My background is in biological oceanography. I have a B.A. in biology from Cornell University, an M.S. in marine and atmospheric science from SUNY Stony Brook, and a Ph.D. in biological oceanography from the joint program between MIT and the Woods Hole Oceanographic Institution. I worked as a postdoctoral research scientist on two different projects. In the first, I collaborated with scientists form the University of the Virgin Islands to find out whether the cooler waters of deeper reefs might provide corals with a refuge from the bleaching events that are happening more frequently in shallow waters as a result of our warming climate. In the second project, I was part of a team that coupled an ocean circulation model with a particle-tracking model to understand the population connectivity of blue crabs in the Gulf of Mexico. We also investigated whether the 2010 Deepwater Horizon oil spill might have overlapped with the dispersal pathways of blue crab larvae that were drifting near the ocean surface at the time of the spill.
Both projects involved working with large datasets. In the first, I had a ten-year-long time series of temperature measured every 15 minutes at 32 coral reefs. In the second, I was tracking the hourly dispersal of 2,000,000 particles for 60 days, which resulted in data on the scale of a Terabyte. I saw the tremendous challenges and opportunities involved in working with large datasets. I decided that I needed more tools to analyze and visualize big data, and I wanted to learn more ways to use data to make predictions. That motivated me to enroll in the program here at UNH.
In the future, I would like to apply my new skills beyond the realm of academia. I am especially interested in working on intellectually challenging projects with a mission to make the world a better place, whether by improving environmental sustainability, promoting social justice, or providing new opportunities to disadvantaged people, for example.
As part of my coursework, I am collaborating with a team of UNH scientists to harness the power of predictive analytics and machine learning to analyze voluminous data being collected by sophisticated, high-frequency sensors in a network of New Hampshire streams and rivers. My role is to create an artificial neural network that will predict the volume of water that rivers discharge on different time scales, and to predict changes in stream chemistry (dissolved organic matter and nitrate concentrations). We expect the results to broaden our understanding of environmental processes and to give us a new tool for managing watersheds in near-real time.
What have you found valuable about the M.S. program thus far?
Today, anyone can access a multitude of online courses on every subject, from statistics to programming languages to machine learning and beyond. But to me, what makes the UNH Analytics program more valuable than an online course is the people. My classmates have incredibly diverse backgrounds. Some are fresh out of college, others have worked in industry for years. Their fields include sports, healthcare, marketing, biological sciences, insurance, IT, music, culinary operations, and more. I have learned so much from their unique perspectives and experiences. My professors are outstanding. They present material in highly engaging ways. They cultivate ties with local businesses, which provides us with amazing opportunities for networking and for gaining hands-on experience through practicum projects. They are attuned to the latest and greatest algorithms and analysis tools, and they teach them to us as soon as they are released. They help us strengthen not just our technical skills, but also skills like presentation, leadership, collaboration, negotiation, and conflict resolution. I always get the sense that they are fully invested in our success.
Joanna has co-authored 9 research papers in peer-reviewed scientific journals, 2 technical reports, and a book chapter. Her work is accessible on ResearchGate
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