My name is Nico Lang and I am an Assistant Professor of Computer Vision and Machine Learning for Earth Observation Data at the University of Copenhagen, associated with the Global Wetland Centre and the Pioneer Centre for AI. I am a core member of the Climate AI Nordics network, an ELLIS member, and I am involved in community efforts like the FGVC workshop at CVPR, the AICC and REO workshops at EurIPS, and the SSL4EO-2024 summer school. Before moving to Copenhagen for a Postdoc advised by Serge Belongie and Christian Igel, I received a PhD from ETH Zurich supervised by Konrad Schindler and Jan Dirk Wegner.

[Curriculum Vitae (CV)] [Headshot] [Bio]

Research
My research interests are in the area of computer vision, machine learning, and remote sensing and in developing new methods using these techniques to support environmental sciences. My PhD research focused on advancing the way we measure forest structure at global scales using publicly available satellite data. My current interests include uncertainty estimation in deep learning, novelty detection, and learning from imbalanced data, as these are omnipresent challenges that arise when working on real-world problems. I see great potential in the application of machine learning to address global environmental issues. My current research activities focus on three main topics (see also publications or scholar).

1. Representation learning for multimodal Earth observation data
keywords: multimodal, data fusion, self-supervised learning, implicit neural representations, “foundation models”
workshops: REO, SSL4EO
projects: MMEarth, MMEarth-Bench, SuperF

2. Global ecosystem modeling
keywords: vegetation canopy height, vertical structure, GEDI, aboveground biomass, biodiversity
workshops: AICC, CAIN-2026
projects: Global canopy height model, MMEarth-Bench

3. Fine-grained open-world recognition
keywords: fine-grained categorization, hierarchical labels, taxonomy, open-set recognition, novelty detection, category discovery
workshops: FGVC10, FGVC11, FGVC12, FGVC13, Visipedia 2024
projects: OpenInsect

Leisure
I enjoy spending my free time outdoors hiking and snowboarding, playing volleyball, and traveling where windy takes me kitesurfing. I play the drums and like making music with others.

News

• April 2026: Invited talk at the CVPR 2026 MONTI workshop.

• Mar 2026: We’re hiring a PhD at UCPH for the Global Wetland Center: PhD fellowship in Machine Learning for Environmental Sciences - Department of Computer Science (Deadline: April 06)

• Mar 2026: Recordings of our EurIPS 2025 REO workshop are released here.

• Feb 2026: New benchmark and preprint out: MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training

• Jan 2026: I’ll be an Area Chair for ECCV 2026

• Jan 2026: Paper accepted to ICLR 2026. Checkout the SuperF project page.

• Jan 2026: Invited keynote at the Open-Earth-Monitor Cyberinfrastructure (OEMC) Global Workshop 2026: “Next-Generation EO & GeoAI Built on Openness and Distributed Data”, 7–9 October 2026, Barcelona, Spain (hosted by CREAF and the OpenGeoHub Foundation).

• Jan 2026: I am an ELLIS member.

• Jan 2026: Co-organising the FGVC13 workshop at CVPR 2026.

• Jan 2026: Recordings of our EurIPS 2025 AICC workshop are released on the Climate AI Nordics channel here.

• Jan 2026: Invited keynote at the “ELLIS Winter School 2026: AI for Earth System, Hazards & Climate Extremes”. March 16 – 20, 2026, National Technical University of Athens (Greece)

• December 2025: New preprint: SuperF: Neural Implicit Fields for Multi-Image Super-Resolution. See the project page for the demo to super-resolve Sentinel-2 satellite images for any place on Earth.

• November 2025: Paper accepted to NeurIPS 2025 Dataset and Benchmark Track (Spotlight): Open-Insect: Benchmarking Open-Set Recognition of Novel Species in Biodiversity Monitoring. See project page for benchmark dataset and code.

• October 2025: Paper accepted in the journal Science of Remote Sensing: Drone imagery for roof detection, classification, and segmentation to support mosquito-borne disease risk assessment: The Nacala-Roof-Material dataset. Data and code on the project website.

• September 2025: I’ll be an Area Chair for CVPR 2026

• September 2025: EurIPS is coming to Copenhagen and we got two exciting workshops accepted: AICC: Workshop on AI for Climate and Conservation and REO: Advances in Representation Learning for Earth Observation (Call for participation deadlines Oct 10/Oct 15).

• September 2025: The Pioneer Centre for AI (short P1) launched the P1 programs initiative. I am co-directing the P1 program on AI for Climate & Conservation.

