Meet the 2024 Summer Fellows at UCSF Center for Intelligent Imaging

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By ci2 Team

We're so excited to welcome our four summer fellows to UCSF's Center for Intelligent Imaging (ci2)! One of our pillars is Education, and we are passionate about providing research and learning opportunities in artificial intelligence and biomedical imaging to high school, undergraduate, and graduate students.

Our summer fellows work one-on-one with a lab leader and contribute to publishable research at the intersection of medical imaging and machine learning. Meet the fellows below!

Rawan Khalifa

Rawan Khalifa

Junior at Minerva University. Faculty mentor and Principal Investigator: Melanie Morrison, PhD.

Under the supervision of Dr. Melanie Morrison and her mentor Devin Schoen, Rawan worked on analyzing MRI image data through MATLAB and LeadDBS software. She further developed a pipeline to quantify the volume of tissue activated (VTA). She also worked on Creating various models to measure the Clinical outcome efficacy utilizing quantitative metrics.

There is a strong interest in using functional MRI (fMRI) to guide DBS optimization by identifying "the therapeutic network," but reliable neural correlates are lacking. In a pilot study of 16 patients with Parkinson's, Dr. Morrison, Rawan and their team performed simultaneous fMRI and brain stimulation and assessed symptom response under the same conditions.

With Rawan's help, the lab incorporated image processing and machine learning to identify critical neural features to explain patient variability in response to DBS.

Nina Phatak

Student at the Unviersity of California, Riverside entering junior year. Faculty mentor and Principal Investigator: Sharmila Majumdar, PhD.

Nina worked with Dr. Majumdar on a project involving functional MRI to treat lower back pain.

Henry Salkever

Henry Salkever

Rising sophomore at the University of North Carolina Wilmington. Faculty mentor and Principal Investigator: Peder Larson, PhD.

Henry focused on Quantitative Cancer Imaging and enhancing deep-learning models for medical image segmentation.

"Ci2 has been an immensely informative experience as someone coming from a primary computer science background," Henry said. "I'm so thankful to Dr. Larson and have found him to be the most hands-on PI I have ever worked under. During my internship, I implemented four different model types to track prostate tumor xenografts over time. I explored various combinations of loss functions to promote precise segmentation and developed measures of prediction confidence for regions of interest."

Nicholas Xing

Senior at the University of Illinois at Urbana-Champaign. Faculty mentor and Principal Investigator: Yang Yang, PhD.

Working on Data-Centric AI - Multimodal Medical Imaging projects, Ying contributed to cutting-edge research and addressed critical challenges such as class imbalance, outliers, and distribution shifts within medical image datasets.