Professional Overview
Eyal Wirsansky is a seasoned data scientist and adjunct instructor specializing in artificial intelligence, with a deep focus on genetic algorithms, machine learning, and optimization techniques. He has extensive experience leading AI-driven projects and deploying scalable cloud solutions using AWS Lambda, SQS, and containerized services. Eyal's technical acumen spans Python, deep learning frameworks, and advanced language models, making him adept at both research and application of AI technologies. In addition to his technical roles, Eyal is passionate about education and serves as an adjunct professor, teaching university-level courses in AI, including computer vision and natural language processing (NLP). He has contributed to student mentorship programs, research initiatives, and educational outreach. His hands-on approach fosters student innovation, particularly in areas like prompt engineering and reinforcement learning. Eyal's collaborative mindset extends to cross-disciplinary projects, such as educational content development and community engagement, as showcased by his leadership roles at conferences and EdTech-focused events. His expertise in genetic algorithms positions him to tackle complex optimization challenges, and he continually seeks opportunities to apply his research to real-world problems across industries.
Areas of Expertise
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
