I am concerned with developing accurate and efficient methods for simulating room acoustics in dynamic scenes with moving sources/receivers and flexible geometries. Applications are in computer games, mixed reality, and building design. The focus is on traditional numerical methods and machine learning methods for solving the underlying physics, implicitly taking wave phenomena into account.
Accelerating sound propagation in realistic 3D scenes with parameterized sources using deep neural operators. To be submitted in May 2023.
A sensitivity analysis on the effect of hyperparameters in deep neural operators applied to sound propagation. To be presentated at a conference in 2023.
I have a profound interest in algorithmic composition, such as data-driven music creation and harmonization. Previously, I developed a method for harmonizing rhythmic music, and it uses a hidden Markov model to learn harmonizations of different artists in different genres and allows new chord sequences to be generated for a given melody.
2019-2023: PhD student, Virtual Acoustics, DTU - Technical University of Denmark.
Developing and implementing methods for solving the physical governing equations taking geometry and boundary conditions into accounts for describing the acoustics in rooms.
2023: Research Scientist Intern, Audio Presence, Meta, Redmond, US.
2022: Visiting Research Scholar, Brown University.
Visiting the CRUNCH group led by Professor George Karniadakis as part of my PhD studies. The focus was on applying neural operators to learn the wave equation for acoustic wave propagations in rooms.
2019: Blockchain Software Developer, eToroX (DK).
Developing blockchain solutions for financial trading, collaborating with academia to solve advanced problems in the field.
2018-2019: Product Owner/Software Developer, Mobile Solutions, 3Shape (DK).
Leading the Mobile Solutions at 3Shape, one of the world's leading manufacturer of 3D scanners and CAD/CAM software solutions within the dental industry.
2013-2018: Mobile Software Developer, 3Shape (DK).
I took over a very young project, re-designed the app and grew the active user base from almost none to a substantial number of users. Leading transition from ObjC/Swift to Xamarin C# involving architectural decisions.
2012-2015: 3D Scanner Software Developer, 3Shape (DK).
Part of a team of ten people developing 3D dental scanning software written in Delphi/C#.
2015-2018: Founder, Livetake (DK).
Founded the award-winning company Livetake, making it possible to co-create stories with friends and automatically replace the poor smartphone sound with high quality live sound. Developed the technology stack on my own.
Launched at Roskilde Festival 2015 (100.000+ visitors), won a TechCrunch Disrupt award in San Francisco (2015), won the Danish Sound Startup Award (2016).
Partnerships, strategy, business plans, hiring, user tests.
Web service in Golang; iOS app for synchronizing videos with high-quality audio; iOS audio app (DAW) for recording multi-channel concert audio
Education
2010-2012: MSc in Computer Science, Uni. of Copenhagen, Denmark. Specialized in Mathematical Modelling and Computations.
2006-2010: BSc in Computer Science, Uni. of Copenhagen, Denmark.
2005-2006: Carl Nielsen Academy of Music, Music Concervatory, Odense, Denmark. Completed first year at the rhythmic section with the guitar as my main instrument.
Theses
Master's Thesis (2012): Real-time Auralisation of the Lower Frequency Sound Field using Numerical Methods on the GPU, Institute for Technical Acoustics, Aachen Uni., DE / Dep. of Computer Science, Uni. of Copenhagen, DK.
The thesis investigated whether it was possible to implement finite-difference time-domain methods for solving the 3-D wave equation in real-time on the GPU using C++/CUDA with focus on physical correct simulations of the lower frequency sound field.
Bachelor's Thesis (2009): Computer-assisted music composition -- A database-backed algorithmic composition system, Dep. of Computer Science, Uni. of Copenhagen, DK.
Bachelor thesis on the topic 'algorithmic composition' using different machine learning techniques. A software tool was developed for automatically generating music phrase variation and harmonisation from user input, each conforming to a predefined musical genre.
Notus is a domain-specific language for expressing musical structures in the high-level, declarative style of functional programming written in Swift.
Harmonisation in modern rhythmic music using Hidden Markov Models [manuscript]
A method for harmonising rhythmic music is presented. It uses a hidden Markov model to learn harmonisations of different artists in different genres and allows new chord sequences to be generated with respect to a given melody.
I have started composing and playing music again after years of hibernation. Some rough sketches for my project San Diego can be found on SoundCloud.
Talks and awards
Invited speaker at Primavera Pro, Barcelona, Spain (2018). Gave a 25 minutes talk about Livetake and how to engage concertgoers.
Keynote speaker at Audio Developer Conference, London (2017) [video]
A method for harmonising rhythmic music, implemented in Haskell, will be presented. It uses a hidden Markov model to learn harmonisations of different artists in different genres and allows new chord sequences to be generated with respect to a given melody. The main focus of this talk is on how to perform the feature extraction for the chords and the melody lines necessary for the method to perform well.
Eventbrite Live Award at TechCrunch Disrupt San Francisco (2015) [video]
Livetake participated in the TechCrunch Disrupt Event 2015 in San Francisco and demonstrated their latest technology. The prize for the technology that most enhance live concert experiences was given to Livetake.
Danish Sound Startup Award (2016)
Livetake won the prize for the most promising startup in Denmark within the audio industry.
The award was given by the Danish Sound Network, an innovation network with the aim of connecting start-ups, established companies and knowledge institutions within the Danish Sound industry.