Our Team
Bio
I became fascinated by cancer immunotherapy through my B.S. and M.S. training in immunology at the University of British Columbia and mouse models of cancer chemoresistance at Genentech. The rise of machine learning inspired me to pursue Ph.D. studies in Computational and Systems Immunology at Stanford. I had the opportunity to put these skills together as a postdoctoral fellow with Dr. Crystal Mackall and Dr. Sylvia Plevritis by learning insights from primary patient datasets on CAR T cell therapy. I look forward to further advancing engineered T cell designs, with the goal of improving patient outcomes.
Bio
Yiyun Chen, Ph.D. is a Postdoctoral Fellow at Professor Crystal Mackall’s group at Stanford Cancer Institute. Applying her expertise in computational cancer biology and immunology, her current research is focused on profiling the spatiotemporal dynamics of the tumor and immune microenvironment, and identifying molecular mechanisms that contribute to the clinical outcomes of patients undergoing CAR-T immunotherapy.
Bio
With my degree in Molecular and Cell biology from UCSD and Computational Biology degree from UCB, I found my passion in developing and applying bioinformatics tools to study cancer immunology. I am currently a Bioinformatician at Dr. Sabine Heitzeneder’s group. My research is dedicated to discovering clean and optimal pan-cancer target antigens for CAR-T immunotherapy for various pediatric cancers.
Bio
From my experiences in academia at UC San Diego and biopharmaceutical companies, along with my background in molecular biology and data science at UC Berkeley, I have solidified my passion for computational immunology. My interest in treatment resistance has driven me to explore the regulatory processes that guide immune system decision-making. As a LSRP, I develop computational tools and predictive models to analyze the tumor microenvironment, uncovering critical insights into CAR T-cell exhaustion and resistance mechanisms. I look forward to further exploring immune system dynamics and potentially improving treatment outcomes.
Bio
Skyler began his career as a bench scientist working on CAR-T at the University of Michigan and then at Stanford in the Mackall lab. He also spent some time working on CAR-T research in industry and earned a Master's degree in Bioinformatics from Johns Hopkins University. Skyler processes and analyzes high dimensional data from patient samples generated by CCSU and supports the general data ecosystem in CCT. This typically involves working with data types such as CyTOF, luminex (cytokines), scRNAseq, etc. and creating visualizations or analyses that clinical trial stakeholders can use to further their research.
Bio
With a background in molecular biology (BS) and Biotechnology (MS), I discovered the power of computational approaches while working in the health product industry. This led me to pursue data science training and brought me to my current role as an LSRP. I focus on applying machine learning to immunotherapy research, specifically adapting single-cell foundation models to analyze CAR T cell therapy data. My work aims to uncover molecular patterns in CAR T cells and their significance in treatment response by leveraging large-scale single-cell genomics data.
Bio
The potential of Synthetic Biology to engineer cells for targeted medicine delivery has captivated me since I first encountered the field during my undergraduate studies in Genetics and Molecular Biology (BA). This passion led me to pursue a master’s degree in Synthetic Biology at UCL London, where I co-founded a startup with a colleague to explore real-world applications of cell engineering. Recognizing the need for better integration of quantitative analyses in our field, I chose to pursue my PhD at Imperial College London, focusing on multiomic analysis of clinical trials. Currently, as a postdoctoral fellow in Rogelio Hernandez Lopez’s lab, I am integrating and expanding my expertise to develop cell therapies designed to thrive in the tumor microenvironment.
