Pascal Wullschleger

Pascal Wullschleger serves as Research Associate and Doctoral Student at Lucerne School of Computer Science and Information Technology, Lucerne University of Applied Sciences since 2022, concurrently working as Data Scientist at Jaywalker Digital. His expertise bridges academic research and industry applications in machine learning.

His educational background includes:

• Master of Science in Computer Science, Lucerne University of Applied Sciences
• Bachelor of Science in Computer Science, Lucerne University of Applied Sciences

Wullschleger's research demonstrates deep specialization in Machine Learning and Natural Language Processing, with significant contributions to health informatics and recommender systems. His work spans over 20 projects including STU Recommender Systems, Adverse Event Mining, and AI for All, focusing on practical implementations in healthcare, finance, and consumer domains. Technical competencies encompass Reinforcement Learning, Deep Learning, and Linux-based development environments.

Publication trends reveal evolving focus from health record analysis (2022) to explainable public health NLP (2024) and specialized LLM applications for food taxonomy (2025), indicating growing expertise in domain-specific language model adaptation.

Key recognition includes:

• ABIZ Team Achievement for crafting first AI-generated beer recipe

While no formal student advising is documented, Wullschleger actively collaborates with industry partners including Prepress Media AG, Eventfrog, and Siemens Building Technologies on revenue management, fake review detection, and financial advisory systems. His projects consistently address real-world optimization challenges through data science.

He operates within the ABIZ research ecosystem at HSLU, contributing to cross-disciplinary initiatives like Skin-App for medical eczema grading and PFAS analysis in Medizintechnik, demonstrating commitment to socially impactful AI solutions.