• September 2025: Invited as a panelist to the “Nordic-Alan Turing Institute AI Research Workshop & Embassy Network Event” in Oslo.

• September 2025: Invited to give a seminar talk at Wageningen University & Research (WUR), visiting Prof. Ioannis Athanasiadis.

• August 2025: Invited talk at the D3A conference deep dive session: From Pixels to Products: CV in Danish Research & Industry

• June 2025: Invited keynote at the OpenGeoHub summer school “Data Science for Earth observation” in Wageningen. I will also give a lecture on self-supervised learning.

• May 2025: Giving three talks (here is a short summary post) at: ESA-NASA International Workshop on AI Foundation Model for EO, 2025 Nordic Workshop on AI for Tackling Climate Change, and SCIA workshop on Challenges in Analysis of Large Image Data.

• April 2025: I joined the core team of the Climate AI Nordics network. Please join us!

• April 2025: Paper accepted to CVPR 2025: Taxonomy-Aware Evaluation of Vision-Language Models.

• March 2025: I started a new position as an Assistant Professor at the Computer Science Department at University of Copenhagen. In this new role I join the Global Wetland Centre, that studies the greenhouse gas balance of global wetlands.

• Jan 2025: Co-organising the FGVC12 workshop at CVPR 2025.

• January 2025: SSL4EO-2024 summer school recordings are released. A brief review with all resources in this blog post.

• December 2024: Paper accepted to NLDL 2025 published in PMLR: Familiarity-Based Open-Set Recognition Under Adversarial Attacks

• December 2024: Invited talk at IIRS for the winter course BigAI for BigGIS.

• November 2024: I also joined Bluesky here: @nicolang.bsky.social. Interesting starter packs to consider: Deep Learning for Earth Observation 🌎 | AI for Conservation | AI and Ecology | Computer Vision 1 & Computer Vision 2 by @csprofkgd.bsky.social | Belongie Lab

• November 2024: Invited talk at DHI about representation learning for Earth observation data.

• November 2024: Joined the research network Climate Change AI Nordics. Invited to give a talk at the 1st workshop on May 13: 2025 Nordic Workshop on AI for Tackling Climate Change.

• November 2024: Invited talk at the DHI.

• September 2024: Invited talk at the LifeCLEF 2024 workshop.

• August 2024: ECCV workshop paper accepted to CV4E: Multimodal Fusion Strategies for Mapping Biophysical Landscape Features

• June 2024: ECCV paper accepted: Labeled Data Selection for Category Discovery. TLDR: Category discovery is improved by selecting labeled data that is neither too similar nor too different to the unlabeled categories.

• June 2024: ECCV paper accepted: MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning. TLDR: We created “MMEarth”, a global dataset with 12 aligned modalities at 1.2M locations to explore multi-modal pretext tasks for learning representations for Sentinel-2 images.

• June 2024: We are organizing a summer PhD course on SSL4EO: Self-Supervised Learning for Earth Observation at University of Copenhagen. Looking forward to a week full of interesting talks and discussions. Registration is open, seats are limited.

• June 2024: Invited talk at the AI2 Environmental seminar series, Seattle.

• May 2024: Working with Lucia Gordon from Harvard University during a summer visit to the Pioneer Centre for AI.

• May 2024: New preprint: MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning. TLDR: We created “MMEarth”, a global dataset with 12 aligned modalities at 1.2M locations to explore multi-modal pretext tasks for learning representations for Sentinel-2 images.

• May 2024: Invited as a panelist to the ML4RS workshop at ICLR 2024 in Vienna.

• April 2024: I am visiting Oisin Mac Aodha’s group at University of Edinburgh for a two weeks research visit as part of a strategic partnership grant between UoE and KU.

• April 2024: I co-organized the Visipedia workshop 2024 at the Pioneer Centre for AI. More info about the Visipedia project can be found here.

• March 2024: Paper accepted to CVPR 2024: From Coarse to Fine-Grained Open-Set Recognition. TLDR: We investigate the role of label granularity, semantic similarity, and hierarchical representations in open-set recognition with a new benchmark based on iNat2021.

• January 2024: I am co-organizing the 11th Workshop of the Fine-Grained Visual Categorization accepted to CVPR 2024 in Seattle.

• September 2023: Journal paper accepted in Nature Ecology and Evolution: A high-resolution canopy height model of the Earth. Our project website links all related resources (data, code).

• September 2023: Workshop paper accepted on “Familiarity-Based Open-Set Recognition Under Adversarial Attacks”. It will be presented at The 2nd Workshop and Challenges for Out-of-Distribution Generalization in Computer Vision during ICCV 2023.

