Hi, I'm Nora!

I'm a PhD student at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) in computer science working on AI for Earth. My goal is to use AI for good and make the Earth a better place. Within my PhD studies, I am working with my supervisors Dr.-Ing. Vincent Christlein, Dr. Thorsten Seehaus, Prof. Dr.-Ing. habil. Andreas Maier, and Prof. Dr. Matthias Braun on interdisciplinary projects combining Computer Vision and Remote Sensing. My main focus lies on the segmentation of glacier calving fronts in Synthetic Aperture Radar (SAR) satellite imagery.

Publications

PASAL: Progress- and sparsity-aware loss balancing for heterogeneous dataset fusion

Thomas Gorges, Teresa Scholz, Stefan Saloman, Mathias Zinnen, Juliane Hoffmann, Nora Gourmelon, Andreas Maier, Sebastian Hettenkofer, Vincent Christlein
Information Fusion Vol. 120
code

Contextual HookFormer for Glacier Calving Front Segmentation

Fei Wu, Nora Gourmelon, Thorsten Seehaus, Jianlin Zhang, Matthias H. Braun, Andreas Maier, Vincent Christlein
IEEE TGRS Vol. 62
code

Out-of-the-box calving front detection method using deep-learning

Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes Fürst, Matthias H. Braun, Vincent Christlein
The Cryosphere Vol. 17
code, demo

AMD-HookNet for Glacier Front Segmentation

Fei Wu, Nora Gourmelon, Thorsten Seehaus, Jianlin Zhang, Matthias H. Braun, Andreas Maier, Vincent Christlein
IEEE TGRS Vol. 61
code

Conditional Random Fields for Improving Deep Learning-Based Glacier Calving Front Delineations

Nora Gourmelon, Julian Klink, Thorsten Seehaus, Matthias H. Braun, Andreas Maier, Vincent Christlein
IGARSS 2023

Caffe - A Benchmark Dataset for Glacier Calving Front Extraction from Synthetic Aperture Radar Imagery

Nora Gourmelon, Thorsten Seehaus, Julian Klink, Matthias H. Braun, Andreas Maier, Vincent Christlein
IGARSS 2023

Calving fronts and where to find them: a benchmark dataset and methodology for automatic glacier calving front extraction from synthetic aperture radar imagery

Nora Gourmelon, Thorsten Seehaus, Matthias H. Braun, Andreas Maier, Vincent Christlein
ESSD Vol. 14
data, code

Implications of Experiment Set-Ups for Residential Water End-Use Classification

Nora Gourmelon, Siming Bayer, Michael Mayle, Guy Bach, Christian Bebber, Christophe Munck, Christoph Sosna, Andreas Maier
Water Vol. 13
data

Implications of Experiment Set-Ups for Residential Water End-Use Classification

Nora Gourmelon, Siming Bayer, Michael Mayle, Guy Bach, Christian Bebber, Christophe Munck, Christoph Sosna, Andreas Maier
ECWS 2020
data

Talks and Presentations

2024
  • Moderation of the discussion group "AI x Sustainability" at the AI Grid Summit, Berlin, November 13
  • "A Battle of AIs and Whether a Human Would Win," Pattern Recognition Symposium Winter 2023/24, March 15
  • "AI for Earth," Invited talk at the Julius-Maximilians-Universität Würzburg, January 22
2023
  • Research presentation for the German Federal Minister of Education and Research Bettina Stark-Watzinger at the Digital Gipfel 2023, November 21
  • Science Pitch at the Digital Gipfel 2023, November 20
  • "AI-based Remote Sensing Applications," Invited talk at the symposium "Artificial Intelligence for Life", Hochschule für angewandte Wissenschaften Weihenstephan-Triesdorf, October 20
  • "Glacier Monitoring with Computer Vision Models," Invited talk at the AI, Machine Learning and Data Science Meetup, Voxel51, October 5
  • "Biodiversity and Glacier Monitoring," Invited Talk at the Green AI seminar as part of the Public Climate School, FAU, May 10
  • "Automatisierte Seevogelerfassung in Luftbild-Videos," Invited talk at the workshop "KI statt IQ? - Potenziale und Herausforderungen des KI-Einsatzes in der Vogelbeobachtung und im Vogelmonitoring," German Federal Agency for Nature Conservation, Vilm, January 31
2022
  • "Deep learning-based Calving Front Delineation" and "Bird Monitoring Using Computer Vision Techniques," Invited talk at the Green AI seminar, FAU, November 9
  • "Denoising SAR Imagery for Deep Learning-based Calving Front Segmentation," Machine Learning for Polar Regions Workshop, Columbia University in the City of New York, June 17
  • "The Birds" and "Calving Fronts and Where to Find Them," Invited Talk at the Green AI seminar, FAU, May 5
2021
  • "Gletscherfronten und wo sie zu finden sind," Invited talk at the symposium "Artificial Intelligence for Life", Hochschule für angewandte Wissenschaften Weihenstephan-Triesdorf, October 22
  • "Glacier Fronts and Where to Find Them," Pattern Recognition Symposium, July 22
  • "Application Area Water (in Different Physical States)," Pattern Recognition Symposium, February 18

