Isha Dhandha

Isha is a PhD researcher in Bioinformatics at the University of California San Diego, with a background in Bioinformatics and Systems Biology and a minor in Computer Science. She specializes in computational approaches to biological research and helps students develop projects that apply machine learning to bioinformatics, computational biology, and biomedical questions.

Isha's research experience includes work in the Mertens Lab at the Sanford Consortium for Regenerative Medicine, where she developed an imaging software pipeline to accelerate fluorescence microscopy image analysis. Her work has also included analyzing RNA sequencing data, visualizing differential gene expression using R and ggplot2, and investigating how neuronal hyperexcitability affects the epigenetic and transcriptomic processes involved in Alzheimer's disease. Her experience with cell culture and reprogramming human skin cells into induced neurons gives her a practical biological foundation for computational research.

Alongside her research background, Isha brings substantial tutoring and teaching experience. As a tutor at UC San Diego's Teaching and Learning Commons, she helps students understand challenging concepts and strengthen their problem-solving skills. She has also served as a lead robotics and coding instructor at Snapology, teaching classes of 15 students and adapting lessons to different learning needs. Her teaching earned a 4.7-star rating from parents, reflecting her ability to make technical material engaging and accessible.

As a research mentor, Isha can guide students through projects combining machine learning with biological data, from identifying a meaningful research question and selecting publicly available datasets to developing computational workflows, evaluating models, interpreting results, and preparing a research paper. Her combination of computational training, biological research experience, and individualized teaching makes her particularly well suited to helping students build the skills and confidence needed for independent dry-lab research.

Isha is especially well suited to students interested in machine learning applications in biology, bioinformatics, computational biology, gene-expression analysis, neuroscience, and disease research. She helps students connect computational methods to meaningful biological questions while developing a clear understanding of both their methods and their findings.