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Genomics and Image Informatics
Genomics and Image Informatics
Our group is interested in developing multi-modal decision algorithms that link and integrate various measurements (imaging, genomics etc) to characterize disease. Our algorithms for phenotypic measurements encompass data from 2D/3D microscopy, radiology and histopathology. We are also interested in methodological aspects of genomic analysis and image assessment. In the context of these investigations, we are very interested in collaborations with clinicians, biologists, engineers and data scientists.
News
News
Reva Kulkarni Attends IEEE EMBC 2024
Reva Kulkarni Attends IEEE EMBC 2024
The IEEE Engineering in Medicine and Biology Society hosts a prestigious international conference every year in July to showcase cutting-edge recent innovations in biomedical engineering. This year's conference was in Orlando, Florida. Reva Kulkarni gave a talk on tensor decomposition to identify spatial cell type neighborhood patterns in the tumor microenvironment (TME). Fellow authors of this paper are Gauri Patel and Joel Eliason.
Elisa Warner successfully defends PhD thesis
Elisa Warner successfully defends PhD thesis
Congratulations Dr. Warner!! Elisa Warner defended her thesis, titled "Advancing Clinical Outcome Prediction through Innovative Multimodal and Domain-Generalized AI that Accommodates Limited Data" on March 10, 2024.
Dr. Joonsang Lee's CLUSA framework featured on Biomedical Picture of the Day on Aug 10, 2023
Dr. Joonsang Lee's CLUSA framework featured on Biomedical Picture of the Day on Aug 10, 2023
Dr. Joonsang Lee's ML-based clustering framework CLUSA was featured on Biomedical Picture of the Day and received many inquiries for collaboration. The paper was published on Aug 5, 2023 and has already received numerous citations. Congratulations Dr. Lee!
See the post here.
Santhoshi Krishnan successfully defends PhD thesis
Santhoshi Krishnan successfully defends PhD thesis
Congratulations Dr. Krishnan!! Santhoshi Krishnan defended her thesis, titled "Mapping the (un)known: Spatially-driven
Frameworks for characterization of Disease Heterogeneity" on July 14, 2023.
Nicholas Wang successfully defends PhD thesis
Nicholas Wang successfully defends PhD thesis
Congratulations Dr. Wang!! Nicholas Wang defended his thesis, titled "Data, Model, Inference: Evaluating Glioma MRI Models on Clinically Informed Axes" on September 12, 2022.
SIBL Students Awarded Internships in 2022
SIBL Students Awarded Internships in 2022
Several PhD students within the SIBL lab were awarded internships in Summer and Fall 2022. Santhoshi Krishnan was awarded an internship at Bristol Myers Squibb, while Ahmed Elhossiny and Elisa Warner were awarded internships at Genentech. Congratulations to our students!
Elisa Warner Attends IEEE EMBC 2022
Elisa Warner Attends IEEE EMBC 2022
The IEEE Engineering in Medicine and Biology Society hosts a prestigious conference every year to welcome the latest innovations in biomedical engineering. This year's conference was in Glasgow, Scotland. Elisa Warner presented on her research on low-grade glioma survival outcome predictions using deep learning. For more information on EMBC, see the link here.
Ahmed Elhossiny Receives Rackham International Student Fellowship
Ahmed Elhossiny Receives Rackham International Student Fellowship
The Rackham International Student Fellowship assists outstanding international students, particularly those who may be ineligible for other kinds of support because of citizenship. The fellowship is awarded to nominees who have a strong academic record, are making good progress toward the degree, and demonstrate outstanding academic and professional promise. The award is $10,000 that may be used as stipend or tuition. More info here.
Dr. Shariq Mohammed Accepts Professorship at Boston University
Dr. Shariq Mohammed Accepts Professorship at Boston University
We are happy to announce that lab alumni Dr. Shariq Mohammed has been offered an Assistant Professor position at the School of Public Health at Boston University. Congratulations Professor Mohammed! See his BU profile here.
Seeking Postdoctoral Fellow
Seeking Postdoctoral Fellow
The Systems Imaging and Bioinformatics Laboratory in the Department of Computational Medicine and Bioinformatics, University of Michigan has a postdoctoral fellow position available to develop analysis models for multiparametric imaging (radiology, pathology) and genomic datasets. The fellow will be responsible for development of image analysis workflows as well as multi-modal predictive models to relate image-derived phenotypes and genetics with clinical outcomes. More broadly, our group extensively uses methods from signal processing, machine learning and multi-modal data integration to study problems in health informatics & bioinformatics. More info here.
Morgan Oneka receives PICTP grant
Morgan Oneka receives PICTP grant
The training program in Advanced Proteome Informatics of Cancer, funded by the National Cancer Institute, supports students performing graduate cancer-related research and provides training for proteome informatics research. The National Cancer Institute has made a substantial investment in new technology platforms for cancer proteomics, especially through the Mouse Models of Human Cancers and the Clinical Proteomic Technologies for Cancer and this investment is expected to result in greatly increased application of proteomics to cancer research. More info here.
Santhoshi Krishnan Attends Grace Hopper Conference
Santhoshi Krishnan Attends Grace Hopper Conference
The Grace Hopper Conference supports women in tech. More info here.
Shariq Mohammed Presented with Precision Health Award
Shariq Mohammed Presented with Precision Health Award
Shariq Mohammed, a research fellow in Computational Medicine and Bioinformatics, will use models combining both imaging and genotypic data to study time-to-recurrence for gliomas. “We aim to integrate genetic susceptibility with tumor-imaging characteristics to determine time-to-recurrence in glioma patients,” says Shariq. He explains, “Gliomas are tumors that start in the glial cells of the brain or the spine and compose about 30% of all brain and central nervous system tumors, and 80% of all malignant brain tumors. We will build statistical models to predict post-treatment time-to-recurrence, an invaluable task which will not only guide physicians in making informed personalized treatment strategies but also shed light on the biological mechanisms underlying disease progression and outcomes. We aim to develop advanced analytic tools by leveraging Precision Health datasets to enable precision discovery, and potentially precision treatment. This project will involve collaboration with experts in Neuroradiology, Bioinformatics, and Biostatistics.”
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