Nella D

- Research Program Mentor

Bio

Project ideas

Why Do Some Brains Bounce Back? Mapping the Circuits of Stress Resilience

My background is in behavioral neuroscience, with doctoral research on the prefrontal cortex circuits and dopamine signaling that underlie stress resilience and psychiatric vulnerability. A student on this project would learn how to read and synthesize primary neuroscience literature, the basics of how brain circuits are mapped and manipulated in research (optogenetics, behavioral paradigms, imaging), and how scientists build a testable hypothesis from a pile of conflicting papers. We'd start by picking a specific angle within resilience research genetic, circuit-level, or behavioral — and work through the key papers together, mapping out what's known, what's contested, and where the open questions are. From there, the student could produce a literature review or research proposal, a visual "circuit map" explainer, a mini grant-style proposal for a follow-up experiment, or a science communication piece translating the science for a general audience.

Reading the Cancer Genome: Hunting for Biomarkers in Public Tumor Datasets

I spent several years in molecular oncology research at a cancer center, and I now also work with public genomic datasets to find disease biomarkers using computational tools. A student here would learn the fundamentals of cancer genetics how tumors accumulate mutations, why some biomarkers predict outcome and others don't plus hands-on experience navigating public repositories like TCGA, GEO, or cBioPortal, and basic bioinformatics in R or Python. We'd start by choosing a cancer type and a specific question (e.g., does a certain gene's expression track with survival or treatment response?), pull real patient data, and work through exploring and interpreting it against the existing literature. Deliverables could range from a formal research paper or poster to a data visualization dashboard, a public-facing explainer article, or a short computational notebook the student can showcase.

Can Machine Learning Diagnose Disease from Biological Data? Building a Biomarker Classifier

I work at the intersection of biology and data science, building machine learning models on molecular data (e.g., blood transcriptomics) to identify biomarkers that can predict disease status or progression the same approach used in precision diagnostics research. A student on this project would learn the core workflow of applying ML to biological data: finding and cleaning a public dataset (e.g., from GEO or Kaggle) for a disease of their choosing, engineering or selecting relevant features (genes, clinical variables, imaging metrics), training and validating a classification or prediction model, and critically evaluating its performance and limitations including where AI risks overfitting or bias in clinical data. Deliverables could range from a working Python notebook/model with a written report, to a research paper evaluating an ML approach against a disease-progression or diagnostic question, to a prototype dashboard visualizing the model's predictions.

Coding skills

Languages I know

Teaching experience

Credentials

Reviews

"Ms. Nella Delva is a patient and approachable mentor. She answered all of my questions. If there are things I didn't understand in what I read or learned, she would clarify them. She always gave detailed feedback for my assignments, which helped me to improve in the next assignment. It has been an honor to have worked with a professor and researcher. I had no previous knowledge about research and was not quite fond of it, but I was motivated to continue research in college after I worked with her. What I loved most is that she shared her personal experiences and gave me educational advice as I transition into college."

Alexina from Paranaque City, Phillipines

Completed Projects

How can the BDNF gene be used as a gene of interest in genetic treatment of major depressive disorder?

Emily's Project

with Nella