Graduate Mentor List

Mentors and projects!
Below is the list of graduate student mentors and a brief description of their research and opportunities to participate.  Please see the mentoring program page for details about the program format and goals.  This list is updated at the beginning of each semester (sometimes more frequently). If you are interested in a position, you can contact the graduate student directly, providing them with a brief introduction and a resume. You may also reach out to if you have any questions.
Graduate students: If you would like to update or add to this page, please contact Preston Thompson or Elise Heffernan at
Revisited August 2023

Who: Elise Heffernan,
1. This project is focused on primary research and seeks to complement my own boreal forest treeline research in the Arctic. A student would choose a topic (if possibly related to another major/minor, great!) and conduct primary research, create an annotated bibliography and write a report on the topic throughout the term. The goal is to get a broader, multidisciplinary understanding of my research area. The student will gain experience with primary source research and writing, and will have rather wide discretion in their chosen topics. I am particularly seeking students who are interested in social-environmental interactions.
2. This project focuses on running a boreal forest - tundra model across multiple sites in Alaska and Canada. Some coding experience would be beneficial (R or python) but we will teach you how to run the model so advanced students and those looking to increase their skills are welcome! We will work as a team and have many people running the model to get an array of simulations and outputs.
Openings: multiple

Who: Amanda Armstrong (
What: Allometry simulations using a Forest Model
The student will gain experience running a cutting edge forest model to simulate a forest in Virginia. We will compare how well the model does simulating trees with parameters measured in the field and taken from the literature as compared to parameters measured by ground-based lidar. The student will be running the model (python) and interpreting results (R). No coding experience necessary though at least exposure to coding preferred.
Forest Model Research
This research-based experience will involve a little bit of detective work. We will be developing a database of global forest model parameters, combing through literature and books to piece together in one place model parameterizations from around the globe. No modeling experience necessary.
Openings: 1-2 students
When: Spring 2023
How: Academic credit.

Who:  Mirella Shaban,
What:  The student will conduct research on literature relevant to near ground meteorology and permafrost dynamics in the Arctic. The student will be responsible for sourcing literature, writing brief literature reviews on the compiled sources, and presenting their findings bi-weekly. The student is expected to self pace and keep an organized bibliography of their sources and extracted information.
Openings: 1-2 students
When: Fall 2023 and Spring 2024
How: Academic credit and Volunteer

Who:  Kelsey Schoenemann,
I have LOTS of video data of bumble bee activity from hives that were located in different habitats. This project involves transcribing video data into spreadsheets and potentially using video analysis (i.e., scene change detection algorithms) to streamline the process. This work can happen remotely or in person.
Openings: 1-2 students
When: Fall 2023 and Spring 2024
How: Academic credit and Volunteer

Who: Stephanie Petrovick (
What: I have openings for at least one student doing one of two projects. One project involves germinating seeds in a greenhouse, with the seedlings needing to be checked once a week - depending on when the seedlings stop appearing, this could take the whole semester or only a couple months. It mostly consists of checking for seedling presence and identifying the species of those seedlings. Another project that I need help with includes sorting and weighing dried biomass samples. Biomass samples are sorted based on categories rather than individual plant species. Further work to supplement these activities, other than the end of semester report required by the program, could include other research/reading papers/data processing – this can be discussed and decided based on how much work the student would like to do.
When: Fall 2023 and Spring 2024
How: Academic credit

Who:  Mirella Shaban and MacKenzie Nelson
What: Hiring an undergraduate student with GIS experience to commit ~1-3 hours a week for sourcing data and mapping it in arcGIS. Research is centered around a remote Alaskan community. The student will be responsible for scouring the internet for GIS data and creating visualizations and analyses of the data with direction from the mentors. Students will mostly have creative freedom throughout this mentorship to explore relationships they are interested in within the data, with some guidance from the mentors when necessary.
Openings: 1 student
When: Fall 2023 (with possible extension into Spring 2024)
How: Academic credit and Volunteer

Who: Henry (
What:This project uses remote sensing to map forest mortality in the US Atlantic Coast using deep learning. The student would mainly be working on airborne images and generate an evaluation dataset for evaluating the deep learning model. It would be a nice introduction to remote sensing, image classification and machine learning. Students with a background in GIS would be helpful but is not necessary.
Openings: 2 students
When: Fall 2023 and Spring 2024
How: Academic credit.