Caitlin will be giving a talk and a poster at the 2026 Annual Meeting of the Translational Research Cancer Centers Consortium (TRCCC) on her work on MitoChontrol, an adaptive mtRNA filtering of single cell RNA sequencing data.

Semester: Spring 2026

This course introduces students to micron, nanometer, and sub-nanometer scale imaging-based approaches in experimental, computational, and systems biology and bioengineering. Emphasis will be placed on understanding the fundamentals of image formation, processing, and analysis of different imaging modalities along with spatial transcriptomic and proteomic methods. Applications of these methods in studying biological phenomena in space and time will be discussed. Python will be the programming language in which image processing, machine learning, and system biology methods introduced in the course will be implemented. Students are expected to know Python basics. It is also expected that students have a basic understanding of linear algebra and calculus.

The course will also be cross-listed as a Biongineering elective (BIOE 2335) within the Bioimaging track.

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The current version of the syllabus can be found here:

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Congratulations to Danielle on the successful defense of her MS thesis in the Department of Bioengineering, titled "The Underlying Mechanisms Separating Inflammation from Remission in Inflammatory Bowel Disease"!

And for getting accepted to the Integrated Systems Biology PhD program in the School of Medicine!

We are all delighted!

Ksena Mats is a rising Senior at Bryn Mawr College, PA. After having successfully completing the summer REU program (TECBio) in the lab, here at University of Pittsburgh, she will continue to be a part of research in the lab during her Senior year.

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Caitlin has been selected as an NIH Pre-Doctoral Trainee on the Cancer Immunology Training Program (CITP) Grant.

Dr. T. Rinda Soong and the Uttam Lab has been awarded the pilot Developmental Research Program (DRP) award from the Hillman Cancer Center Ovarian Cancer SPORE.

An easy-to-use, nonlinear filter for effective background identification in fluorescence microscopy images with dense and low-contrast foreground.

(Preprint on BioRxiv currently under review)

We have received R21 grant award from NCI's ITCR program to develop methods for characterizing mechanobiology of the tumor microenvironment landscape!