Sheida Nabavi

Sheida Nabavi is an Associate Professor in the Department of Computer Science and Engineering at the University of Connecticut (UConn), where she has been since Fall 2015. Prior to this, she was a Research Associate at the Center for Biomedical Informatics at Harvard Medical School. She holds a PhD in Electrical and Computer Engineering from Carnegie Mellon University (2008) and a Master’s in Medical Science (Bioinformatics) from Harvard Medical School (2012).

Her research focuses on computational methods for analyzing genomic data and biomedical images, leveraging statistical machine learning and signal/image processing. Key contributions include tools like DCCNV for CNV detection, SEACON for allele-specific profiling, and CAPTURE for image registration. She leads the Nabavi Lab, which develops open-source tools accessible via GitHub.

She advises a diverse group of students, including PhD candidates researching AI in medical imaging, single-cell sequencing, and multimodal data analysis. Notable alumni include Jun Bai (Cincinnati University Assistant Professor), Tianyu Wang (Meta Research Scientist), and Fatemeh Zare (Thermo Fisher Scientific Data Scientist).

• Courses Taught: Medical Imaging ML, Genomics Data Analysis, Probabilistic Graphical Models.
• Labs/Teams: Nabavi Lab (specializing in bioinformatics and AI for healthcare).

Her work bridges machine learning and biomedical applications, with grants and projects funded by NSF and industry partnerships.