Program At A Glance
| Date | Duration | Location |
| Week 1: June 29 – July 2, 2026 Computer Science | 8:30AM – 3PM | CSE Computer Lab |
| Week 2: July 6–10, 2026 Neuroscience | 10AM – 3PM | SDSC Auditorium |
| Week 3: July 13–17, 2026 Biophysics | 10AM – 3PM | SDSC AuditoriumxTBA |
| Week 4: July 20–24, 2026 Data Science Week 5: July 27–30, 2026 College Preparednes | 8:30AM – 3PM | SDSC Auditorium |
Week 1: June 29 – July 2, 2026
AI and Basic Machine Learning Algorithms
The weeklong session on machine learning will focus on three aspects: basic theoretical foundation of machine learning using statistics and the probability, foundational coding skills in Python, and the analysis of sample data sets using machine learning tools. We will also practice prompt engineering on available AI tools. Students are expected to have basic mathematical and coding skills and bring their own laptop to class.
Instructor: Dr. Paul Cao, Department of Computer Science and Engineering, UCSD
Biography:
Dr.Paul Cao is currently a continuing lecturer in the Computer Science & Engineering Department at UC San Diego. Before joining UCSD in 2015, he has been teaching in liberal arts colleges in the midwest for about 10 years. His research interests include K12 education, privacy in machine learning, and algorithms. He also coaches competitive coding programs. He is the recipient of the Jacob School of Engineering best teacher award in 2021. Paul Cao received his PhD in Electrical & Computer Engineering from Duke University.
Week 2: July 6–10, 2026
Exploring the Brain: An Introduction to Neuroscience
Neuroscience is the scientific study of the nervous system — this crash course will touch upon how the nervous system is built, how it works, how it produces behavior, thoughts, emotions, and consciousness, and what happens when it goes wrong. Specifically, following topics will be covered in the course: 1) The basics of Neuroscience and its importance; 2) The structure of the brain and nervous system; 3) How neurons communicate through electrical and chemical signals; 4) How the brain processes information from the senses; 5) What are the neural basis of memory formation and how it relates to learning; 6) How does neural activity influence on emotions and behavior; and Finally 7) An overview of some common brain and nervous system diseases
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Instructor: Dr. Chengbiao Wu, Department of Neuroscience, UCSDs
Biography:
Dr. Chengbiao Wu is a faculty member in the Department of Neurosciences at UCSD. Dr. Wu’s research focuses on the early cellular and molecular mechanisms of neurodegenerative diseases such as Alzheimer’s, Huntington’s and Parkinson’s diseases. Dr. Wu earned his doctorate from Queen’s University, Canada and previously trained at NIH, University of Texas Southwestern Medical Center and Stanford University. In addition to his research interest, Dr. Wu has been also actively engaging in teaching and training of college undergraduates as well as high school students through various outreach programs.”
Week 3: July 13–17, 2026
Using Physics and Chemistry to Understand Biological Systems
Biophysics is an interdisciplinary field that applies physics and chemistry principles to understand the biological systems. The course will cover the fundamental concepts of the structure, function and dyanmices of biological molecules and cellular components; 1) Cellular processes; 2) Molecular machines; 3) Molecular interactions; 4) Structural biology; 5) Modeling.
Instructor: Dr Kijung Sung. Center for Chronobiology, UCSD
Biography:
Dr. Kijung Sung is an Associate Project Scientist in the Department of Neurosciences at UCSD. Dr. Sung’s research is about the mechanism underlying neurodegenerative diseases in central and peripheral nervous system. The diseases include Alzheimer’s dis
eases, Parkinson’s diseases and chemotherapy induced peripheral neuropathies. Dr. Sung earned his doctorate in biophysics from Stanford University, was trained at UCSD for her postdoctoral career.
