Outreach

Media Coverage

• Building more responsive, AI-driven infrastructure (Canadian Broadcasting Service), Radio/Podcast feature on the energy consumption of AI models. (link, around 26m mark)
• Samfundets AI-ambitioner har en skjult bagside: »Træning af systemerne kræver en enorm mængde energi« (INGENIØREN, Danish media outlet) (link) (pdf)
• Computer scientists show the way: AI models need not be SO power hungry (UCPH Press release), April, 2024. (link) (pdf)
• Klimabevidst AI-teknologi er fremtiden, DM Digi (Danish Magazine), Jan. 2024. (link) (pdf)
• Sort samvittighed eller grøn gamechanger?, Uddannelsebladet (Danish Magazine), Feb. 2024. (link) (pdf)
• ‘Ej Efternavn’: Indian in Denmark unable to get real name on residence card (TheLocal.dk), Feb. 2024. (link) (pdf)
• AI skyder afsted med rekordfart – hvad gør det egentlig ved klimaet?, Prosa, (Danish Magazine), Dec. 2023. (link) (pdf)
• The increasing carbon footprint of AI is a challenge. Here is what we can do about it (University Press Release) Oct. 2023. (link)
• Eksperter har udregnet Chat GPT’s elregning, Børsen, (Danish newspaper), July 2023. (link)
• Der Energiehunger der KIs, Süddeutsche Zeitung (German newspaper), April 2023 (link) (pdf)
• Taming AI models to minimize their impact on climate, June 2023, (link) (pdf)
• These simple changes can make AI research much more energy efficient, MIT Technology Review (2022) (link)
• Insect wingbeats will help quantify biodiversity, UCPH Press Release (2022) (link)
• Algorithm reveals the mysterious foraging habits of narwhals, UCPH Press Release (2021) (link)

• Students develop tool to predict the carbon footprint of algorithms, UCPH Press Release (2020) (link)

• Columns for The Hindu
  • Building an image classifier for sorting images, The Hindu (2022) (link)

