Meet the 2026 Seoul Research Program faculty, part 1: seven STEM professors
Seven STEM professors from Harvard, Oxford, Northwestern, Caltech, Columbia and UChicago: what each course covers, who it suits, and what to know before you start.
Programs & Faculty
Can a wearable sensor catch the early signs of a health problem? Why can two events that start from similar conditions end so differently? How does the brain make sense of uncertain information from its surroundings? Questions like these run through the STEM courses of CRI's 2026 Seoul Research Program.
The 2026 lineup included fourteen professors. This first part of a two-part series covers the seven who teach science, technology, engineering and math: who they are, what each course covers, who it suits, sample research questions, and the fields each one opens up.
What the courses have in common
None of these courses is a lecture series. Each is built around student research and runs more like a university seminar than a class: students read the literature, tackle a question in teams, and finish with a research paper and an academic poster. What differs is the preparation each professor expects, from high school biology to first-year university math.
Professor
University
Focus
Background expected
Samuel Kunes
Harvard University
Memory and brain plasticity
High school biology
Robin Murphy
University of Oxford
Neuroscience of mental health
No psychology needed; suits quantitative, logical thinkers
Nabil Alshurafa
Northwestern University
Wearable sensors and mobile health
High school biology; coding or electronics a plus
Brian Stoltz
Caltech
Organic chemistry and synthesis
Interest in chemistry and lab work
George Tselioudis
Columbia University
Observing Earth by satellite
Required: basic linear algebra, calculus and differential equations
Anastasia Romanou
Columbia University
Numerical modeling
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Required: first-year university linear algebra, calculus and differential equations
Haifeng Xu
University of Chicago
Algorithms and agentic AI
Recommended: math fundamentals and basic programming, such as Python
Samuel Kunes, Harvard: the biology of memory
Samuel Kunes, a professor of molecular and cellular biology at Harvard University, teaches how memories form and how the brain changes with experience, seen through molecular biology. His course treats the brain as one biological system, following learning and memory from genes and synapses to neural circuits and on to diseases such as Alzheimer's. It runs as a research seminar: students read the literature themselves and debate it.
High school biology is enough to take part. The course suits students drawn to neuroscience who are considering brain science or medicine, especially those who would rather do research than sit through lectures, and anyone curious how events inside a cell connect to behavior.
Research questions in the course include:
How do interactions between genes and environment affect memory decline?
How does stress in a learning environment affect brain development?
Teams finish with a paper and poster, an early look at biomedical research for students headed toward neuroscience, medicine or the life sciences.
Robin Murphy, Oxford: the neuroscience of mental health
Robin Murphy, a professor of experimental psychology at the University of Oxford, teaches Behavioural and Cognitive Neuroscience for Human Psychopathology. The course treats brain and mind as a system that adapts to its environment, combining experimental psychology, neurobiology and computational models. Students examine how learning, prediction errors and decision-making shape behavior, and how breakdowns in those systems can surface as depression, anxiety or schizophrenia. Each team then analyzes a psychiatric topic through a neuroscientific model.
No prior psychology is required. The course fits students interested in psychology, brain science or psychiatry who like bringing mathematical and logical reasoning to human behavior. Because it also covers modeling brain function on a computer, students drawn to cognitive science or AI will find plenty to work with.
Sample questions:
How does the brain process uncertain information from its environment?
How do different cognitive systems respond to stress?
Students design an experiment, analyze the data, and write up a paper and poster. The work points toward clinical psychology, neuroscience and cognitive science, and later toward mental health or AI-driven brain research.
Nabil Alshurafa, Northwestern: wearable sensors and mobile health
Nabil Alshurafa, a Northwestern University professor whose work spans medicine and engineering, teaches Behavioral Medicine and Bioengineering in Mobile Health. His subject is mobile health, or mHealth: systems that use biosignals and lifestyle data from wearable sensors to monitor health and prevent disease. The course runs in two phases. Students first design and build sensors that measure signals such as heart rate, activity and stress, then analyze the data they collected for insights into preventive medicine.
It is a strong match for students aiming at biomedical engineering, computer science or pre-med who pair high school biology with a liking for coding or electronics. The work is hands-on and project-driven, so it rewards students who enjoy building devices and solving problems creatively, and those curious about health startups and digital health.
Questions from the syllabus:
How do environmental factors such as air pollution affect the body's signals?
How could a wearable device detect early signs of a health problem?
Teams form a hypothesis, build a sensor system, collect and analyze data, and produce a paper and poster, gaining hands-on research experience that connects directly to biomedical engineering, digital health and preventive medicine. Some students have taken that work further: four teams from his 2025 class had abstracts accepted as posters at IEEE BSN, the International Conference on Body Sensor Networks. Their story is on our Student Success page.
