency. One of our notable achievements includes enhancing gold processing efficiency by 2% for Brendt LLP through automated inspections using drones. My commitment to innovation is further exemplified by my role as Co-founder and CPO at WMA Group, where we are creating interactive outdoor advertising solutions that leverage cutting-edge technologies like Computer Vision and Large Language Models.

Experience

Work history, roles, and key accomplishments

Current

Co-founder and CPO

Current

WMA Group LLP

Sep 2024 - Present (1 year 9 months)

Co-founded WMA Group, a startup focused on creating innovative and interactive outdoor advertising solutions. Developed "Ailyn" and "Tamara", virtual assistant smartboards equipped with advanced software powered by Computer Vision, Speech-to-Text, Large Language Models, and Text-To-Speech technologies.

Computer Vision Text To Speech Large Language Models Product Development Business Development AI Software Engineering Project Management

Current

Machine Learning Researcher

Current

Nazarbayev University

Aug 2024 - Present (1 year 10 months)

Designed a custom architecture integrating Mamba SSM with Convolutional Neural Networks (CNN) and Multi-Layer Perceptrons (MLP). Achieved subject-dependent accuracy of 81.21% and subject-independent accuracy of 71.18% on the EEG Motor Imagery BCI IV 2a dataset.

Mamba SSM Convolutional Neural Networks Multi Layer Perceptrons EEG Machine Learning Deep Learning Research Python Data Analysis

Current

Machine Learning Researcher

Current

Nazarbayev University

Jun 2023 - Present (3 years)

Developed a YOLO and Vision Transformers-based solution with custom georeferencing to localize and classify sprinkler states in UAV video footage. Collected 700 video samples covering three sprinkler states during fieldwork at "Brendt LLP".