Spyridon (Spyros) Bakas, Ph.D.

Assistant Professor (Tenure Track)

Spyridon Bakas, Ph.D.Dept. of Pathology & Laboratory Medicine
Dept. of Radiology (joint appt)
Dept. of Bioengineering (secondary appt)
Perelman School of Medicine
University of Pennsylvania
Medical Research Analytics for Quantitative Integration (MeRAQI) lab - Director
Artificial Intelligence in Biomedical Imaging Lab (AIBIL)
Center for AI & Data Science for Integrated Diagnostics (AI2D) - Executive Faculty Committee
Center for Biomedical Image Computing & Analytics (CBICA)

Google Scholar  |  LinkedIn  |  Twitter  |  GitHub

Richards Medical Research Labs, Fl7, St.A702
3700 Hamilton Walk
Philadelphia, PA 19104

Research Summary

My research interest focuses on the development, application, and benchmarking of advanced computational algorithms in oncological imaging, with the intention of improving the assessment, quantification, and diagnosis of cancer in the current clinical practice. Eagerly embracing the concept of personalized/precision medicine, I am involved in radio-patho-genomic research where correlations between quantitative imaging features and molecular characteristics can lead to highly accurate imaging biomarkers, towards enabling treatment selection models customized on an individual patient basis. I have also been leading federated machine learning efforts in healthcare towards facilitating expedited multi-institutional studies, while patient data are always retained within the acquiring institution. My work so far has spanned across the areas of image segmentation, feature extraction, statistical analysis, motion analysis, and machine learning techniques applied in magnetic-resonance (MR), digitized histopathology, and contrast-enhanced ultrasound (CEUS), imaging data. The ultimate aim of my research is clinical deployment, towards making diagnostic and treatment decisions more promptly, objectively, and precisely.

(for a complete up to date list of publications, please visit my Google scholar page)

Educational Qualifications

Ph.D. in Medical Image Computing & Analysis - Kingston University, London (UK)
M.Sc. in Vision, Imaging & Virtual Environments - University College London (UK)
B.Sc. (Hons) in Computer Science - Kingston University, London (UK)

  • The Federated Tumor Segmentation (FeTS) platform: An intuitive tool facilitating secure multi-institutional collaboration (U01CA242871, NIH/NCI/ITCR, PI: Bakas, Spyridon, 07/01/2019 - 06/30/2023)
  • Populating the Penn Immune Health Report to Support Precision Medicine: Immunohistochemical Markers to Predict Response to Checkpoint Blockade in Non-Small Cell Lung Cancer (NSCLC) (Abramson Cancer Center, PI: Thompson, Jeffrey (Role: Co-I), 04/22/2020 - 04/21/2021)
  • A pilot radiogenomics study evaluating MRI signatures of therapeutically targetable gene expression alterations in human glioblastoma (CTSA/ITMAT/TBIC, PIs: Bakas, Spyridon / Bagley, Stephen, 03/01/2019 - 02/28/2021)
  • Democratization of AI-based Lesion Segmentation (Intramural CBICA seed grant, PI: Bakas, Spyridon, 02/03/2020 - 02/02/2021)
  • Cancer imaging phenomics software suite: application to brain and breast cancer (1U24CA189523, NIH/NCI/ITCR, PI: Davatzikos, Christos, 09/01/2015 - 08/31/2020)
  • Predicting brain tumor progression via multiparametric image analysis and modeling (R01NS042645, NIH/NINDS, PI: Davatzikos, Christos, 09/01/2014 - 05/31/2020)
  • Refined Personalized Radiotherapy Target Volume Definition using Predictive Recurrence maps in Glioblastoma (Intramural CBICA seed grant, PI: Bakas, Spyridon, 06/01/2018 - 05/31/2019)
  • In vivo surrogate markers of clinically-relevant molecular characteristics of glioblastoma, based on multivariate machine learning and clinically-acquired MRI (CTSA/ITMAT/TBIC, PIs: Bakas, Spyridon / Davatzikos, Christos, 02/01/2017 - 01/31/2019)
  • In vivo predictive models of meningioma progression, (CTSA/ITMAT/TBIC, PIs: Dahmane, Nadia / Grady, Sean / Davatzikos, Christos, 02/01/2017 - 01/31/2019)
  • Collaborative Funding
    • Imaging Signatures of Genetic Mutations in Glioblastoma Using Machine Learning (R01NS042645, NIH/NINDS, PI: Davatzikos, Christos (Role: Co-I), 12/15/2019 - 11/30/2024)
    • Generalizable quantitative imaging and machine learning signatures in glioblastoma, for precision diagnostics and personalized treatment: the ReSPOND consortium (R01CA269948, NIH/NCI, PI: Davatzikos, Christos (Role: Co-I), 06/15/2022 - 05/15/2027)