Our Team
Dr. Benjamin Misiuk
Principal Investigator
My primary research interest is on geospatial environmental modelling. I am keenly interested in empirical methods for mapping surficial geology at the seafloor. During my Ph.D. and postdoctoral fellowships I have developed geospatial models for predicting substrate parameters at locations throughout the northwest Atlantic and eastern Canadian Arctic. I am working on the development and application of emerging machine and deep learning techniques to improve our capacity to map the seafloor. I also work on acoustic data analysis, species distribution modelling, and benthic habitat mapping projects. Geospatial data visualization via the cartographic presentation of model predictions is extremely interesting to me and I aim to uphold the highest cartographic standards in my research group.
Farnoosh Heidary
PhD student
My interest lies in developing deep and machine learning techniques for image processing and remote sensing, with a focus on solving environmental monitoring challenges. In 2025, I embarked on my Ph.D., transitioning my expertise in image analysis to enhancing sonar backscatter data for seabed mapping. Before this, I built extensive experience in geospatial modeling and advanced image processing, emphasizing data quality improvement and extracting meaningful insights from complex datasets. My research is dedicated to addressing challenges such as denoising, de-speckling, and artifact removal, while ensuring rigorous validation to create reliable and innovative tools for marine mapping and environmental monitoring.
Brenna Bales
MSc student
I am a passionate marine scientist and conservationist originally from Austin, Texas. I spent my undergraduate years at the University of Miami, where I interned for three years with the Shark Research and Conservation lab tagging wild sharks under the mentorship of Dr. Neil Hammerschlag and Steve Cain. There, I completed my undergraduate thesis investigating blood plasma protein reference intervals in nurse sharks. This experience fueled my fascination with marine megafauna and set the stage for a diverse career at the intersection of science, outreach, and conservation. After my academic pursuits, I ventured to the waters of the Hawaiian Islands and later the Maldives, merging science and tourism through the conservation of sharks, sea turtles, and coral reefs. My commitment to protecting marine ecosystems then took me to New England, in the United States, where I immersed myself in various offshore industries. As an observer, I collected data on marine life in contexts such as commercial fishing and geophysical surveying. Beyond science, I find joy in exploring the world as an expatriate, relishing the thrill of freediving, savoring spicy cuisines, and trying to pet every dog I meet.
Ali Asghar Rostami
PhD student
I am a researcher specializing in geospatial data fusion, GIS, and machine learning applications for environmental and water resource management. My academic journey has been shaped by my expertise in surface and ground water hydrology, flood modeling, water quality assessment, and the integration of remote sensing and AI-driven approaches for environmental monitoring. Prior to my PhD, I worked extensively with hydrological modeling, flood vulnerability mapping, and predictive analytics for heavy metal indices in drinking water. My research focuses on seafloor composition modeling in Atlantic Canada, integrating geospatial datasets for enhanced environmental monitoring. I primarily focus on geospatial modeling of the seafloor, specifically using statistical methods to map seafloor surficial geology. My research involves predicting key substrate parameters, such as sediment grain size, through advanced geospatial models. I am particularly excited about the application of emerging machine learning and deep learning techniques, which will enhance our ability to model seafloor characteristics with greater accuracy. By leveraging my background in geospatial modeling, particularly in seabed sediment mapping, I seek to advance methodologies that improve our understanding of marine environments and predictive capabilities.