Samantha B
- Research Program Mentor
PhD at University of Southern California (USC)
Expertise
Adolescent development; Psychology and behavior; Applications of neuroimaging; Educational neuroscience and psychology; The neuroscience of sleep and emotion; Social determinants of health; Music and the brain; Memory and learning; Environmental neuroscience; Neurolinguistics; Ethics of neuroscience and AI; Genetics and behavior
Bio
I’m a recent Ph.D. graduate in Neuroscience from the University of Southern California, where my research explored interactions between adolescent brain development, sleep patterns, and cognitive functions like emotion regulation and working memory using large-scale neuroimaging datasets. I’m passionate about helping students develop research questions that connect scientific theory to tangible, real-world applications, particularly in areas related to education, mental health, and public policy. I especially enjoy mentoring interdisciplinary projects that bridge neuroscience with psychology, social science, AI, and whatever gets you most excited. Outside of research and teaching, I enjoy board games, racket sports, the great outdoors, and, occasionally, rock climbing and Muay Thai. I also love spending time with my Siberian cat, Penelope, who supervises virtual mentoring sessions when she’s not busy walking across my keyboard or curating her social media presence. As both a researcher and mentor, I value curiosity, creativity, academic ownership, and approachable science communication.Project ideas
Designing an Educational Course Informed by Psychology, Neuroscience, and AI Research
How can research in psychology, neuroscience, and artificial intelligence be used to improve education? In this project, students would design an original course, curriculum unit, or educational intervention grounded in scientific research on learning, memory, creativity, attention, motivation, stress, cognitive development, or communication. Students could explore questions such as: How should schools adapt to AI tools like ChatGPT? What teaching methods best support long-term retention and engagement? How do stress, sleep, and social media affect learning? Projects could also incorporate emerging research in natural language processing (NLP), such as how language reflects emotion, attention, or communication style. The final product could include a syllabus, lesson plans, multimedia educational materials, policy recommendations, or a prototype educational resource accompanied by a research-based rationale connecting the design to existing psychological and neuroscience literature. Through the project, students would gain experience in critically evaluating scientific evidence and translating research into practical educational applications.
Designing and Conducting a Psychology or Neuroscience Research Study
In this project, students would learn how to develop an original research question in psychology or neuroscience and design a study to investigate it. Possible topics include the influence of extracurricular activities on sleep architecture, how access to greenspace affects attention and memory, associations between language and emotional state, adolescent mental health, peer relationships, and social media use. Depending on the student’s interests, background, and available time, projects could involve designing surveys or behavioral experiments, analyzing publicly available datasets, conducting interviews, exploring basic NLP methods, evaluating existing scientific literature to identify gaps in current research, and/or conducting a meta-analysis of published results. Final deliverables could include a literature review, research proposal, pilot dataset analysis, conference-style poster, presentation, or research manuscript. For example, a student interested in language use and emotional state might investigate whether patterns in written language reflect stress or emotional well-being in adolescents. The student could review existing research in psychology and natural language processing (NLP), design interviews or surveys incorporating both self-report mood measures and open-ended written responses, analyze publicly available text data using basic Python-based NLP tools, and create data visualizations in R or Python examining relationships between language use and emotional state.