School of Medicine
Showing 1-50 of 129 Results
-
Christopher Maximilian Arends
Postdoctoral Scholar, Pathology
Current Research and Scholarly InterestsUsing genetic models of large-scale biobanks in combination with experimental models to study hallmarks of hematopoietic stem cell ageing, such as age-related myeloid-bias and clonal hematopoieisis.
-
Dr. Qiwen Deng
Postdoctoral Scholar, Pathology
BioHow fibroblasts participate in the organ fibrosis and whether targeting fibroblasts is a good strategy to reverse fibrosis is still a mystery. We have identified two important immune checkpoints, CD47 and PD-L1, are highly expressed in fibroblasts and blocking CD47 and PD-L1 reversed lung fibrosis. This is a prove of concept that targeting immune regulatory pathways could be an effective therapeutic approach to treat fibrotic diseases. In addition to identifying novel targets for the treatment of fibrosis, I am also interested in the crosstalk between fibroblasts and innate immune cells in the development of fibrosis. Combined with cutting-edge NGS approaches including single cell sequencing, spatial transcriptomics and high-dimensional CyTOF technique, we have identified several potential targets and characterized immune cells landscape in lung fibrosis. In the long run, I will focus on the validation of these targets. Specifically, I will apply gain- and loss-function approaches to investigate their role in fibrosis in vitro and in vivo.
-
Ifeanyichukwu Emmanuel Eke
Postdoctoral Scholar, Pathology
BioI am a chemical biologist with a broad interest in defining the mechanisms-of-action of novel compounds that can be used as potential drugs or diagnostic probes for different bacterial and viral infections. In addition to my flair for research, I am passionate about teaching, mentorship, leadership, and entrepreneurship.
-
Jelle Folkerts
Postdoctoral Scholar, Pathology
BioDr. Folkerts received his master's degree in Drug Innovation from Utrecht University in the Netherlands, during which he spent a year at the Galli lab at Stanford on a Fulbright Scholarship. During this time, Dr. Folkerts played a key role in developing a technology platform employing functional genomics and high-resolution single-cell confocal imaging, enabling the rapid identification of degranulation regulators in primary human mast cells. Following his time at Stanford, Dr. Folkerts studied the regulatory mechanisms of human mast cell activation under the guidance of Rudi Hendriks and Marcus Maurer, earning his Ph.D. in 2022. He then returned to Stanford as a postdoctoral fellow in the Galli lab, where his current research focuses on the identification of human mast cell degranulation regulators using a whole-genome CRISPR knockout library screen, and the validation of these findings using the recently developed technology platform. It is his long-standing goal to contribute to the design and development of specific and effective therapeutic interventions for mast cell-mediated diseases.
-
Rongting Huang
Postdoctoral Scholar, Pathology
BioDr. Huang is a computational biologist with academic interests in cancer genomics and spatial biology, particularly in the field of gynecologic cancers. During her Ph.D. under the mentorship of Dr. Yuanhua Huang, she developed statistical methods to detect allele-specific somatic copy number variations from single-cell and spatial transcriptomic data, aiming to understand genetic diversity in biological systems. Currently, her research focuses on advancing gynecologic cancer studies and women’s health through spatial technology platforms, computational modeling, and innovative data visualizations to uncover meaningful insights.
Outside of research, she enjoys hiking, rock climbing, and calligraphy, which help her stay creative and balanced. -
Rathinaraja Jeyaraj
Postdoctoral Scholar, Pathology
BioMy research interests revolve around unboxing, manipulating, and applying machine and deep learning algorithms to address computer vision challenges. Currently, I focus on histopathology image analytics using contrastive learning and multi-modal representation learning (image and text).
