Hi, my name is

Yanick.

I like to build stuff

A software engineer and researcher. I am generally into learning new technologies and building things with them that people enjoy using.

About Me

I am a software engineer and researcher in the digital health domain with a passion for great digital experiences. I have a background in computer science and game design. I am currently pursuing a PhD at ETH Zürich. Here are a few technologies I've been working with recently:
  • C#
  • Python
  • Java
  • C++
  • Unity
  • Tensorflow

Experience

PhD Candidate and Doctoral Researcher - ETH Zürich
Sep 2019 - present
View the project
Development and evaluation of a gamified slow-paced breathing training. Design and implementation of a real-time breathing phase detection algorithm.
Research Assistant - ETH Zürich
Apr 2019 - Sep 2019
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Conducting a field study about the relation of mouse interactions and job strain. Participating in a research project concerned with digital physiotherapy coaching through motion tracking and mixed reality.
Tutor for the Computer Science Degree Program - ZHAW
Feb 2015 - May 2015
Planning and conducting interactive lessons for the course Mathematics Analysis 2.
Software Engineer - Netcetera
Aug 2012 - Jul 2013
Software development in a Scrum project. Developing a big Java/Maven RCP application.
Software Engineer (Apprenticeship) - Netcetera
Aug 2008 - Aug 2012
  • Learning the basics of IT with a strong focus on software development.
  • Participation in a Scrum project, where a big Java/Maven RCP application was developed.

Education

Sep 2019 - present
PhD Candidate and Doctoral Researcher
ETH Zürich

Teaching Activities

  • Teaching Assistant for the course Mastering Digital Business Models
My academic record
2016 - 2019
Master of Science ZFH in Engineering with a Specialization in Information and Communication Technologies
ZHAW School of Engineering
  • Semester Project 1: Interactive Visualization of Very Large Voxel-Based Datasets
  • Semester Project 2: Deep Learning as a Game Technology
  • Master Thesis: Visual Analytics for Explainable Deep Learning
2017 - 2018
Master of Arts ZFH in Design with a Specialization in Interaction
Zurich University of the Arts (ZHdK)
  • Master Thesis: Automatic Game Mechanic Generation
Master Thesis
2013 - 2016
Bachelor of Science in Computer Science UAS Zurich
ZHAW School of Engineering
  • Project Thesis: Speaker Identification using Convolutional Neural Networks (translated)
  • Bachelor Thesis: Automatic Voice Recognition through Deep Learning (translated)
2008 - 2012
Technical Vocational Baccalaureate (Berufsmatura)
Berufsbildungsschule Winterthur (BBW)
2008 - 2012
Informations Technology Apprenticeship (Informatiker Applikationsentwicklung EFZ)
Berufsbildungsschule Winterthur (BBW)

Publications

Breathing as an Input Modality in a Gameful Breathing Training App (Breeze 2): Development and Evaluation Study
JMIR Serious Games, 2022, 10(3), e39186.
The Impact of a Gameful Breathing Training Visualization on Intrinsic Experiential Value, Perceived Effectiveness, and Engagement Intentions: Between-Subject Online Experiment.
JMIR Serious Games, 2021, 9(3), e22803.
A Playful Smartphone-based Self-regulation Training for the Prevention and Treatment of Child and Adolescent Obesity: Technical Feasibility and Perceptions of Young Patients.
In 1st Workshop on Healthy Interfaces (HEALTHI), collocated with the 26th ACM Annual Conference on Intelligent User Interfaces (IUI)–Where HCI meets AI. ACM.
Physiological Responses and User Feedback on a Gameful Breathing Training App: Within-Subject Experiment.
JMIR serious games, 2021, 9(1), e22802.
Breeze: Smartphone-based acoustic real-time detection of breathing phases for a gamified biofeedback breathing training.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3(4), 1-30.
Learning embeddings for speaker clustering based on voice equality.
In 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP), Tokyo, 25-28 September 2017. IEEE.
Speaker identification and clustering using convolutional neural networks.
In 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), Vietri sul Mare, Italy, 13-16 September 2016. IEEE.

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