Brian Stoltz, Caltech: organic chemistry at work
Brian Stoltz, a professor of chemistry at Caltech, teaches Organic Chemistry: Structure, Reactivity, and Synthesis. Students learn the field's core ideas, such as molecular structure and reaction mechanisms, and apply them to real chemical systems: the roles organic molecules play in materials, energy and medicine, and how catalysis and stereochemistry can make synthesis cleaner and more efficient. Alongside the lectures, each group chooses a system to research, such as polymer degradation or green chemistry, then writes a paper and presents a poster.
The course fits students interested in chemistry, biotechnology or materials engineering, especially those drawn to polymers, medicinal chemistry or the lab. Its steady move from theory to application helps future pre-med students and would-be drug developers see the bigger picture, and its treatment of green chemistry speaks to students who want to tackle environmental problems.
Example topics:
How does a synthetic polymer's structure affect how it breaks down in the environment?
How can catalysts make organic synthesis more efficient and less wasteful?
Groups work through a literature review and experimental design in search of creative answers, such as a greener chemical process. It is groundwork for university lab research and for careers in pharmaceuticals and advanced materials.
George Tselioudis, Columbia: watching Earth from space
George Tselioudis teaches applied physics at Columbia University and is a senior research scientist at NASA's Goddard Institute for Space Studies (GISS). He has also contributed to the UN's IPCC climate reports.
His course, Observing Earth's Environment from Space, treats the planet as one complex system and shows how satellites track the interactions among atmosphere, ocean, land and ice. Students learn the principles behind it, including black-body radiation, the motions of Earth and Sun, and satellite sensor technology, then analyze satellite data on climate change, resource management and natural disasters. In the research seminar, each team chooses one environmental system, such as a climate pattern or air pollution, and builds a group project around satellite observations of it.
The course requires a grounding in linear algebra, calculus and differential equations, so students with solid math and physics have an edge. It suits future climate scientists, aerospace engineers and environmental engineers, and anyone eager to work with satellite imagery or GIS tools.
Sample questions:
What long-term climate trends show up in satellite records?
How do aerosols affect cloud formation, and how does that relate to extreme weather?
Along the way, students learn to process satellite data and, like working researchers, test models against observations. Teams present their paper and poster at a conference-style poster session, good preparation for climate science, environmental engineering or satellite data analysis.
Anastasia Romanou, Columbia: numerical models
Anastasia Romanou teaches applied mathematics at Columbia University and has conducted climate research with NASA and the US Department of Energy. Her course, Numerical Models and Applications, shows how numerical models describe systems of every kind, in physics, climate science and geophysics but also in economics, finance, the life sciences and the social sciences. Students learn numerical methods for differential equations, stability analysis and machine-learning-based models, and practice building computer models of real phenomena. Each team takes one modeling topic from literature review to implementation to analysis, ending with a paper and poster.
The prerequisites are first-year university linear algebra, calculus and differential equations. This is a course for students at ease with mathematical tools and keen on programming, whether their strength is math, computer science, physics or engineering. Because its examples range from climate models to economic ones, it also rewards broad interests, including in the scientific uses of big data and machine learning.
Sample questions:
How do numerical climate models simulate the interaction between atmosphere and ocean?
In a complex system, why can events that start from similar conditions lead to different outcomes?
Students design numerical experiments, analyze the results, and weigh their model's limits and uncertainties. That full research cycle is a solid base for meteorology, computational science, financial engineering and other fields built on quantitative modeling.
Haifeng Xu, UChicago: algorithms and agentic AI
Haifeng Xu is a professor of computer science and data science at the University of Chicago whose research centers on algorithms and artificial intelligence. His course, Algorithms & Agentic AI, uses algorithms, data analysis and AI as tools for understanding the complex systems of modern society, from economic activity and digital platforms to the flow of information and human decision-making. Teams take on a real-world problem, write a paper and present a poster.
The course is recommended for students with a math foundation and basic programming skills, such as Python. It suits logical problem solvers curious about AI agents and reinforcement learning, particularly those who want to use technology to analyze social and economic systems, and it is a natural fit for future computer science and data science majors.
Topics students have researched in his course include:
How can algorithms make energy or resource-allocation systems more efficient?
How do market participants respond to incentives in a regulated economy?
Can simulation predict the unintended consequences of an economic policy?
Applying algorithms to real data sharpens critical thinking and creative problem solving, and the team format builds the collaboration that university research demands.
More from the 2026 faculty
Part 2 of this series introduces the seven professors in the humanities and social sciences, whose courses range across language, law, design and the arts. You can find it on the CRI blog, along with a full course profile for each professor above.
If one of these questions is the kind you would happily spend a summer chasing, the Seoul and Global Research Programs page explains how the in-person summer programs work and which faculty tracks are open.
