Current Team

image Pedram Bakhtiarifard(2022/10–)In August 2022 Pedram Bakh. joined the Machine Learning section at DIKU as a research assistant to work on methods for sustainable AI and Resource Efficient ML. His primary interest lies in reducing the carbon footprint of ML tasks while maintaining similar performance statistics to current state-of-the-art methods. Pedram holds a BSc in Computer Science from DIKU and starts the MSc programme in September 2022.
imageFrederik L. Johansen(2022/08–)Hi! My name is Frederik, and I am a PhD student in the AIChemy project. I have a BSc in Physics and Computer Science from Aarhus University and a MSc in Computational Physics from UCPH. I am mainly doing atomic structure prediction from X-ray Total Scattering and Pair Distribution Function data using Generative ML.
image Ulrik Friis-Jensen(2022/08–)I am a PhD-fellow in the AIChemy project. I have both BSc and MSc in Nanoscience from the University of Copenhagen. I used my elective courses on the masters programme to do ML oriented math and programming courses. My work is mainly focused on using GNNs and Generative Models to do structure solution of nanoparticles from Total Scattering and Pair Distribution Function (PDF) data.
image Julian E. Schön(2023/01–)PhD candidate studying resource efficient ML methods.
image Tong Chen(2023/06–)Postdoc working on sustainable Machine Learning
image Jákup O. Svöðstein(2023/06–)Double PhD candidate (jointly with University of Faroe Islands) studying Data-Driven Machine Learning Approaches for Compressible and Incompressible Fluid Dynamics Modelling.
image Sebastian Eliassen(2023/10–)Research Assistant working on Low-precision Deep Learning
image Bob Pepin(2024/01–)Postdoc working on sustainable machine learning
image Rasmus Løvstad(2024/03–)Student Research Assistant working on carbon footprint aware task scheduling.

Former Team Members

image Dustin Wright(2023/02–2024/01)Postdoc who worked on sustainable Machine Learning