Background
To provide a bit more background information, here is my not so straightforward path through the academic and professional world.
Professional Experience
2023 - present
Senior Machine Learning Staff Engineer · ams OSRAM, Martigny
As a technical lead in AI development for next-gen wearable devices, I optimize signal processing pipelines (DSP), exploit nuanced information in latent spaces using specialized loss functions, and minimize computational costs for applications in vital signs monitoring (PPG, respiration), eye-tracking (gaze), AR/VR, and spatial computing on edge hardware. My role involves collaborating extensively with cross-functional engineering teams to translate complex research findings into robust, scalable AI solutions.
2022 - 2023
Machine Learning Staff Engineer · ams OSRAM, Martigny
Spearheaded projects in sensor fusion, signal processing, and optical solutions, using machine learning—including generative models and constrained optimization — to enhance the performance of spatial and biomedical sensing devices. Developed real-time processing capabilities for vital signs monitoring (PPG, respiration) and eye-tracking (gaze) and pioneered innovative technologies like self-mixing interferometry (SMI), aiming for high-accuracy, low-power solutions at remarkable speeds.
2019 - 2022
Data Science Course Developer & Instructor · EPFL, Lausanne
As an Applied Machine Learning Course Developer and Instructor, I mentored hundreds of participants through hands-on ML projects across various industries and optimized numerous company internal processes. I created and executed AI workshops, hackathons, conference talks, and collaborated with academic and industry partners to identify data-driven solutions. As Content Director for That’s AI, I led the creation of an informative multilingual AI education platform, coordinating with content creators, designers, marketing, and front-end developers.
2014 - 2016
Research Collaborator in Neuroscience & Neuroimaging · CHUV, Lausanne
Developed, executed, and analyzed eight neuroimaging studies using MRI, EEG, and eye-tracking, focusing on neurological health conditions. Developed several software tools to enhance the analysis and interpretation of complex MRI and EEG data, focusing on performance and adaptability, optimizing processing pipelines for efficiency.
2013 - 2014
Research Assistant in Neuroscience & Neuroimaging · INAPIC, Zurich
Supported a range of projects by developing software tools for analyzing behavioral, physiological, and MRI data focused on aging; provided support to collaborators for data analysis, enhancing the accuracy and efficiency of research outcomes.
2011 - 2011
Internship at Massachusetts Institute of Technology · MIT, Cambridge, USA
Design and execution of neuroimaging research, development and optimization of signal processing software. Extended internship due to exceptional performance, emphasizing my ability to work autonomously and effectively in a research setting.
2012 - 2017
Special officer in the Psychological-Pedagogical Service of the Armed Forces · Swiss Army
Counseling, stress prevention, and guidance to soldiers and cadre of the Armed Forces.
2007 - 2014
Clerk in payment transactions · Migros Bank, Zurich
Data analysis for the purpose of anomaly detection and process optimization.
Education
2016 - 2021
PhD in Neuroscience · University of Lausanne
Thesis: Innovation and standardization of processing pipelines for functional MRI data analysis
Work: Focused on optimizing neuroimaging data analysis pipelines using advanced machine learning techniques. Developed eight neuroimaging toolboxes facilitating efficient processing and analysis of MRI, EEG, and eye-tracking data. Executed seven research studies incorporating novel measuring techniques, emphasizing performance and adaptability.
2012 - 2014
Master of Science in Neuroscience with minor in Neuroinformatics · University of Zurich
Explored computational models in neuroscience, with a thesis comparing neurological patterns in ASD (autism spectrum disorder) and ADHD via structural MRI data analysis. Lectures covered neuroinformatics, neurobiology, cognitive psychology, neuroimaging methods, AI, signal processing & computational vision.
2007 - 2012
Bachelor of Science in Psychology with minor in Neuroinformatics · University of Zurich
Studied the intersection of psychology and technology, focusing on how technological tools can enhance our understanding of cognitive and emotional processes, with lectures in neuroinformatics, statistics, neuroscience, informatics, biology, mathematics & AI.
Awards & Fellowships
2020
Solo gold medal (11th place out of 1047 teams) · Kaggle
Solo gold medal (11th place out of 1047 teams) in Kaggle’s TReNDS Neuroimaging challenge.
2018
Travel Fellowships for code sprint at MIT · Massachusetts Institute of Technology (MIT)
Travel Fellowship and invitation to 3-day code sprint at McGovern Institute for Brain Research at MIT. Code sprint focused on neuroimaging toolbox Nipype and dataflow engine Pydra.
2018
Invitation to Neurohackademy summer school · University of Washington
Chosen from 400 applicants to be one of 60 participants at the Neurohackademy 2018 at the eScience Institute, University of Washington in Seattle, a two-week hands-on summer school in neuroimaging and data science.
2018
SSN Travel Fellowships · Swiss Society for Neuroscience (SSN)
SSN Travel Fellowships for Student & Postdoc Members for 1’500.00 CHF. Awarded to support travel to a selective summer school abroad.