I was the Instructor of Record for an undergraduate Landscape Ecology at Stony Brook University during the Fall 2023 semester. Prior to this, I was a Laboratory Teaching Assistant for the course over three semesters.

Course description: A computer lab course focusing on spatial concepts, methods, and tools for addressing ecological and environmental problems.  The course will be based on fundamental concepts in ecology and environmental science and extend that knowledge, as well as teaching technical skills, including the use of geographic information systems (GIS) software, image processing, spatially explicit modeling, and spatial statistics.  The lab exercises will introduce a variety of spatial approaches for addressing problems in environmental protection, ecotoxicology, natural resource management, conservation biology, and wildlife management.

You can view the syllabus here.

In May 2023, I developed and instructed an accelerated graduate-level Geographic Information Systems (GIS) course at Fordham University in New York.

Course description: Geographic information systems (GIS) are powerful tools for analyzing fundamental geographic questions. GIS involves generating, managing, linking, manipulating, and implementing data in many different formats. The most common way involves visualizing information in the form of two-, and sometimes three-, dimensional maps. This course will cover major topics in GIS with applications relevant to the broad fields of biology and the natural sciences, yet theories can easily be applied to economic development, urban planning, epidemiology, and many aspects of the anthropogenic world. The goal of this course is to teach students a level of GIS proficiency such that they will be self sufficient in their further learning and use of GIS. This course is an intense, five-day short course combining short lectures that will cover basic ideas and concepts, paired with longer, hands-on computer laboratory exercises that will provide experience learning the free, open-source GIS software QGIS.

You can view the syllabus here.

During the Spring 2023 and 2024 semesters, I was the Teaching Assistant for an undergraduate course at Stony Brook University in Statistics and Data Analysis. The course was instructed by Dr. Pascal Title, however I had the opportunity to give several lectures throughout the semester.

Course description:  A conceptually focused introduction to probability and data analysis emphasizing statistical literacy and critical thinking. Topics will include probability, t-tests, chi-squared tests, correlation, regression, and Analysis of Variance, as well as special topics of interest to undergraduate Biology majors such as case-control studies and meta-analysis. This course includes a one-hour recitation in which students will do hands-on activities, discuss papers from the primary literature, and gain experience with data analysis. 

You can view the syllabus here. 

Over the 2022 and 2023 summers, I ran a Research Methods and Professional Development Seminar through Stony Brook University's Institute for Advanced Computational Sciences' (IACS) NSF REU program: Data + Computing = Discovery!

In 2022, I ran the seminar entirely on my own, while in 2023 I was assisted for part of the seminar by Stony Brook PhD Candidate Catherine Feldman while I was away for field owrk.

Seminar description: This seminar aims to aid students in developing their communication skills (e.g., presenting, writing, networking), technical reading comprehension, and coding proficiency as professionals in their respective fields. Because students in this seminar are coming from a range of backgrounds with a wide breadth of interests, students are encouraged to think about how lessons learned during this seminar will allow them to grow and progress as scientists, science communicators, and professionals in their fields of interest.

You can view the 2022 and 2023 seminar syllabi here and here, respectively.