Week 4: July 20 –24, 2026
Using. Data Science for Biology and Health Research Christmas do
This week-long module will introduce students to the challenges of using data science within the areas of health and biology. Biological systems, be they individuals, single cells, or whole ecosystems, work in complex ways that make them hard to manage with traditional assumptions underneath data science and statistics. Students in this module will learn some tricks to work with biological data. We will focus on time series, non-linear systems, and estimating uncertainty. Students will work with real data, and develop small projects which they will also present. This gives them a chance to engage with the technical challenges unique to biology and health analysis, but also the challenge of communicating across domains, as most doctors don’t know data science, and most data scientists don’t speak doctor. The end result should be an introduction that allows students to contemplate developing careers that cross fields of study to impact rela human outcomes.
Instructor: Dr Benjamin Smarr, Halicioglu Data Science Institute , UCSD
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Biography:
Dr. Benjamin Smarr is an assistant professor at the Halicioğlu Data Science Institute and the Department of Bioengineering at the University of California, San Diego. As an NIH fellow at UC Berkeley he developed techniques for extracting health and performance predictors from repeated, longitudinal physiological measurements. Historically his work has focused on neuroendocrine control and women’s health, including demonstrations of pregnancy detection and outcome prediction, neural control of ovulation, and the importance of circadian rhythms in healthy in utero development. Pursuing these and other projects he has won many awards from NSF, NIH, and private organizations, and has founded relationships with patient communities such as Quantified Self. With the COVID-19 pandemic, he became the technical lead on TemPredict, a global collaboration combining physiological data, symptom reports, and diagnostic testing, seeking to build data models capable of early-onset detection, severity prediction, and recovery monitoring.
Week 5: July 27–30, 2026
Finding Your Path: Leadership for College and Beyond
At this point of their lives, students face a myriad of questions from the communities surrounding them: which college would you like to attend? What is your ambition? What professional path do you want to pursue? Amidst expectations, projections, and pressures from their surroundings, it is pivotal to establish self-anchoring practices to develop their purpose away from all the external noise. In this course, students will:
– Reflect on their inner worlds, capturing the loyalties, the learnings, the wisdom that was passed on to them. Through guided individual exercises, they will enhance their self-awareness and strengthen their statements of purpose, self-image, and narratives that will dictate the early stages of their careers.
– Research and learn about social issues that interest them, working with other peers to develop innovative and sustainable actions to foster systemic changes. Through group work, they will use the learning from other classes during the Summer to boost creative problem-solving to advance on societal challenges.
– Lead presentations and campaigns related to topics of their interest. Student agency and experiential learning are trademarks of this course. Either through case studies, fishbowl discussions, or other interactive sessions, students will get exposed to participative pedagogies that will inspire them to improve interpersonal relationships.
Course structure:
Morning – > Check in, reflection of the day, case study, discussion
Afternoon – > Team building activities, group work
Potential topics for discussion/research: social mobility; homelessness; obesity; hunger; climate change.
By the end of this course, students are expected to:
– Gain clarity of their own inner worlds, better articulating their purpose and creating more solid college essays
– Steer the direction of their career decision-making more aligned with societal needs
instructor: Professor Leonardo Da Silveira, Department of Leadership and Education Studies, USD
Biography:
Professor Leonardo Civinelli Tornel da Silveira brings over 15 years of international experience in leadership, organizational change, and development, having worked across 12 countries with institutions such as the United Nations and Harvard University. He is currently pursuing a PhD in Leadership Studies at USD’s SOLES and teaches LEAD-150 (Emerging Leaders) and LEAD-350 (Leadership and Group Development) at the Leadership Studies Minor. He holds a Master in Public Administration from Harvard University, a Master in International Affairs and Diplomacy from the Open University of Catalunya, a Master in Leadership from University College London, and a Bachelor of Arts in Communications from Universidade Federal de Juiz de Fora (UFJF). His passion lies in creating engaging learning environments where we can explore leadership not just as a concept, but as a practice that helps us navigate complexity and drive meaningful change.
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