Maria Shumskaya, Ph.D.

Welcome!

I’m Maria Shumskaya, an Associate Professor of Biological Sciences at Kean University, where I teach Biochemistry, Bioinformatics, and Plant/Fungi Science and lead an active research program in plant biochemistry, fungal ecology, and metabolomics.

My scientific journey began with a Ph.D. in Plant Biochemistry and Physiology from the Russian Academy of Sciences, followed by postdoctoral work in Sweden, Japan, and the United States, exploring molecular biology, biochemistry, and mechanisms by which plants and fungi adapt to their environments. Today, my laboratory investigates the molecular ecology of fungi in dead wood using tools such as next‑generation sequencing, community analysis, bioinformatics, and LC–mass spectrometry to understand how these organisms interact with each other and with their environments.

My recent projects include work on dead‑wood fungi, and fungal DNA barcoding in undergraduate education. My publication record spans plant biochemistry, metabolic engineering, molecular ecology, and microbial stress responses.

I am also the principal investigator of a National Science Foundation–funded project exploring biological insecticides originating from fungi, specifically Phellinus tremulae, a fungus naturally avoided by insects. This three‑year NSF project aims to uncover  insect‑repelling compounds using an integrated workflow of metabolomics, computational modeling, and molecular analysis, while creating hands‑on research opportunities for both undergraduate and high‑school students.

My teaching philosophy is simple: evidence, critical thinking, and curiosity. I encourage my students to engage deeply with scientific questions and to develop the analytical mindset essential for careers in modern biology. I designed several Open Education Resources for classes in bioinformatics for undergraduate students, you can check them here:

NMDS to Study Dead Wood Fungi Communities in Parks of New Jersey

Introduction to nucleotide sequence analysis and protein modeling in MEGA and PyMol using coronavirus SARS-CoV-2

Statistics with epidemiology of COVID-19

Thank you for visiting my site. I invite you to explore my research, publications, and ongoing projects, and to connect if you are interested in collaboration, student research, or science outreach.