My primary research is in data science applied to a number of domains. I work with a number of signal modalities (biological, neural and behavioral signal; audio and video). In neuroscience and biomedical engineering, I work with neural (EEG), physiological (HR, GSR, Respiration, Pupillometry), and behavioral (eye movements, annotations) signals. In the acoustical and image processing domain, I work with both audio signals (speech and music) and video. This is all looking at cognitive and perceptual aspects of speech, music, and video. Here I have been specifically looking at engagement, emotions, memory, and learning.

My work is in the cross-section between machine learning, digital signal processing, cognitive psychology, and neuroscience.

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Curriculum Vitae


2012-2015: Ph.D. at Cognitive Systems group, Department of Applied Mathematics and Computer Science
2014: Visiting researcher at Center for Digital Music at Queen Mary University in London.
2007-2011: M.Sc. Engineering Acoustics, Technical University of Denmark.
2003-2007: B.Eng. Information and Communication Technology, Engineering College of Copenhagen (IHK).
2005: Visiting student at Royal Melbourne Institute of Technology.

Academic Thesis

Ph.D. thesis: “Predicting the emotions expressed in music”
Master thesis: “Modelling of Emotions expressed in Music using Audio features“
Bachelor thesis: “Natural sound field synthesis in headphones”

Current Position(s)

2023-now: Research Assistant Professor in Neuroscience, City College of New York, Department of Biomedical Engineering.
2022-now: Psychology Researcher, Hume AI Inc.

Previous Positions

2021-2023: Research Associate in Neural Engineering at City College of New York, Department of Biomedical Engineering.
2017-2021: Postdoc in Neural Engineering at City College of New York, Department of Biomedical Engineering.
2016-2017: Postdoc at Technical University of Denmark (DTU), Department of Applied Mathematics and Computer Science in the Cognitive Systems group.
2011: Research assistant at DTU Informatics.
2006-2007: Bachelor trainee and student help at Bang & Olufsen ICEpower A/S.


2018-now: Electrophysiological experiments for Research Assistants at City College of New York, Instructor.
2016: Big Data Business Academy, Lecturer
2013+2016: 02459/60 “Advanced Machine Learning” (5 ECTS), Project supervisor
2013+2016: 02450: “Introduction to Machine Learning and Data Modeling” (5 ECTS), TA
2012-2013: 02451: “Digital Signal Processing” (10 ECTS), TA
2012-2013: 02453: “Applied Digital Signal Processing” (5 ECTS), Project supervisor

Master Thesis Supervisor

2016: Damir Sasivarevic, thesis titled “Activity recognition and repetition counting of cross-training exercises”.
2016: Stina Lyck Carstensen, thesis titled “Modeling the effect of music on human stress responses”.

Reviewer / PC Member

Scientific Reports, NeuroImage, Trends in Hearing, Experimental Brain Research, Journal of Imaging Neuroscience, Journal of Psychophysiology, Annals of New York Academy of Science, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Affective Computing, Frontiers in Integrative Neuroscience, Frontiers Human Neuroscience.

Awards and Scholarships

Danish Sound Young Researcher Award 2015. Received 21.5k EUR from the Danish Agency for Science, Technology and Innovation for the project called “Musik, Matematik og Følelser” (case no. 6163-00017B), received 17k EUR from H.C. Ørsteds foundation for the project “Modelling the Effect of Music intervention”. Received 6k EUR from A.N. Neergaard og Hustrus Fond for the project “Musikintervention til forbedring af dementes søvnkvalitet”. Furthermore, received travelling grants from Knud Højgaards foundation, Otto Mønsted foundation and Oticon foundation.