Science Research Experience Program
The Science Research Experience Program (REx) invites a select cohort of student scholars to move beyond textbooks and classrooms — joining research teams engaged in real scientific inquiry.
Through close mentorship and hands-on investigation, REx students gain authentic experience in the process of discovery. In their junior year, accepted scholars work with faculty mentors to refine their interests and secure summer placements at leading academic and professional labs across the country. When they return as seniors, they present their findings through a formal research paper and academic poster session.
REx scholars have contributed to advanced research across disciplines, including:
- Protein Design and Antibiotic Resistance Using Mass Spectrometry – University of Pennsylvania
- Understanding Language Recovery After Strokes – Johns Hopkins University
- The Role of Internal Variability and Greenhouse Gas Forcing on Arctic Sea Ice Trends – Princeton University
- Molecular Representation of Behavioral Differences in Memory Rescue – Columbia University
- Dual-Catalyzed Hydroalkylation Reaction to Produce Molecules – Duke University
- The Epidemiology of Depression – Harvard University
See the 2025 REx Scholars in Action
Jillian Flynn ’26
Rutgers New Jersey Medical School
In Dr. Veronika Miskolci’s lab at Rutgers University, Flynn studied how the immune system responds to injury and infection, using zebrafish as a model organism. Using specialized microscopy, she watched immune cells in action, observing how factors such as anesthesia and metabolism affect their movement and responses during inflammation and wound healing. Flynn also worked with genetically modified zebrafish whose fluorescent immune cells made them visible under the microscope, helped maintain the lab’s zebrafish colony, and analyzed video data to understand how immune cells coordinate repair in real time.
Jacobo Garcia-Carrillo ’26
Centro Láser, Universidad Politécnica de Madrid
Under Dr. Miguel Morales at Universidad Politécnica de Madrid, a leading engineering university in Madrid, Spain, Garcia-Carrillo explored how ultrafast lasers can permanently transform the surface of metals like titanium and steel to create color without pigments. By fine-tuning pulse frequency, wavelength, and focus, he examined how oxidation and light interference generate stable, tunable color gradients at the microscopic level. Garcia-Carrillo later applied the same precision to laser-scribing photovoltaic cells, studying how subtle changes in ablation depth influence conductivity and overall efficiency.
Beth He ’26
National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory
At NOAA’s Geophysical Fluid Dynamics Laboratory, under Dr. Xiao Liu, He studied oxygen loss in the California Current using data from biogeochemical Argo floats. She analyzed how temperature, salinity, pH, and chlorophyll shape low-oxygen zones that threaten marine life. Using machine learning, He built a random forest model to predict oxygen variability and tested how sampling frequency and location affected accuracy. Her findings, which she’s preparing to submit to the Harvard National Science Research Competition, help refine how scientists monitor oxygen loss and track ocean health.
Max Levy ’26
Yale School of Medicine
In Dr. Diyendo Massilani’s lab at Yale University, under the supervision of Dr. Michael James Boyle, Levy studied traces of ancient human DNA preserved in soil from a Stone Age site in Mongolia. Working in a cleanroom, he extracted and purified genetic material, prepared DNA libraries, and isolated human sequences from environmental samples. The project is part of the lab’s effort to use ancient DNA to map how early human populations migrated, adapted, and evolved across Eurasia. By analyzing genetic fragments invisible to the naked eye, Levy helped uncover connections between people separated by tens of thousands of years.
Daniel Rozenblat ’26
NYU Langone Health
In Dr. Eric Oermann’s lab at NYU Langone Health, which studies both human and artificial intelligence, Rozenblat worked on projects using large language models to improve clinical decision-making. The lab’s goal is to understand how AI can enhance, rather than replace, human reasoning in medicine. Using Python and NYU’s high-performance computing cluster, he tested how prompt design affects model behavior, aiming to reduce distraction while maintaining diagnostic accuracy on medical datasets. Rozenblat’s work contributed to a forthcoming paper and advanced research on AI systems that learn not only from data, but from the way clinicians think.
Kristine Wang ’26
University of Pennsylvania, Perelman School of Medicine
At UPenn’s Perelman School of Medicine, under Dr. Clementina Mesaros and postdoctoral researcher Dr. Hennrique Taborda Riba, Kristine Wang studied Friedreich’s Ataxia, a rare neurodegenerative disease that disrupts fat metabolism in cells. Using mass spectrometry, she measured carnitine levels in frataxin-deficient samples and gained experience in cell culture, lipid extraction, and protein quantification. Wang’s experiments contributed to ongoing efforts to understand the disease’s metabolic effects and offered insight into how small biochemical changes can have far-reaching effects.
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