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Dr. Yu Han | Optical remote sensing | Best Researcher Award

Scientific Assistance | Institute of Geodesy and Photogrammetry, ETH Zurich | Switzerland

🧑‍🔬 Yu Han is an accomplished scientist with expertise in geomatic engineering, focusing on multimodal multispectral LiDAR technologies. Currently, Yu is completing his Doctor of Science at ETH Zurich, contributing significantly to optical metrology and remote sensing. His academic journey and professional experiences have been marked by notable achievements and innovations in LiDAR systems.


Google Scholar


Yu Han has pursued an illustrious academic career:

Doctor of Science in Geomatic Engineering from Swiss Federal Institute of Technology in Zurich (ETH Zurich), Switzerland (10/2019 – 03/2024). His thesis focuses on “Material probing using multimodal multispectral LiDAR based on a femtosecond laser supercontinuum.”

Master of Science in Optics and Photonics from Karlsruhe Institute of Technology (KIT), Germany (10/2016 – 07/2019), with an outstanding GPA of 1.1/1.0. His master’s thesis was on “Modeling and simulation of aperture effects in coherent light detection and ranging systems.”

Bachelor of Engineering in Information Display and Opto-Electronic Technology from the University of Electronic Science and Technology of China (UESTC), China (09/2012 – 07/2016), graduating with a GPA of 3.93/4.0. His bachelor’s thesis investigated the “Thermal effect induced by the laser incident on a liquid crystal phase array.”


Yu Han has gained extensive professional experience in both academic and industrial settings:

  • Scientific Assistant and Doctoral Student at ETH Zurich, Switzerland (10/2019 – 03/2024). He designed, developed, and built a multimodal multispectral LiDAR prototype, implemented data processing algorithms, and contributed to various projects in optical metrology and remote sensing.
  • Working Student for Master Thesis at Robert Bosch GmbH, Germany (11/2018 – 05/2019), where he simulated and modeled light propagation in MATLAB for FMCW LiDAR and analyzed the impacts of various factors on its performance.
  • Student Assistant at KIT, Institute of Photonics and Quantum Electronics (IPQ), Germany (06/2018 – 08/2018), focusing on fabricating optical elements for 3D photonic integration.
  • Internship at the Research Center for Information Technology (FZI Forschungszentrum Informatik), Germany (08/2017 – 10/2017), working on modeling temperature distribution in retinal layers caused by incident laser beams.

Research Interests

Yu Han’s research is centered around:

  • Multimodal multispectral LiDAR systems.
  • Optical metrology and remote sensing.
  • Spectroscopy and polarimetry.
  • Machine learning for sensor data processing.


Yu Han’s academic excellence and contributions have been recognized with several awards:

  • Scholarship from Carl Zeiss AG for his Master’s program (2018 – 2019).
  • Excellent Graduate of UESTC (2016).
  • Annual scholarships for being in the top 5% of students (2012 – 2015).
  • Best Competitor in school CUPT competition (China Undergraduate Physics Tournament) (2013).


  1. A feature selection method for multimodal multispectral LiDAR sensing
    ISPRS Journal of Photogrammetry and Remote Sensing, 2024.
    Cited by: Researchers exploring advanced LiDAR sensing techniques
  2. Remotely sensing inner fruit quality using multispectral Lidar: estimating sugar and dry matter content in apples
    Computers and Electronics in Agriculture, 2024.
    Cited by: Studies on agricultural applications of remote sensing.
  3. Classification of material and surface roughness using polarimetric multispectral LiDAR
    Optical Engineering, 2023.
    Cited by: Research on material classification using LiDAR.
  4. Comb-based multispectral LiDAR providing reflectance and distance spectra
    Optics Express, 2022.
    Cited by: Innovations in LiDAR technology.
  5. Polarimetric femtosecond-laser LiDAR for multispectral material probing
    SPIE Photonics Europe, 2022.
    Cited by: Advances in femtosecond-laser applications in LiDAR.



Yu Han | Optical remote sensing | Best Researcher Award

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