/filters:quality(90)/prod01/production-cdn-pxl/media/umassdartmouth/profiles/smast/221005-SIQI-LI.jpg)
faculty
Siqi Li '20, PhD he/him
Assistant Research Professor
SMAST / Fisheries Oceanography
Contact
508-999-8193
508-999-8197
tmj5Avnbtte/fev
Education
| 2022 | University of Massachusetts Dartmouth | PhD |
| 2012 | Ocean University of China | BS |
Teaching
Courses
Training in the use of the unstructured grid, Finite-Volume, Ocean Community Model (FVCOM). Lectures will cover dynamical principles used to develop advanced unstructured grid finite-volume ocean models with a focus on FVCOM, as well as practical training on how to configure FVCOM for various ocean application cases. The course consists of 13 lectures and 14 project assignments, which will be arranged weekly. Students will be expected to give a presentation summarizing their findings upon completion of each project. Additionally, the instructor will conduct virtual oral examinations with individual students to assess their achievements in the course.
An advanced treatment of a special topic in specific areas of marine sciences and technology with an emphasis on recent developments. The subject matter varies according to the interests of the instructor and the students.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Seminar discussions and presentations based on research or detailed literature surveys.
Research
Research awards
- $ 95,794 awarded by Town of Falmouth for Re-assessing the Environmental Impact of the Proposed Outfall from a Site off Kite Park, Falmouth, in Vineyard Sound
Research
Research interests
- Coastal ocean modeling
- Air-sea interaction
- River-ocean coupling
- Machine learning in oceanography
- Wind turbine wake modeling
Select publications
- Siqi Li, Changsheng Chen (2022).
Air-sea interaction processes during hurricane Sandy: Coupled WRF-FVCOM model simulations
Progress in Oceanography, 206, 102855. - Siqi Li, Changsheng Chen, Zhongxiang Wu, Robert C Beardsley, Ming Li (2020).
Impacts of oceanic mixed layer on hurricanes: A simulation experiment with Hurricane Sandy
Journal of Geophysical Research: Oceans, 125, e2019JC015851. - Changsheng Chen, Liuzhi Zhao, Scott Gallager, Rubao Ji, Pingguo He, Cabell Davis, Robert C Beardsley, Deborah Hart, Wendy C Gentleman, Lu Wang, Siqi Li, Huichan Lin, Kevin Stokesbury, David Bethoney (2021).
Impact of larval behaviors on dispersal and connectivity of sea scallop larvae over the northeast US shelf
Progress in Oceanography, 195, 102604. - Changsheng Chen, Liuzhi Zhao, Huichan Lin, Pingguo He, Siqi Li, Zhongxiang Wu, Jianhua Qi, Qichun Xu, Kevin Stokesbury, Lu Wang (2024).
Potential impacts of offshore wind energy development on physical processes and scallop larval dispersal over the US Northeast shelf
Progress in Oceanography, 224, 103263. - Zhengchen Zang, Rubao Ji, Yonggang Liu, Changsheng Chen, Yun Li, Siqi Li, Cabell S Davis (2022).
Remote silicate supply regulates spring phytoplankton bloom magnitude in the Gulf of Maine
Limnology and Oceanography Letters, 7, 277-285.
Dr. Siqi Li is an Associate Research Professor at the School for Marine Science and Technology (SMAST), University of Massachusetts Dartmouth. His research focuses on coastal ocean modeling, air-sea interaction, and the coupling of computational fluid dynamics (CFD) with geophysical fluid models such as FVCOM. He has contributed to multiple NOAA- and state-funded projects on topics including offshore wind farm impacts, scallop larval transport, and ocean model development. Dr. Li is also actively involved in developing next-generation modeling tools that integrate observations and machine learning with traditional numerical models.