Machine Learning Data Science

Yavar Pourmohamad

Green card holder

Boise, ID 986-***-****

****************@*.**********.***

www.linkedin.com/in/yavar-pourmohammad/

Education

Ph.D., Computing (emphasis in Data Science) 2021-2025

Boise State University (USA)

Ph.D., Water Engineering and Sciences (Natural Sciences) 2012 – 2017

Ferdowsi University of Mashhad (Iran)

Visiting Graduate Researcher 2015 – 2016

UCLA Henry Samueli School of Engineering (USA)

M.S., Water Engineering (Irrigation and Drainage) 2009 – 2011

Sari Agricultural Sciences and Natural Resources University (Iran)

B.S., Water Engineering and Sciences 2004 – 2009

Ferdowsi University of Mashhad (Iran)

Skills

Software capabilities

Python programming (dask, CuDF, etc)

R programming

MySQL

Java script (Google Earth Engine)

QGIS/ArcMap

Cloud Computing

Languages

English (Fluent verbal and written)

Farsi/Persian (Native)

Research Interests and Coursework

●Machine Learning (Scikit-Learn)

●Deep Learning (Pytorch & Keras)

●Remote Sensing

●Wildfire Risk

●Flood Risk

●Statistics

●Data Science

Hydrology Modeling

Work Experience

Boise State University – Computer Sciences Department:

●Graduate Research Assistant 2021 – Present

-Work in team environment to conduct research on predicting wildfire ignition and risk.

-Collect, develop and analyze big data [FPA FOD-Attributes].

-Create and develop Machine Learning and Deep Learning models.

-Capability to work with Windows, Linux based operating systems.

-Experience in using High Performance Clusters (HPC) and cloud computing.

●Teacher Assistant 2021 – Present

-Provide support for Computer Science students

Ferdowsi University of Mashhad – Water Sciences and Engineering Department:

●Postdoc Research 2017 – 2020

-Collaborated with research scientists and engineers on research projects

-Optimized actual evapotranspiration algorithm

-Evaluated real-world, large-scale problems and provided solutions

-Created model simulations, and developed scenarios for water management

●Adjunct Professor 2016 – 2021

-Instructed environmental students in a laboratory environment

-Taught students how to use lab tools, equipment, and setup the lab

Hydrotech Toos Consulting Office, Expert for following Projects:

●National Document of Water 2012 – 2014

●Ground Water Conceptual Model of Neyshabur Basin 2013 – 2014

●Designing of Pressurized Irrigation Systems 2012 – 2014

Proposals and funding

Awarded (1 proposal)

●Machine Learning Classification of Unknown Fire Causes in Western US, $25K, Student Investigator,

Joint Fire Science Program (JFSP)

Not awarded (6 proposals)

Workshops

●Model, understand, and visualize drivers of historical wildfire occurrences to predict and mitigate future ignitions, 4th, Southwest Fire Ecology Conference. Fall 2024.

●Machine Learning in Environmental Sciences, Water and Environmental Research Institute, Ferdowsi University of Mashhad. Summer 2022.

●WEAP (Water Evaluation and Planning), Khorasan and Mazandaran Regional Water Company. Fall and summer 2019.

Media Appearances

●An enhanced database helps predict wildfires, August 1, 2024, Northwest Public Broadcasting, Link.

●What sparks a wildfire? The answer often remains a mystery, January 17, 2025, Grist, Link.

●Machine learning sparks insight: Computing student identifies wildfire ignition sources, February 24, 2025, Boise State News, Link.

Peer-Reviewed Journals Articles (6 out of 13 papers) – Google Scholar

Pourmohamad, Y., Abatzaglou, J., Belval, E., Short, K., Fleishman, E., Prestemon, J., Shuman, J., Coleman, A., AghaKouchak, A., Seydi, S.T., Sadegh, M. 2025, Inference of Wildfire Causes from Their Physical, Biological, Social and Management Attributes. Earth’s Future, 13,e2024EF005187. https://doi.org/10.1029/2024EF005187

Seydi, S.T., Abatzaglou, J., AghaKouchak, A., Pourmohamad, Y., Mishra, A., Sadegh, M. 2024. Predictive Understanding of Causal Links between Vegetation and Soil Burn Severities Using Physics-informed Machine Learning. Earth’s Future, 12, e2024EF004873.

Pourmohamad, Y., Abatzoglou, J.T., Belval, E.J., Fleishman, E., Short, K., Reeves, M.C., Nauslar, N., Higuera, P.E., Henderson, E., Ball, S. and AghaKouchak, A., 2023. Physical, Social, and Biological Attributes for Improved Understanding and Prediction of Wildfires: FPA FOD-Attributes Dataset. Earth System Science Data Discussions, 2023, pp.1-29.

Modaresi Rad, A., Abatzoglou, J.T., Fleishman, E., Mockrin, M.H., Radeloff, V.C., Pourmohamad, Y., Cattau, M., Johnson, J.M., Higuera, P., Nauslar, N.J. and Sadegh, M., 2023. Social vulnerability of the people exposed to wildfires in US West Coast states. Science advances, 9(38), p.eadh4615.

Mianabadi, A., Salari, K. & Pourmohamad, Y. 2022. Drought monitoring using the long-term CHIRPS precipitation over Southeastern Iran. Applied Water Science, 12(8), pp.1-13.

Pourmohamad, Y., Ghandehari, A., Davary, K., & Shirazi, P. 2020. Multicriteria Decision-Making Approach to Enhance Automated Anchor Pixel Selection Algorithm for Arid and Semi-Arid Regions. Journal of Hydrologic Engineering, 25(11), 04020049.

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