Student Profile

Graduate student profile: Maria Emilia Mazzolenis

Helping SEAS combine data science with ethics

Harvard SEAS graduate student Maria Emilia Mazzolenis wearing a black and white dress standing in front of the Science and Engineering Complex next to a tree

Maria Emilia Mazzolenis, S.M. '24, in data science (Eliza Grinnell/SEAS)

Maria Emilia Mazzolenis knows that to change a system, you first must understand it. Want to understand the needs of your fellow graduate students? Join a graduate advisory committee. Want to know what students are actually learning in their classes? Become a teaching fellow. Want to learn about the entrepreneurial world? Join a startup. Want future students to study the ethical implications of their research? Take on a new fellowship focused on changing the curriculum.

“I am deeply committed to the causes I believe in, and devoting my time and energy to them has been immensely rewarding,” said Mazzolenis, who’s about to finish her master’s degree in data science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). “That’s allowed me to contribute to reshaping the integration of ethics into technical education, which has the potential to impact the next generation of data and machine learning scientists, and is something I’m really honored to be working towards.”

Originally from Buenos Aires, Mazzolenis arrived at SEAS after majoring in economics and psychology at the University of North Carolina at Chapel Hill. Her first exposure to data science and machine learning came as an undergraduate, and she quickly realized data science was the right field for her graduate degree. She joined the SEAS master’s program almost immediately after graduating UNC.

“The program was the perfect combination of my interdisciplinary interests, and having access to the Harvard-MIT community proved to be incredibly beneficial,” said Mazzolenis, who’s cross-registered as a grad student in computer science at MIT. “The program had rigorous technical training, but also a focus on real-world applications. I knew that research was highly emphasized at SEAS, and I’d been drawn to research since I was a child. It all seemed like a great fit in terms of my academic and professional interests.”

It didn’t take long for Mazzolenis to become a student leader. In her first semester, she became an Institute for Applied Computational Science Social Fellow and co-leader of an admissions and funding initiative for the Graduate Advisory Committee (GAC) on Diversity, Inclusion, and Leadership in Applied Computation. The following spring, she became co-chair of the GAC.

“In order to truly make an impact, you have to know who you’re working with, have contact with students, and understand the intricacies of the technical curriculum,” she said.

The summer after her first year at SEAS, Mazzolenis gained a new level of understanding of the importance of socially conscious technical training. She was selected for the Fellowships at Auschwitz for the Study of Professional Ethics, a program dedicated to examining contemporary professional ethics through an exploration of how technologists and engineers enabled and executed Nazi policies. She returned to campus with an even greater passion for the intersection of ethics and data science.

“I think everyone is aware that machine learning has immense potential to shape the world, but we can’t forget that shaping the world also comes with responsibilities,” she said. “As data scientists, if we’re not actively thinking about the impact that our actions can have, it can feel like we’re just coding behind a computer screen, disconnected from real-world implications and applications. We need to consider that our code can have an impact, both positive and unfortunately negative, in our community, the people we hope to help, and even on those who we were not originally thinking about.”

Harvard SEAS graduate student Maria Emilia Mazzolenis wearing a black and white dress standing in front of the Science and Engineering Complex

While at SEAS, Maria Emilia Mazzolenis has been an Institute for Applied Computational Science Social Fellow, co-chair of the Graduate Advisory Committee, an AI Ethics Pedagogy Fellow, and teaching fellow in both advanced data science and data science master's capstone project classes (Eliza Grinnell/SEAS)

Last fall, Mazzolenis became an AI Ethics Pedagogy Fellow at SEAS. Combined with her roles as a teaching fellow in both an advanced data science class and the data science capstone project course, she’s directly influenced how ethics are integrated into data science classes.

“I’m working on adapting the curricula we present students,” she said. “I’m starting from the ground up, and I am identifying essential ethical concepts we need to address, spanning societal, environmental, technical, and legal considerations. I’m collaborating closely with key stakeholders to ensure the class content and assignments cover both technical and ethical concepts.”

Mazzolenis’s own research initiatives have covered a range of topics. For a capstone project, her team examined the role online questionnaires and data from wearable technology can play in predicting suicidal ideation. She’s also researched the ways in which healthcare professionals may influence their patients’ decisions to continue or discontinue in vitro fertilization treatment depending on how they communicate the probabilities of treatment outcomes derived from machine learning models. She’s also collaborating with doctors at Massachusetts General Hospital to evaluate the current state of machine learning applications for studying chronic pain and headaches, and she is also acting as the principal investigator in training for a research project that uses computer vision for healthcare-related applications.

“Machine learning and data science are extremely applicable to a wide variety of disciplines, which is what drew me to them,” Mazzolenis said. “A lot of the research that I do is at the intersection of machine learning and psychology, healthcare, or economics. I’m able to integrate those areas because of the progression of my academic path.”

Wherever her professional career goes next, she knows SEAS has prepared her for success.

“The program was indeed challenging, but it helped me grow as a machine learning engineer, a researcher, and as a person,” she said. “I’ve made a lot of connections with people in the program, professors, administrators, and other professionals in the field. SEAS has not only equipped me with technical skills but also fostered a sense of leadership and innovation that will certainly guide me in my professional and personal life.”

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