My name is Nico Lang and I am a Postdoc at the University of Copenhagen associated with the Pioneer centre for AI, where I am co-advised by Serge Belongie and Christian Igel. I received my PhD from ETH Zurich, where I was working in the EcoVision Lab that is part of the Photogrammetry and Remote Sensing (PRS) group under the supervision of Prof. Konrad Schindler and Prof. Jan Dirk Wegner.
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 interests also include uncertainty estimation in deep learning, anomaly 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.
During my Bachelor’s degree in Geomatics and Planning at ETH Zurich, I discovered my fascination for machine learning and computer vision in the context of geospatial data science. Before continuing with my Master in Geomatics at ETH Zurich, I started an internship in computer vision at upicto, a start-up from the Computer Vision Lab at ETH, and continued it at Logitech, as upicto was acquired during my time there.
Following the work started during an early academic visit to Prof. Pietro Perona’s Computational Vision Lab at Caltech, I worked on deep learning approaches to monitor urban trees from street-level images. During my Phd I’ve had the chance to collaborate with the NASA GEDI mission, the Swiss Federal Institute for Forest, Snow and Landscape Research WSL, as well as with companies and institutions outside academia: Barry Callebaut, High carbon stock Approach (HCSA), Hunziker, Zarn und Partner (HZP), and MeteoSwiss.
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.
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).