Conference Abstracts

2024
2023
2022
2021

Posters

2024
  • "Calving Fronts and Where to Find Them - A Benchmark Framework", AI Grid Summit 2024, Berlin, November 12 – November 13
  • "SSL4SAR – Self-Supervised Learning for Synthetic Aperture Radar Imagery", Pattern Recognition Symposium, July 16
  • "Calving Fronts and Where to Find Them - A Benchmark Framework", International Computer Vision Summer School 2024, Baia Samuele, Italy, July 8 – July 12
2023
  • "Calving SAM", Pattern Recognition Symposium, July 11
  • "Conditional Random Fields for Post-processing Deep Learning-based Glacier Calving Front Delineations", Pattern Recognition Symposium, March 7
2022
  • "Calving Fronts and Where to Find Them: A Multi-Task Model for Automatic Glacier Calving Front Extraction from SAR Imagery", Cryosphere 2022, Reykjavik, Iceland, August 22 – August 26
  • "Trainable Bilateral Filters for Everybody", Pattern Recognition Symposium, July 27
  • "The Birds", Pattern Recognition Symposium, March 9
2021
  • "Calving Front Detection in SAR Images using Deep Learning Techniques", #GeoWoche2021, Arbeitskreis Fernerkundung, October 8

Awards

2024 On t3n's list of nominees for AI Person of the year
2023 AI-Newcomer 2023 in the field of natural and life sciences
2023 Member of AI Grid
2022 Best Poster Award for the poster: "The Birds", Pattern Recognition Symposium, March 2022
2021 Master Prize for outstanding achievements in the Master's thesis: "End-use Classification Using High-Resolution Smart Water Meter Data"
2020 Best Paper Award at the 5th International Electronic Conference on Water Sciences in the session "Water Resources Management and the Ecosphere Resilience and Adaptation" for the paper: N. Gourmelon, S. Bayer, M. Mayle, G. Bach, C. Bebber, C. Munck, C. Sosna, and A. Maier: "Implications of Experiment Set-Ups for Residential Water End-Use Classification", ECWS, 2020

Education

July '24 Summer School, International Computer Vision Summer School (ICVSS), "Computer Vision in the Age of Large Language Models", Baia Samuele, Italy
Since 2022 Fellowship, FAU, Measuring and Modelling Mountain Glaciers and Ice Caps in a Changing Climate (M³OCCA)
Since 2020 Ph.D. Student, FAU, Pattern Recognition Lab (PRL)
Aug. '19 - Dec. '19 Semester abroad, Norges teknisk-naturvitenskapelige universitet (NTNU), Trondheim, Norway
2018 - 2020 M.Sc. Computer Science, FAU, Grade: very good (with honors)
  • Master's thesis: End-use Classification Using High-Resolution Smart Water Meter Data
  • Specialization: Pattern recognition
  • Minor: Geology
Mar. '18 Scholarship, Fulbright, "Leaders in Entrepreneurship" Program at the Louisiana State University (LSU), Baton Rouge, Louisiana, USA
Sep. '16 - Dec. '16 Semester abroad, Saint Mary`s University (SMU), Halifax, Canada
2016 - 2020 Scholarship, Max Weber program of the Free State of Bavaria
2014 - 2018 B.Sc. Computer Science, FAU, Grade: very good (with honors)

