Talks and posters
Keynote talk
- Conference: Machine Learning Conference for X-Ray and Neutron-Based Experiments, Garching, Germany (2024)
- Generative machine learning for scattering and spectroscopy data analysis
Invited talks
- Conference: Chemical Compound Space Conference, Heidelberg, Germany (2024)
- TBA
- Conference: Conference: Machine Learning Modalities for Materials Science, Ljubljana, Slovenia (2024)
- TBA
- Seminar: DTU NanoLab, Copenhagen, Denmark (2023)
- AI in Science: Transforming Communication, Data Analysis, and Laboratory Practices
- Seminar: Materials Innovation Factory, Liverpool, United Kingdom (2023)
- Towards Automated Structure Analysis of Nanoparticles
- Seminar: European Spallation Source Data Management and Software Centre, Copenhagen, Denmark (2022)
- Using Generative Adversarial Networks to match experimental and simulated inelastic neutron scattering data
Talks
- SMART Meeting, DTU (2023)
- Machine helping the Chemist - Towards Automated Modelling of Pair Distribution Function Data
- Best talk award to PhD Seminar, Department of Chemistry, UCPH (2022)
- Machine helping the Chemist - Towards Automated Modelling of Pair Distribution Function Data
- UK Neutron & Muon Science and User Meeting (NMSUM) (2022)
- Using Generative Adversarial Networks to match experimental and simulated inelastic neutron scattering data
- SMART Student Meeting (2022)
- Machine helping the Chemist - Towards Automated Modelling of Pair Distribution Function Data
- SMART Lighthouse PhD Summer School (2021)
- Machine helping the Chemist - Towards Automated Modelling of Pair Distribution Function Data
- Danscatt Annual Meeting (2019)
- Formation mechanism of metal oxido clusters: A complex modelling study using PDF and SAXS
- Nanoscience Symposium (2018)
- Formation mechanism of metal oxido clusters: A complex modelling study using PDF and SAXS
Posters chosen
- MLG - 16th International Workshop on Mining and Learning with Graphs (2020) (Paper published at workshop)
- Characterising the atomic structure of mono-metallic nanoparticles from x-ray scattering data using conditional generative models
- ADD - 16th Analysis of Diffraction Data in Real Space (2019) (Poster gold medal)
- Formation mechanism of metal oxido clusters: A complex modelling study using PDF and SAXS
- EMRS – European Materials Research Society (2019)
- Formation mechanism of metal oxido clusters: A complex modelling study using PDF and SAXS
- ISIS Student Meeting (2021) (Poster gold medal)
- Using Generative Adversarial Networks to match experimental and simulated inelastic neutron scattering data
- CHEAC Lighthouse Retreat (2021) (Poster medal)
- Automated Characterization of the Atomic Structure of Mono-Metallic Nanoparticles from X-ray Scattering Data using Generative Models
Posters
- 6th AI in Chemistry Symposium (2023)
- DeepStruc: Towards structure solution from pair distribution function data using deep generative models
- Summer school on human-in-the-loop and learning with limited labels (2022)
- DeepStruc: Towards structure solution from pair distribution function data using deep generative models
- Epdic17 (2022)
- DeepStruc: Towards structure solution from pair distribution function data using deep generative models
- Conference on High Entropy Alloy Electrocatalysis (2022)
- DeepStruc: Towards structure solution from pair distribution function data using deep generative models
- MaRDA Annual Meeting (2022)
- Using Generative Adversarial Networks to match experimental and simulated inelastic neutron scattering data
- Harwell NextGen ‘Celebration of Science’ Poster Competition (2021)
- Using Generative Adversarial Networks to match experimental and simulated inelastic neutron scattering data
- PhD Seminar - Department of Chemistry, University of Copenhagen (2021)
- Formation mechanism of metal oxido clusters: A complex modelling study using PDF and SAXS
- Innovative Inelastic Neutron Scattering Workshop (2021)
- Using Generative Adversarial Networks to match experimental and simulated inelastic neutron scattering data
- MAX IV User Meeting (2021)
- Extracting Structural Motifs from Pair Distribution Function Data of Nanostructures using Interpretable Machine Learning
Danscatt Annual Meeting (2017, 2018 & 2020)
AIinChem - 3rd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry (2020)
AIForPANS – Artificial Intelligence Applied to Photon and Neutron Science conference (2019)
- Inorganic Graduate Student Seminar (2018 & 2019) (Poster Gold Medal 2019)