Machine Learning Research Assistant

Yavar Pourmohamad, Ph.D. (Green Card holder) Cell: 986-***-****

Graduate Research Assistant at Boise State University Email: ****************@*.**********.***

I.ABOUT ME

Ph.D. candidate in Computing with a focus on Data Science. I apply machine learning and deep learning techniques to predict environmental hazards, such as wildfires and floods and etc, using large geospatial datasets and high-performance computing. My interdisciplinary background combines environmental engineering, remote sensing, and statistical modeling. In collaborative academic and consulting environments, I’ve led projects that deliver data-driven solutions to complex physical world problems, particularly related to climate-driven risk.

II.WORK EXPERIENCE

• Boise State University, Boise, ID, Graduate Research Assistant, 2021 – Present

As a Graduate Research Assistant at Boise State University, I collaborated within a multidisciplinary team to advance research on predicting wildfire ignition and associated risks. My responsibilities involve collecting, curating, and analyzing large-scale datasets, particularly the FPA FOD-Attributes dataset, to extract meaningful patterns and insights. I design and implement machine learning and deep learning models to support predictive analysis, leveraging both Windows and Linux environments. Additionally, I utilize high-performance computing (HPC) systems and cloud platforms (GCP, AWS) to scale data processing workflows and accelerate model training, ensuring efficient and reproducible research outcomes.

• Ferdowsi University of Mashhad, Iran, Postdoctoral Researcher, 2018 – 2020

My work focused on optimizing algorithms for estimating actual evapotranspiration, a critical component in hydrological modeling and water resource planning. I addressed complex, large-scale environmental challenges by developing and evaluating computational models tailored to real-world scenarios. This included creating detailed simulations and designing predictive scenarios to support sustainable water management strategies in arid and semi-arid regions.

• Hydrotech Toos Consulting, Iran, Hydrologist, 2012 – 2014

I contributed to several national and regional-scale projects aimed at enhancing Iran’s water management infrastructure. I played a key role in the development of the National Document of Water, providing technical input and modeling support. I was also involved in constructing the Groundwater Conceptual Model of the Neyshabur Basin, where I analyzed hydrogeological data to inform sustainable groundwater use.

III.EDUCATION

Boise State University, Boise, ID, 2025

Ph.D., Computing (Data Science)

Ferdowsi University of Mashhad, Iran, 2017

Ph.D., Water Engineering and Sciences

UCLA, Los Angeles, CA, 2016

Visiting Graduate Researcher

Sari Agricultural Sciences University, Iran, 2011

M.S., Water Engineering

Ferdowsi University of Mashhad, Iran, 2009

B.S., Water Engineering

IV.SOFTWARE SKILLS

Programming & Software: Python (Dask, CuDF, Scikit-learn, PyTorch, Keras), R, SQL, Google Earth Engine, QGIS, ArcMap

V.HONORS

Recipient of a $25,000 Joint Fire Science Program grant as Student Investigator, 2024

Submitted 6 national and international proposals as PI or co-PI in data science and environmental modeling

VI.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, February 24, 2025, Boise State News, Link.

VII.PUBLICATIONS (Google Scholar)

• First author/co-author on 14 peer-reviewed publications with extensive citations.

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