Campus Directory

Pronouns He/him

Division Physical & Biological Sciences Division

Department/College/Unit Institute of Marine Sciences

Title Postdoctoral Scholar

Affiliation Staff

Web Site

Primary Office Location Remote work location

Mail Stop No Mailstop

Biography, Education and Training

Dr. Brandyn Lucca is a Postdoctoral Scholar as a part of the Fisheries Collaborative Porgram in collaboration with the Southwest Fisheries Science Center, where he leverages over a decade of experience as a scientific software developer and modeler. His work focuses on the intersection of fisheries acoustics, theoretical physics, and open-source tool development. Before joining the Fisheries Collaborative Program, he was a Postdoctoral Scholar at the Applied Physics Laboratory at the University of Washington and earned his Ph.D. and M.Sc. in Marine and Atmospheric Science from Stony Brook University.

Brandyn is the lead developer of several scientific packages, including echopop and acousticTS, designed to bridge the gap between complex physical modeling and high-throughput data processing. With over 225 days of experience at sea, he brings a practical, field-tested perspective to his computational work, ensuring that theoretical models translate effectively to real-world oceanographic challenges.

Summary of Expertise

• Fisheries acoustics and spatiotemporal modeling: Developing and validating theoretical scattering models for biological taxa and habitat classification.

• Applied Field Research: Broad experience bridging theoretical acoustics with practical application, supported by over 200 days of sea-going research.

• Open-source software development: Extensive experience in R, Python, MATLAB, C++, and Julia for signal processing, statistics, numerical optimization, data visualization, and documentation/API maintenance.

Research Interests

My research involves developing theoretical acoustic scattering models to represent diverse taxa within the water column. I am particularly interested in using remote sensing, statistical modeling, and machine learning to automate habitat classification and quantify the spatiotemporal distributions of marine life. A core component of my work is the democratization of these methods through the development of open-source software that supports biological inversion and high-throughput data processing.

Teaching Interests

• Scientific computing & reproducibility: Software Carpentry workshops covering R, Python, and Version Control (Git).

• Bioacoustics & signal processing: Theoretical and applied acoustics in marine environments.

• Marine ecology: Field-based labs, boat-based data collection, and habitat characterization.

• Open science practices: Workflows for open-source package development, documentation, and collaborative coding.

Selected Publications

Lee W., Staneva, V., Setiawan, L., Mayorga, E., Tuguinay, C., Butala, S., Lucca, B.M., and Lei, D. 2024. Echostack: A flexible and scalable open-source software toolbox for echosounder data processing. Proc Python Sci Conf, 386-397. https://doi.org/10.25080/WXRH8633

 Lucca B.M. and Warren J.D. 2024. Experimental target strength measurements of pteropods and shrimp emphasize the importance of scattering model inputs. ICES J Mar Sci, 81: 1345-1361. https://doi.org/10.1093/icesjms/fsad211

Lucca B.M., Ressler P.H., and Warren J.D. 2023. Individual sub-Arctic target strength measurements have frequency-dependent differences relative to scattering model predictions. J Acoust Soc Am, 154: 3374-3387. https://doi.org/10.1121/10.0022459

Besnard L., Lucca B.M., Shipley O.N., Croizier G.L., Octavio Rincon R.O.M., Sonke J., Point, D., Galván-Magaña F., Kraffe, E., Kown S.Y., and Schaal, G. 2023. Mercury isotope clocks predict coastal residency and migration timing of hammerhead sharks. J Anim Ecol, 60: 803-813. https://doi.org/10.1111/1365-2664.14384

Lucca B.M., Ressler P.H., Harvey H.R., and Warren J.D. 2021. Variations in sub-Arctic krill material properties, lipid composition, and other scattering model inputs affect acoustic estimates of their population. ICES J Mar Sci, 78: 1470-1484. https://doi.org/10.1093/icesjms/fsab045

Lucca B.M. and Warren J.D. (2019). Fishery-independent estimates of Atlantic menhaden (Brevoortia tyrannus) in the coastal waters south of New York. Fish Res, 218: 229-236. https://doi.org/10.1016/j.fishres.2019.05.016

Lucca B.M. and Warren J.D. (2018). Acoustically-measured distribution and abundance of Atlantic menhaden (Brevoortia tyrannus) in a shallow estuary in Long Island, N.Y. Estuaries Coast, 41: 1436-1447. https://doi.org/10.1007/s12237-018-0367-x