Tamara J
- Research Program Mentor
PhD candidate at University of Southern California (USC)
Expertise
biology, medicine, neuroscience, Bioinformatics, Writing, Data science and AI for health and medicine, applications of neuroimaging, Genetics, Neuroscience, Neuroimaging, data visualization using real datasets, Precision medicine and the future of healthcare
Bio
I am a PhD student in Computational Neuroscience where I develop AI and data science methods to analyze brain imaging and genetic data, with a focus on Alzheimer’s disease and aging. My work blends computer science, neuroscience, and statistics to uncover meaningful patterns in large, complex datasets - an interdisciplinary approach I enjoy sharing with students. I’m passionate about making complex scientific ideas clear and engaging, and I love helping students turn their own questions into creative, data-driven projects. Over the past seven years, I’ve taught and mentored students at all levels, from serving as a bioengineering lecturer at UC Berkeley to leading AI and coding courses at USC and teaching graduate students about venture capital and business development. Outside of the lab, I enjoy hot yoga, baking, and exploring my creativity through art and photography. I bring that same curiosity and creativity to mentoring, encouraging students to explore new ideas, experiment boldly, and create projects that reflect their unique interests.Project ideas
Mapping the Teenage Brain
Explore how different parts of the brain change during adolescence and how this affects decision-making, learning, and emotions. Students will learn the basics of brain anatomy, read neuroscience articles, and gather information from publicly available brain imaging resources. The final project could be a visually engaging presentation, infographic, or short scientific paper explaining their findings in a way that peers can understand.
AI as a Doctor’s Assistant
Discover how artificial intelligence can help doctors diagnose diseases from brain scans. Students will learn the basics of AI, data visualization, and ethics in medicine, using simplified, open-source medical imaging datasets. They will gather information by reading accessible AI-in-healthcare case studies and experimenting with beginner-friendly coding notebooks. The final project could be a mock-up of an AI tool, a concept paper, or a set of visual data analyses.