About Me
Staff Machine Learning Engineer at twig.energy developing machine learning models for trading in power markets – enabling higher revenues for producers and unlocking zero carbon power for consumers.
In my PhD, I worked on deep generative models, including normalizing flows and diffusion models with Prof. Ole Winther at DTU Compute.
For more details, see my full CV or my Google Scholar.
Interests
I am broadly interested in machine learning and deep learning. I have previously worked on deep generative models, probabilistic inference approaches and boosting methods.
News
| May 22, 2023 | I joined twig.energy as a staff machine learning engineer where I will be developing machine learning models for trading in power markets – enabling higher revenues for producers and unlocking zero carbon power for consumers. |
| Jun 15, 2022 | I held a 3-hour lecture on normalizing flows at the Nordic Probabilistic AI School in Helsinki, Finland. |
| Feb 7, 2022 | I successfully defended my PhD on Normalizing Flows with Non-Bijective Layers after thorough examination by Rianne van den Berg, José Miguel Hernández-Lobato and Søren Hauberg. I am very grateful to my supervisor Prof. Ole Winther. |
| Sep 27, 2021 | Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions accepted at NeurIPS 2021! |
| Jun 18, 2021 | I held a 2-hour lecture on normalizing flows at the Nordic Probabilistic AI School. |