• September 2023: Invited talk at the RISE Research Institutes of Sweden Learning Machines Seminars. The recording of the talk and the lively discussion is online. [video]

• September 2023: New journal publication in Science Advances led by Siyu Liu: The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe.

• July 2023: I am very happy to receive the Culmann Prize that recognizes outstanding doctoral theses.

• June 2023: I joined the CVPR23 “house band” as a drummer in Vancouver.

• May 2023: New journal publication in Nature Food led by Nikolai Kalischek: Cocoa plantations are associated with deforestation in Côte d’Ivoire and Ghana.

• May 2023: I am honored to have been named one of the outstanding reviewers for CVPR 2023.

• May 2023: Invited talk at AI for Good: “Global vegetation monitoring with probabilistic deep learning”. [video] [slides]

• December 2022: I am excited to co-organize the “FGVC10: The 10th Fine-Grained Visual Categorization” workshop which was accepted to CVPR 2023 in Vancouver. CALL FOR PAPERS: Interested in fine-grained learning and its applications? Consider submitting your paper to FGVC10. Deadline: March 20, 2023.

• December 2022: German national TV “ARD” presents our research on global canopy height mapping in the quiz show “Wer Weiss Denn Sowas”. Watch the episode here (at 7:45 min).

• September 2022: I moved to Copenhagen and started as a Postdoc at the University of Copenhagen, where I am associated with the new Pioneer centre for AI. I am co-advised by Serge Belongie and Christian Igel.

• June 2022: My doctoral thesis is now online: Mapping Vegetation Height — Probabilistic Deep Learning for Global Remote Sensing. Here are the slides from my defense.

• May 2022: Swiss national TV “SRF” reports on our research in the news program “10 vor 10”: «Living Planet Symposium» mit Schweizer Beteiligung.

• May 2022: I defended my PhD! Big thanks to all the great people supporting me on this journey. I posted a picture of my amazing hat on twitter here.

• May 2022: Got invited to speak at the at ML for Remote Sensing virtual discussion group organized by Hannah Kerner and Patrick Clifton Gray. See their schedule here.

• May 2022: Our research has been covered by several news articles from NVIDIA, NASA, NBC. See the list of links under “Media”.

• April 2022: ETH News reported about our research: Neural network can read tree heights from satellite images.

• April 2022: New preprint available: A high-resolution canopy height model of the Earth; and a new project website to access the demo and data.

• February 2022: I got invited to give a seminar talk to the Alan Turing Institute Environment and Sustainability Special Interest Group.

• January 2022: I got invited to give a talk at Google’s Geo for Good Lightning Talks Series #6: Forest & Nature.

• October 2021: Our paper together with the NASA GEDI mission is published in the journal Remote Sensing of Environment.

• October 2021: Our research project Automated Large-scale High Carbon Stock Estimation from Space was selected to be featured at the AI+X Summit organized by the ETH AI Center.

• August 2021: I got invited to give a Radio interview at Swiss Radio SRF1 about our research in a program called “The measurement of forests”. Die Aufzeichnung der Sendung “Treffpunkt” zum Thema: Die Vermessung der Wälder (Swiss German).

• July 2021: Our research got featured on the High Carbon Stock Approach (HCSA) website: Publicly available indicative High Carbon Stock Forest maps for Malaysia, Indonesia, and the Philippines

• June 2021: Mongabay covered our research in a news article: Chocolate giant funds high resolution carbon map to protect forests

• May 2021: News article by Barry Callebaut: Artificial intelligence against deforestation

• January 2021: We were interviewed by RESET: “EcoVision Lab Is Mapping Biomass for the Good of the Planet” (German, English translation)

• May 2020: News article by ETH Zürich Industry Relations: A global tool against deforestation

• August 2019: I wrote a Medium post summarizing my first journal paper as first author: Deep learning reconstructs forests in 3D using only satellite images and initiated the Medium publication of the EcoVision Lab.

• March 2019: The U.V. Helava Award for best paper 2018 in ISPRS Journal of Photogrammetry and Remote Sensing (with Jan D. Wegner, Konrad Schindler, and Steve Branson, David Hall, Pietro Perona from the Caltech Computational Vision Group)

• October 2018: I am an associate PhD fellow of the Max Planck ETH Center for Learning Systems (CLS)

• August 2016: I am visiting Prof. Pietro Perona’s Computational Vision Lab at Caltech for my interdisciplinary project. I am supported by a travel grant from the Erich-Degen Stiftung (ETH Zürich).