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The FHNW comprises 10 schools with different specializations. Select a school to see its specific courses, study programmes and information.

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  • Computer Science
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People directory

Prof. Dr. Daniel Per­ru­choud

Job title/activity of the person
Lecturer for Data Science

hero_daniel_perruchoud-topbild.jpg

Contact

Phone
+41 56 202 83 41 (Direct)
E-Mail
daniel.perruchoud@fhnw.ch

Address

FHNW University of Applied Sciences and Arts Northwestern Switzerland
School of Computer Science
Bahnhofstrasse 6
5210 Windisch

Activities at FHNW

Lecturer for Data Science at the Institute for Data Science FHNW

Teaching

At Bachelor of Science in Data Science

  • Exploratory data analysis,
  • Applied in Machine Learning
  • Natural Language Processing
  • Supervisor of Bachelor project theses

At Master of Science in Engineering MSE

  • Advanced Natural Language Processing
  • Supervisor of Master students

Research

  • Natural Language Processing applications
  • AI-based information retrieval
    Machine Learning applications for process and product optimization

Profile

Projects

2025: Robust Swiss German Speech-to-Text System for Multi-Speaker Psychological Dialogues (in progress, Innosuisse funded)

2025: Low-latency Swiss German AI agents (in progress, Company funded)

2025: Artificial Intelligence Integration into the Safety Reporting System (in progress, Company funded)

2025: Schweizerdeutsch-to-LLM (in progress, Company funded)

2025: Robust visual identification of UI elements in business process testing (in progress, Innosuisse funded)

2025: Use of Natural Language Processing and Generative Artificial Intelligence for efficient information extraction (in progress, Company funded)

2025: Enhancing Patient Education with AI Avatars in Preoperative Care: Feasibility of German LLMs (Innosuisse funded)

2025: LUKE App for visual cloth discrimination (Innosuisse funded)

2025: Optimization of the production process of current and voltage transformers with machine learning (Company & HTZ funded)

2025: AI-based Solutions for FtO Assessment in Technical Patent Searches (Company & HTZ funded)

2024: “AI Tutor for Students” - Efficient Information Extraction with Retrieval Augmented Generation (FHNW funded)

2024: “RockPulse” - Sensing precursors of landslide accelerations in ambient vibration data (Innosuisse funded)

2024: “AI-Selfie@ENTER” - Developing personalized selfies with generative AI (FHNW funded)

2024: Understanding Client Sentiment with NLP from Small Data (Company & HTZ funded)

2024: Introduce data-driven development and operation in device qualification (Innosuisse funded)

2022: Enhancing DSM’s Third Party Patent Monitoring with Machine Learning and Natural Language Processing (Company funded)

2021: ML-based visual quality monitoring for Hybrid Photon Counting device manufacturing (Innosuisse funded)

2020: Condition Monitoring and Predictive Maintenance for Wind Turbines Developed on Massive Wind Park Sensor Data (Innosuisse funded)

Biography

1986-1991

Diploma in theoretical solid state physics (dipl. phys. ETH Zürich, Switzerland)

1992-1996

PhD in the domain of climate change impact studies (Dr. sc. nat. ETH Zürich, Switzerland)

1997-1999

Research Associate at the Swiss Federal Office for the Environment

1999-2000

Analytical Consultant at NCR / Teradata Wallisellen, Switzerland

2000-2008

Data Scientist at UBS Switzerland AG Zürich, Switzerland

2009-2018

Senior Data Scientist and Team Lead at UBS Switzerland AG Zürich, Switzerland

Since 2019

Professor at FHNW in Brugg-Windisch, Switzerland

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School of
Computer Science FHNW University of Applied Sciences and Arts Northwestern Switzerland

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