Professional Experience

Nov. 2020 - Today Academic Researcher, FAU, PRL
  • Several years of experience in deep learning, image processing, and computer vision
  • Teaching experience in computer science and medical engineering
  • Mentoring experience (Bachelor und Master students)
  • Interdisciplinary work with the geography department and the German Federal Agency for Nature Conservation
Jan. '20 - Oct. '20 Working student, Diehl Metering GmbH
Jan. '17 - Feb. '17 Trainee, Alfred-Wegener-Institute, Helmholtz Center for Polar and Marine Research
2015 - 2018 Scientific assistant, FAU
  • Research assistant at the Chair for System Simulation (2018)
  • Tutor of "Algorithms of continuous systems" (2017)
  • Research assistant at the Chair in Hardware-Software-Co-Design (2015)

Academic Experience

Teaching & Mentoring

Projects
  • Project Remote Sensing (Summer term '22 - Winter term '24/25)
Exercises
  • Introduction to Machine Learning (Winter term '21/22)
  • Medizintechnik II (Summer term '21)
Mentoring
  • Master's Theses
    • Geospatial Foundation Models for Glacier Front Delineation (Running)
    • Semi-Supervised Learning for Glacier Front Delineation
    • Calving Fronts and How to Segment Them Using Diffusion Networks
    • Design and Evaluation of Machine Learning Applications for Space Systems
    • Multi-Task Learning for Glacier Segmentation and Calving Front Detection with the nnU-Net Framework
    • Identification and Detection of Birds Using Deep Learning and Aerial Imagery
    • Incorporating Time Series Information into Glacier Segmentation and Front Detection using U-Nets in Combination with LSTMs and Multi-Task Learning
    • Image Segmentation via Transformers
  • Bachelor's Theses
    • EcoScapes: LLM-powered advice for crafting sustainable cities
    • Evaluation of a Pixel-wise Regression Model Solving a Segmentation Task and a Deep Learning Model with the Matthew’s Correlation Coefficient as an Early Stopping Criterion
    • Evaluation of a Modified U-Net with Dropout and a Multi-Task Model for Glacier Calving Front Segmentation
  • Projects
    • Time Series Calving Front Snakes
    • Transformer-based Contrastive Unsupervised Learning for Glacier Segmentation
    • Uncertainty Estimation for Transformer-based Glacier Segmentation
    • Evaluation of an Attention U-Net for Glacier Segmentation
    • Evaluation of an Optimized U-Net for Glacier Segmentation
    • Evaluation of a Bayesian U-Net for Glacier Segmentation
    • Temporal Information in Glacier Front Segmentation Using a 3D Conditional Random Field
    • Evaluation of Different Loss Functions for Highly Unbalanced Segmentation

Involved Research Projects

2023 - 2026 "Large-scale Automatic Calving Front Segmentation and Frontal Ablation Analysis of Arctic Glaciers using Synthetic-Aperture Radar Image Sequences" (LASSI), DFG, Role: Ph.D. student
2022 - 2026 "Measuring and Modelling Mountain Glaciers and Ice Caps in a Changing Climate" (M³OCCA), Elite Network of Bavaria, International Doctorate Program, Role: Ph.D. student (2022 - 2023), Affiliate (2023 - 2026)
2019 - 2022 "Tapping the Potential of Earth observations" (TAPE), FAU, Emerging Fields Initiative, Role: Ph.D. student (since 2020)
Glacier

Voluntary Work

  • Founding Member of the PRL's Mental Health Team (since 2022)
  • Founding Member of the PRL's Equality Team (since 2022)
  • Representation of the Doctoral Students in the Steering Committee of the International Doctorate Program M³OCCA (since 2022)
  • Member of the Selection Committee of the Max Weber Program (since 2021)
  • Reviewer for Journals (number of reviewed articles)
    • The Cryosphere (3)
    • IEEE Transactions on Geoscience and Remote Sensing (3)
    • International Journal of Applied Earth Observation and Geoinformation (2)
    • Ecological Informatics (1)
    • Scientific Reports (1)
  • Presentation of own work (talks, demos, and posters) at the Long Night of Sciences
  • Part of the organizing team of the Local Conference of Youth (LCOY) - Young Climate Conference Germany 2019

Press & Media