Select Invited Talks

• 2024
  • “On the Carbon Footprint of Deep Learning: From Monitoring to Mitigation”. Talk at the Pioneer Center for AI workshop on Diverse AI Tasks, Denmark.
  • “Representation learning for Multi-Modal Data”. Invited Talk (remote) at University of St. Andrews, Scotland.
  • “Dialogue between Danish ICT Sector on ESG considerations about Generative AI”. Danish ICT Association (IT-Branchen). Denmark
  • “Graph Neural Networks: From spectral signal processing to self-attention”. Winter School lectures at Geilo Winter School. Norway.
• 2023
  • “Climate-Aware AI: Monitoring and Improving the Environmental Impact of ML”. Expert Talk at Danish Digital Tech Summit. Denmark. 2023
  • “Carbon Footprint of Medical Image Analysis and Mitigation Strategies”. Invited Talk at Erasmus MC.Netherlands. 2023
  • “On the Carbon Footprint of Deep Learning”. Invited Talk at Green Labs. Netherlands. 2023
  • “Generative ML and Ecological Modelling”. Invited Talk at Wageningen University. Netherlands. 2023.
  • “Representation Learning with Graph Neural Networks”, Invited Talk at 3rd GraphNeT Workshop, Bornholm, Denmark, 2023
  • “Representation learning in Medical Image Analysis”, Invited Talk at Chalmers University, Sweden, 2023
  • “On the Carbon Footprint of Deep Learning”, Invited Talk at Chalmers University, Sweden, 2023
  • “Resource Efficient ML: A Carbon Footprint view of Deep Learning”, Invited Talk at IT University, Denmark, 2023
  • “Carbon Footprint of Deep Learning”, Invited Talk at the ROS AI Workgroup (Online), 2023
  • “Resource Efficient ML: A Carbon Footprint view of Deep Learning”, Invited Talk at SINTEF, Oslo, Norway, 2023
  • “Graph Neural Networks: From Spectral Graph Processing to Self-Attention and Beyond”, Invited Talk in the Seminar on AI Meets Complex Knowledge Structures, Oslo, Norway, 2023
• 2022
  • “Quantum Tensor Networks for Medical Image Analysis”, Guest Lecture at MSc course on Medical Image Analysis, UCPH, 2022
  • “Behavioural Analysis with Big Data and Deep Learning”, Guest Lecture at PhD course on Animal Models of Disease, UCPH, 2022
  • “Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas Using a Contrastively Learned Semantic Space”, Oral Presentation at Workshop on Biomedical Image Registration, 2022 (video)
  • “Machine Learning for Biomedical Image Analysis”, Guest Lecture at Center for Advanced Bioimaging Summer School, 2022
  • “Quantum Tensor Networks for Medical Image Analysis”, Centre for the Mathematics of Quantum Theory, University of Copenhagen, Denmark
• 2021
  • “Deep Learning for Medical Image Analysis”, Guest Lecture, Jönköping University, Sweden
  • “Exploring Sustainability of ML/AI, With Carbontracker as an example”, 50 year celebration event of Dept. of Computerscience, UCPH, Denmark
  • “ML for Chemistry”, Datascience for Chemistry PhD course, University of Copenhagen, Denmark
  • “Graph Neural Networks”, DIKU/DTU/AAU Summer School on Geometric Deep Learning, Vejle, Denmark (slides) (video)
  • ``Graph refinement based airway extraction”, University of Iowa (virtual)
  • ``Carbon footprint driven deep learning model selection for medical imaging”, MIDL 2021, (video)
  • ``Segmenting two-dimensional structures with strided tensor networks”, IPMI 2021, (video)
  • “Quantum Tensor Networks for Medical Image Analysis”, Frederich-Alexander University, Erlangen-Nuremberg, Germany (virtual) (slides) (video)
  • “Quantum Tensor Networks for Medical Image Analysis”, Weill Cornell Medicine and Cornell-IthacaUniversity, USA (virtual)
• 2020
  • “Extraction of Airways from volumetric data”, Radboud University Medical Center, The Netherlands, (slides)
  • “Uncertainty quantification in medical image segmentation using normalizing flows”, International workshop on Machine Learning in Medical Imaging, (MLMI 2020), (video)
  • “Tensor networks for medical image classification”, International conference of Medical Imaging with Deep Learning (MIDL 2020), (slides) (video)
  • “Machine learning for Medical Image Analysis”, Alumni Talk @ BMS Institute of Technology. Also at SIT, Tumkur (video)
  • “Inclusive AI”, Free Software Movement - Karnataka
• 2019
  • “Cell Imaging and Analysis using Machine Learning”, Summer School in Advanced Live Cell Imaging, UCPH
  • “Features for Image Analysis”, Danish Meteorological Institute (slides)
  • “Graph Refinement based Airway Extraction using Mean-Field and Graph Neural Networks”, Department of Computer Science, Aalto University School of Science (slides)
• 2018
  • “Extraction of airways from volumetric data”, PhD Defence, University of Copenhagen (slides)
  • “Graph Refinement using GNNs With a focus on Airway Extraction”, Erasmus Medical Center, Rotterdam (slides)
• 2017
  • “Segmenting Tree Structures with Probabilistic State-space Models and Bayesian Smoothing”, AMLab, University of Amsterdam (slides)
  • “Extraction of Airways from CT Data Using Bayesian Smoothing”, MICCAI Workshop on GRaphs in biomedicAl Image anaLysis, Quebec (slides)
• 2016
  • “Introduction to university pedagoy lecture on Pattern Recognition”, University of Copenhagen (video)
  • “Extraction of airway trees from CT data Using Multiple Hypothesis Tracking and Statistical Ranking of Template-matched Hypotheses”, MICCAI workshop on Pulmonary Image Analysis, Athens (slides)
• 2015
  • “Bayesian tracking of multiple point targets Using Expectation Maximization”, MSc defence, Chalmers University (slides)