I completed my Ph.D. training at Harvard with Elliott Kieff, uncovering the complex host-pathogen chromatin interactions during viral-driven lymphomagenesis. I next moved west for some warmth and sunshine, where I worked with Garry Nolan at Stanford on technology development and ways to better interrogate biological systems. My current interests lie at the intersection of addressing critical questions in host-disease interactions, through the development and applications of novel spatial technology platforms and computational algorithms. Ongoing work includes the biology of viral pathogenesis, tumor biology, and immune dysregulation.

My doctoral thesis focused on solving the molecular mechanisms driving humoral immune evasion during human cytomegalovirus infection, with the aim of identifying viral targets for novel intervention and prevention strategies. Outside the lab, I enjoy interior designing and traveling.

I am a biostatistician by training. Currently, my research interests are mostly in medical image analysis and machine learning methods. In my leisure time, I enjoy photography, cooking, badminton, and kendo.

Hello! My name is always mispronounced, and I am currently older than I look. I am pursuing a PhD in Virology at Harvard, where I spend too much time daydreaming and learning in the lab. I find viruses fascinating for their extraordinary capabilities despite being minuscule pieces of genetic material, and I admire the potential for highly multidisciplinary research. Outside of work, I enjoy playing the piano and gaming with my friends.

I am passionate about advancing research that transforms healthcare and benefits mankind. Germinal centres and B cells are my first scientific loves, but I am keen on expanding my arsenal of scientific tools, so I can delve into diverse biological researchareas in the future. After long days at work, I recharge by reading a (non-scientific) book and enjoying a cup of tea. I also enjoy travelling, hiking, and singing.

I fell in love with bench work while spending summers with my dad while he was in a PhD program, and bench work is all I’ve wanted to do since. I attended Lewis & Clark college and got a BA in Biochemistry and Molecular biology and a few years later joined a histology core in Oregon. My interests lie in all things tissue (so long as it can’t talk back).

I was recruited to the CVVR in Feb 2023 to bring research histotechnology capabilities to the institute. I split my time between Sizun’s lab, Dan Barouch’s lab and running the Tissue Technologies Unit.

After finishing high school in Germany, I moved to Cambridge (UK) for my undergraduate and master’s degrees where I worked with Dr. Geoffrey Smith on SARS-CoV-2 innate immune evasion and Dr. Colin Crump on HSV-1 tegument proteins, respectively. I then moved to the US in 2022 and am currently a G2 graduate student in the Virology PhD Program. My previous rotations were with Dr. Ben Gewurz and Dr. Philip Kranzusch, after which I rotated in and then joined the Jiang lab. My primary research interests are host-pathogen interactions at the immunity interface as well as the development and implementation of novel spatial technologies.

I am studying the mechanisms of EBV infection of nasopharyngeal epithelium cells and B cells in Dr. Bo Zhao’s Lab at Brigham and Women’s Hospital.Outside of the lab, I enjoy walking with my family on weekends

I completed my doctoral training with Ben Gewurz at Harvard. Through transcriptomics and proteomics approaches, I constructed the Epstein-Barr Virus (EBV)-B cell protein-protein interaction map, uncovering multiple mechanisms the virus employs to evade host intrinsic and innate immune pathways. Outside the lab, I enjoy photography and running.

During my Ph.D. life, I was co-trained in a wet lab (Dr. Zihai Li at OSU) and a dry lab (Dr. Qin Ma at OSU) for developing and applying machine/deep learning tools to study anti-tumor immunity. For computation,  I am interested in modeling biological pattern presentation using graph-based methods. Regarding biology, I prefer to mine atlas-level data to study T-cell exhaustion mechanisms in different conditions. In the future, I would like to work in this direction in-depth.

I completed my M.D. training in Kidney Transplant department of the First Affiliated Hospital of Sun Yat-Sen University (FAH-SYSU) and worked as a surgeon in the Liver Transplant department. My research interest is in the immune and metabolic microenvironment of liver at diseased (especially cancer) and transplanted status. I have been focusing on exploring immune mechanism underlying liver cancers using bioinformatics methods, including bulk, single-cell and spatial transcriptomics. I would like to pursue further training in the field of spatial-omics. I enjoy rogue-like and metroidvania games in my spare time.

During my Ph.D. studies, I specialized in deep learning and bioinformatics, primarily focusing on developing language and vision models for scRNA-seq, single-cell proteome, spatial transcriptomics, as well as multi-modal for multi-omics analysis.

During graduate school, my research focused on developing molecular classifiers to predict immunotherapy response in bladder cancer. Looking ahead, my goal is to build machine learning models that integrate multimodal data—genomics, histopathology, and clinical features—to predict disease risk and treatment response. By bridging computational biology with translational research, I hope to create predictive tools that can be integrated into clinical workflows to improve patient care through data-driven decision-making.

I completed my undergraduate degree at Hunan University, where my thesis focused on electrochemistry, specifically the synthesis of electrode materials. I then earned my Ph.D. in glycobiology of SARS-CoV-2 at the State University of New York at Buffalo, under the mentorship of Dr. Sriram Neelamegham. Here are two fun facts: 1. I transitioned from electrochemistry to biological engineering and completed my Ph.D. 2. I’m originally from Wuhan and I study the virus for my Ph.D. program. My curiosity lies in understanding viral pathogen-host interaction.

I completed my Ph.D. at University of Hong Kong (HKU) under the mentorship of Dr. Yuanhua Huang, focusing on single-cell genomics. My research has centered on developing statistical methods for allele-specific somatic copy number variation detection from single-cell and spatial transcriptomic data, with the goal of understanding genetic diversity in biological systems.

Currently, my interests lie in advancing research in gynecologic cancers and women’s health through the development and application of novel spatial technology platforms, computational modeling approaches, and creative data visualizations to uncover meaningful insights.

Outside of research, I am passionate about hiking, rock climbing, and other extreme sports. I also enjoy practicing calligraphy and recording moments from daily life for fun, which helps me stay creative and balanced.

I’m from Beijing, China, and half of my life in Canada, where I developed a passion for exploring how molecular systems shape the brain. My research focuses on spatial transcriptomics and computational modeling, studying how neural stem cell niches remodel during pregnancy. I’m fascinated by how data-driven approaches can reveal the hidden rules of cellular communication across space. Outside the lab, I enjoy snowboarding — always looking for the next mountain to explore.

I am fascinated by the intricate dynamics of infection and immune response and how it can to inform preventative and therapeutic strategies, staying ahead of even the most rapidly evolving pathogens. I have investigated the E. coli response to phagocytosis at the single-molecule level, studied the impact of lung microbiome composition on recurring lung infections in cystic fibrosis, and am now, in the Jiang lab, I am excited to explore the tissue-level response to SARS-CoV-2!

I am a PhD student in Biomedical Engineering at Southern Medical University. My research interests center on multi-omics data analysis and machine learning, specifically the development of mathematical models for cancer prognosis. I focus on constructing interpretable, trustworthy, and computationally efficient models that improve prediction accuracy while uncovering critical disease-associated features from proteomic, transcriptomic, and other omics data. My goal is to advance biological insights and inform clinical decision-making. Outside the lab, I enjoy travelling and exploring good food.