Hai Lin
Professor of Data analysis for environmental modelling
- Name
- Prof.dr.ir. H.X. Lin
- Telephone
- +31 71 527 7460
- h.x.lin@cml.leidenuniv.nl
- ORCID iD
- 0000-0002-1653-4854
Lin obtained his PhD from Delft University of Technology in 1993. After graduation (ir.) in Applied Mathematics at Delft University of Technology.
Professional Experience
Lin obtained his PhD from Delft University of Technology in 1993. After graduation (ir.) in Applied Mathematics at Delft University of Technology. He worked at TNO in Rijswijk from 1986 to 1990. In 1990 he joined the Department of Applied Mathematics of Delft University of Technology. Dr. Lin has many years of research experience in mathematical modelling and high performance computing. In recent years his research interests shifted to parallel numerical algorithms, modelling and simulation of large scale systems. Examples of ongoing research projects include improving the forecast of volcanic ash (cloud) transport with data assimilation, and studying the impact of wind- and solar energy to the stability of electrical power grid.
Present position
Prof.dr.ir. Hai Xiang Lin will share his knowledge in mathematical modelling and high performance computing with other researchers of CML. He will actively cooperate with the Leiden Centre of Data Science (Prof.dr. Jaap van den Herik) and LIACS. Given his main appointment in Delft and having a chair now at CML will strongly support the further development of the Leiden-Delft-Erasmus Centre for Sustainability. Furthermore, he is visiting professor of the University of Chinese Academy of Sciences and Shandong University, and has been collaborating with a number of universities in China for many years.
Professor of Data analysis for environmental modelling
- Science
- Centrum voor Milieuwetenschappen Leiden
- CML/Industriele Ecologie
- Li K., Ward H., Lin H.X. & Tukker A. (2024), Economic viability requires higher recycling rates for imported plastic waste than expected, Nature Communications 15: 7578.
- Chen Z., Kleijn R. & Lin H.X. (2023), Metal requirements for building electrical grid systems of global wind power and utility-scale solar photovoltaic until 2050, Environmental Science and Technology 57(2): 1080-1091.
- Wang S., Homem de Almeida Correia G. & Lin H.X. (2022), Assessing the potential of the strategic formation of urban platoons for shared automated vehicle fleets, Journal of Advanced Transportation 2022: 1005979.
- Fang L., Jin J., Segers A., Lin H.X., Pang M., Xiao C., Deng T. & Liao H. (2022), Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China, Geoscientific Model Development 15(20): 7791-7807.
- Wang S., Homem de Almeida Correia G. & Lin H.X. (2022), Modeling the competition between multiple Automated Mobility on-Demand operators: an agent-based approach, Physica A: Statistical Mechanics and its Applications 605: 128033.
- Verkaik J., Hughes J.D., Walsum P.E.V. van, Oude Essink G.H.P., Lin H.X. & Bierkens M.F.P. (2021), Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument, Environmental Modelling and Software 143: 105092.
- Verkaik J., Engelen J. van, Huizer S., Bierkens M.F.P., Lin H.X. & Oude Essink G.H.P. (2021), Distributed memory parallel computing of three-dimensional variable-density groundwater flow and salt transport, Advances in Water Resources 154: 103976.
- Lin H.X., Jin J. & Herik H.J. van den (2019), Air quality forecast through integrated data assimilation and machine learning. Rocha A., Steels L. & Herik H.J. van den (Eds.), Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART 2019. ICAART 2019: 11th International Conference on Agents and Artificial Intelligence 19 February 2019 - 21 February 2019 no. 2: SCITEPRESS. 787-793.
- Dias Rodrigues J.F., Yuan R. & Lin H.X. (2019), The expectations of and covariances between carbon footprints, Economic Systems Research 32(2): 192-201.
- Ye L., Lin H.X. & Tukker A. (2019), Future scenarios of variable renewable energies and flexibility requirements for thermal power plants in China, Energy 167: 708-714.
- Ye L., Rodrigues J.F.D. & Lin H.X. (2017), Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016, Applied Energy 203: 495-505.
- Rossum A.C., Lin H.X., Dubbeldam J. & Herik H.J. van den (2016), Nonparametric Segment Detection. Pearce D. & Pinto H.S. (Eds.), STAIRS 2016. STAIRS 2016 29 August 2016 - 2 September 2016 no. vol. 284 Frontiers in Artificial Intelligence and Applications. Amsterdam: IOS Press. 203-208.
- Rossum A. van, Lin H.X., Dubbeldam J. & Herik H.J. van den (2016), Nonparametric Bayesian Line Detection - Towards Proper Priors for Robotic Computer Vision. Marisco M. de, Baja G.S. di & Fred A. (Eds.), Proceedings 5th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2016). IPCRAM 2016 24 February 2016 - 26 February 2016. Rome: Scitepress. 119-127.
- Onderwijs en Onderzoek