I am an AI engineer from Mongolia with a solid educational background in Software Engineering and Data Science, complemented by practical experience in both research and industry. My interests focus on developing intelligent systems in computer vision, natural language processing, multimodal models, and robotics.
Hurile is a master’s student in Data Engineering and Analytics at the Technical University of Munich, specializing in AI, multimodal learning, and robotics. With hands-on experience in autonomous driving perception and ontology-based reasoning, he focuses on integrating large language models with structured knowledge systems. In addition to his AI background, Hurile has strong experience in software and database development, as well as cloud computing, which enables him to design scalable, data-driven applications. He combines technical expertise with creativity and curiosity, driven by a passion for building intelligent systems that connect machine understanding with real-world impact.
Python, C++, C, MATLAB, ROS2, PyTorch, FastAPI, React, Next.js, Docker, Azure OpenAI, LangChain, LangGraph, Docker, Kubernetes, AWS, SQL, NoSQL
Computer Vision (3D Object Detection, Tracking, Sensor Fusion), NLP & LLMs, Reinforcement Learning, Ontology Learning, Multimodal Reasoning
M.Sc. in Data Engineering & Analytics; B.Eng. in Software Engineering
Developed 3D perception and fusion pipelines for autonomous driving, built LLM-based ontology and concept-tree systems at Siemens.
Multimodal learning, difussion model, ontology learning, data modelling, semantic representation, vision-language-action models.
Mongolian (native), Mandarin(native), English (C2), German (B1), Spanish(A2)
During my studies I have worked on several projects at the university as well as in industries, including autonomous driving perception, web development, robotics and ontology-based reasoning.
Developed a comprehensive 3D perception pipeline integrating LiDAR and camera data for robust object detection, tracking, and sensor fusion in autonomous vehicles.
Built an advanced ontology and concept-tree system leveraging Large Language Models (LLMs) to enhance knowledge representation and reasoning capabilities for industrial applications.
Implemented reinforcement learning algorithms to enable autonomous agents to learn optimal policies for complex tasks in dynamic environments.
Developed a web application that integrates Large Language Models (LLMs) to visualize and analyze underground water storage data, providing intuitive insights and decision-making tools.
"Obstructions are what you must overcome to reach your dreams; excuses are the obstacles you turn into reasons to abandon them."
Sparse covariance estimation explained
3D object detection pipeline
Comprehensive lecture notes on Computer Vision 3 at TUM.
I would love to hear from you! Whether you have a question, a project idea, or just want to say hello, feel free to reach out to me via email at hurile.borjigin@icloud.com.
hurile.borjigin@icloud.com