CONTACT

J. Manuel Perez

Image-Guided Intervention Branch Dr. J. Manuel Perez is a Program Director in the Image Guided Interventions Branch of the Cancer Imaging Program, Division of Cancer Treatment and Diagnosis at the National Cancer Institute (NCI). He received his PhD in Biochemistry at Boston University and a post-doctoral training at the Massachusetts General Hospital/Harvard Medical School. Before joining NCI, Dr Perez was tenured professor at the University of Central Florida (2005-2015) and Cedar Sinai Medical Center (2015-2021). Dr Perez has over 20 years of academic experience in the fields of bio-organic chemistry, biochemistry, biotechnology, nanotechnology, and molecular imaging. His research interest included the development of magnetic sensors, molecular imaging agents, therapeutic nanoagents and intraoperative procedures to image and treat cancer. His work was supported by multiple NIH (K01 and R01s) and industry-sponsored grants. He joined the NCI’s Cancer Imaging Program in 2021 and is currently managing projects in areas related to image guided intervention, nanotechnology, and molecular imaging.

Pegah Khosravi

About My research focuses on the development of machine learning techniques and AI-based models for the innovation of medical data analysis. I am an Assistant Professor at New York City College of Technology (City Tech) and teach Biomedical Data Analytics. Also, I serve as Deputy Editor of the Journal of Magnetic Resonance Imaging (JMRI). Education: Ph.D., Bioinformatics, 2014 Courses Taught at City Tech: Research Interests: Current and Previous Appointments: Assistant Professor (2022-present)Department of Biological Sciences, New York City College of Technology, CUNY, NY, USA. Deputy Editor (2020-present)Journal of Magnetic Resonance Imaging (JMRI): New Developments and Future Direction, NY, USA. Sr II Computational Biologist (2020-2022)Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, NY, USA. Postdoctoral Associate (2017-2020)Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medical College, NY, USA. Postdoctoral Research Fellow (2014-2017)School of Biological Sciences of Institute for Research in Fundamental Sciences (IPM), Tehran, Iran. Visiting Researcher (2012-2013)Donnelly Center for Cellular and Biomolecular Research, Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. Representative Publications: Khosravi P., Lysandrou, M., Eljalby, M., Brendel, M., Li, Q., Kazemi, E., Zisimopoulos, P., Sigaras, A., Barnes, J., Ricketts, C., Meleshko, D., Yat, A., McClure, T. D., Robinson, B. D., Sboner, A., Elemento, O., Chughtai, B., Hajirasouliha, I., A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion, Journal of Magnetic Resonance Imaging, 54 (2021). Boehm K. M., Khosravi P., Vanguri R., Gao J., Shah P. S., Harnessing multimodal data integration to advance precision oncology, Nature Reviews Cancer (2021), 22: 114-126. Xu, Z., Verma, A., Naveed, U., Bakhoum, S., Khosravi P., Elemento, O., Using Histopathology Images to Predict Chromosomal Instability in Breast Cancer: A Deep Learning Approach, Iscience (2021), 3;24(5). Asgari, Y., Khosravi P., Flux variability analysis reveals a tragedy of commons in cancer cells, SN Applied Sciences (2020), 2:1966. Khosravi, P., Kazemi, Zhan, Q., Toschi, M., Malmsten, J., Cooper, L., Hickman, C., Meseguer, M., Rosenwaks, Z., Elemento, O., Hajirasouliha I., Deep Learning Enables Robust Assessment and Selection of Human Blastocysts after In-vitro Fertilization, npj digital medicine-Nature (2019), 4;2:21. Khosravi, P., Kazemi, E., Imielinski, M., Elemento, O., Hajirasouliha I., Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images, EBioMedicine (2018), 27: 317-328. Habibi, M., Khosravi, P., Disruption of the Protein Complexes from Weighted Complex Networks, IEEE/ACM transactions on computational biology and bioinformatics (2018). Asgari, Y., Khosravi, P., Zabihinpour, Z., Habibi, M., Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis, Integrative Biology (2018), 10:113-120. Aghdam, R., Baghfalaki, T., Khosravi, P., Ansari, E. S., The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer, Genomics, Proteomics & Bioinformatics (2017), 15: 396-404. Emamjomeh A., Robat E. S., Zahiri J., Solouki M., Khosravi P., Gene co-expression network reconstruction: a review on computational methods for inferring functional information from plant-based expression data, Plant Biotechnology Reports (2017), 1:6. Aghdam, R., Khosravi, P., Ansari, E. S., Comparative Analysis of Gene Regulatory Networks Concepts in Normal and Cancer Groups, Bioinformatics and Biocomputational Research (2016), 1: 42-45. Khosravi P., Gazestani V.H., Pirhaji L., Law B., Sadeghi M., Bader G., Goliaei B., Inferring interaction type in gene regulatory networks using co-expression data, Algorithm for molecular Biology (2015), 10:23. Khosravi P., Gazestani V.H., Asgari Y., Law B., Sadeghi M., Goliaei B., Network-based approach reveals Y chromosome influences prostate cancer susceptibility, Computers in Biology and Medicine (2014), 54:24-31. Hosseinpour B., Bakhtiarizadeh M.R., Khosravi P., Ebrahimie E., Predicting distinct organization of transcription factor binding sites on the promoter regions; a new genome-based approach to expand human embryonic stem cell regulatory network. Gene (2013), 531:212-9. My Google Scholar: