Asparuh Stoyanov

Key Ward HUB – AI SaaS Platform for Engineering Teams
Led product and strategy for a self-service AI platform that accelerates simulation and test data workflows in engineering. Drove platform vision, technical architecture, and cross-functional execution to enable scalable, trustworthy AI adoption.

• AI & Data Science Integration: Embedded agentic AI features (e.g., intelligent assistants, workflow automation) into the engineering data pipeline; championed the use of ROMs, neural operators, and simulation-driven ML models.
• Engineering Workflow Enablement: Streamlined data workflows for engineers and data scientists through intuitive UX and automation; improved accessibility of ML/AI tools for non-ML experts.
• Customer-Centric Design: Led user research with engineers and technical managers to ensure product-market fit and alignment with real-world simulation and test data challenges.
• Scalable Product Operations: Built internal systems for data-driven product management (Notion, Jira, GitLab) and scaled cross-functional execution across engineering, data, and product teams.
• Technical Advocacy: Authored use cases and case studies focused on AI for simulation, design automation, and predictive modeling, enhancing technical engagement and credibility.

Founding Executive – Technology & Product Strategy
Led early-stage tech and product strategy for a data-driven SaaS platform supporting simulation and engineering workflows. Focused on scalable AI/ML systems and infrastructure for industrial data science adoption.

• ML System Design: Built surrogate modeling pipelines using ROMs, Neural Operators, GNNs, Autoencoders, and CNNs
• Data Architecture: Designed full-stack data infrastructure and AWS-based cloud architecture
• Low-Code Enablement: Developed a low-code ML platform for domain experts (e.g., mechanical engineers)
• Team Leadership: Scaled and led cross-functional teams to deliver ML-integrated simulation workflows
• Product & Strategy: Defined roadmap around engineering AI use cases; aligned with users through structured research
• Technical Advocacy: Acted as technical lead on AI/ML and simulation strategy with executive stakeholders

Gaze Estimation System – Bachelor Thesis (Grade: 1.0)
Developed a 3D/2D gaze estimation algorithm integrating computer vision and machine learning. Implemented facial landmark tracking, head pose estimation, and camera calibration to predict gaze direction from monocular input.

• Applied CNNs, regression models (XGBoost, Linear), and clustering (GMMs, K-Means)
• Built in Python/C++ using OpenCV, Dlib, TensorFlow, ADTF
• Combined traditional CV with supervised learning for real-time estimation

R&D – Driver State Monitoring
Developed and optimized C++ computer vision algorithms (face detection, tracking, cropping) within the ADTF framework. Generated synthetic training data for CNN-based driver monitoring systems.

Product Development & Prototyping
(Co-)developed 5 boat cockpits and 3 innovative device prototypes in collaboration with renowned industrial designers. Led full product development from sketches to CAD and prototype fabrication.

• 3 years in 3D design (ProEngineer, SolidWorks); CAE & CFD (StarCCM+)
• Hands-on with milling, turning, bending, and punching machines
• 3 years working with aluminum products
• Led R&D on industrial coatings and adhesives

Quality Control & Production Insight – Common Rail Injection Systems
Rotated through 12 specialized assembly and measurement stations, gaining in-depth exposure to the manufacturing and quality assurance processes of high-precision common-rail diesel injection pumps. Developed a strong understanding of automotive production workflows and standards.