Our Research Team
Christina Curtis, PhD, MSc
Assistant Professor of Medicine and Genetics
Stanford University School of Medicine
Co-Director, Molecular Tumor Board, Stanford Cancer Institute
Christina Curtis, PhD, MSc is an Assistant Professor in the Departments of Medicine (Oncology) and Genetics in the School of Medicine at Stanford University where she leads the Cancer Computational and Systems Biology Group and is Co-Director of the Molecular Tumor Board at the Stanford Cancer Institute. Trained in molecular and computational biology, she received her doctorate from the University of Southern California in 2007 advised by Simon Tavaré, and holds Masters degrees in Bioinformatics and Computational Biology from the University of Southern California and in Molecular and Cellular Biology from the University of Heidelberg, Germany. Dr. Curtis has been the recipient of numerous awards, including the 2012 V Foundation for Cancer V Scholar Award, the 2012 STOP Cancer Research Career Development Award and a 2016 AACR Career Development Award. She was named a Kavli Fellow of the National Academy of Sciences in 2016 and received the NIH Director's Pioneer Award in 2018. Dr. Curtis is also the principal investigator on grants from the NIH/NCI, Department of Defense, American Association for Cancer Research, Breast Cancer Research Foundation, Susan G. Komen Foundation, V Foundation for Cancer Research and Emerson Collective. She serves on the Editorial Boards of Breast Cancer Research, Carcinogenesis: Integrative Biology, Cell Systems, the Journal of Computational Biology and JCO Precision Oncology.
Jennifer Caswell, MD
Jennifer is an Oncology fellow at Stanford. She did her internal medicine residency training at UCSF and her medical school and undergraduate studies at Harvard. She is interested in using genomic data to uncover germline and somatic determinants of breast cancer traits, including drug resistance vs response and metastasis.
Graduate Student, Genetics
BS, Columbia University (Mathematics)
Joe is interested in (epi)genetic resistance mechanisms.
Graduate Student, Cancer Biology (SGF Fellow); jointly advised by Michael Angelo
Noah received his BA in Biophysics from Harvard University. He then worked for two years at Harvard Medical School and the Broad Institute in the labs of Drs. Rameen Beroukhim and Ian Dunn studying the genomics of brain tumors.
Noah is interested in combining multiplexed imaging techniques with genomics to understand the tumor microenvironment and response to therapy.
Zheng Hu, PhD
Postdoc (Innovative Genomics Initiative Postdoctoral Fellow)
PhD Beijing Institute of Genomics
Zheng is interested in applying population genetics approaches to study mechanisms of tumor evolution.
Kasper Karlsson, PhD
PhD Karolinksa Institute
Kasper is interested in studying tumor dynamics using experimental and computational approaches.
Zhicheng Ma, MD, MS
Senior Research Associate
MD Hunan Medical University;
MS Central South University, China
Zhicheng is interested in characterizing mechanisms of tumor progression and evolution, as well as in technological developments for cancer ‘omic’ profiling and single cell sequencing.
Katherine received an undergraduate degree in Computer Science from Princeton University and a master's degree in Computational Biology from the University of Cambridge. She is presently an MD/PhD student at Stanford. She is passionate about using computation and data-driven techniques to conduct translational research and is currently interested in using "-omics" data to model cancer metastasis and resistance.
Graduate Student, Genetics (NSF Fellow); jointly advised with Prof. Anshul Kundaje
Chris is interested in cancer regulatory genomics.
Jose Seoane, PhD
Postdoc (Susan G. Komen Postdoctoral Fellow)
PhD University of Coruna, Spain
Jose obtained his PhD in Computer Science at the Universidade da Coruña (Spain). Throughout his doctoral training, he focused on methods development and application for bioinformatics and machine learning approaches. During his postdoctoral training he contributed to the development of machine learning based approaches and applied them to cardiovascular and cancer genetic data. His current interest is in the development of methods to investigate how different layers of (epi)genomic data can be integrated in order to establish a holistic view of the molecular mechanisms underlying cancer initiation and progression.
PhD, University of California at Berkeley (Chemical Engineering)
BS, Carnegie Mellon University (Chemical Engineering)
Scott develops mathematical models and computer simulations to address several issues in tumor immunology. Most recently, his work has focused on the heterogeneous spatial distribution of neoantigens within tumors, the effects of HLA genotype on the immunogenicity of neoantigens, and the corresponding response to immune checkpoint blockade therapies.
Graduate Student, Genetics (NSF Fellow); jointly advised with Prof. Polly Fordyce
BA, Vanderbilt University (Molecular and Cellular Biology)
Alex is interested in developing and applying single-cell microfluidics methods to characterize tumor evolution.
Krystal Straessler, PhD
Postdoc (Cancer Systems Biology Fellow); jointly advised with Prof. Alejandro Sweet-Codero
Krystal is interested in the genomics and evolution of pediatric sarcomas.
Ruping Sun, PhD
PhD Fudan University, China
Postdoc Columbia University (Califano Lab)
Ruping is interested in developing novel tools for cancer genome analysis and interpretation. He is also interested in the contribution of non-coding variation to tumor progression.
Johannes Reiter, PhD
Instructor (Erwin Schrödinger Fellow); jointly advised with Prof. Sanjiv Sam Gambhir
PhD Institute of Science and Technology Austria
Postdoc Harvard University
Hannes works at the interface of computer and biomedical sciences and focuses on the stochastic processes underlying cancer evolution. He designs computational methods to learn from large-scale biological data sets and develops mathematical models to generate novel hypothesis and explain clinical observations on a mechanistic level.
Graduate Student, Biology; jointly advised by Dmitri Petrov
Susanne is interested in applying population genetic and evolutionary theory to understand tumor progression and the drivers of this process.
Intern (CS undergrad)
Mark is jointly pursuing a BS and a MSc in Computer Science with emphases in machine learning and biocomputation, respectively. He is interested in a variety of topics that are within the intersection of computer science, biology, and medicine, including rare genetic variation, the heritability of complex diseases, and regulatory genomics.
Jie Ding, PhD
Senior Computational Scientist
PhD Ohio State University;
Postdoc Johns Hopkins/Harvard Biostats (Parmigiani Lab)
Jie has a B.S. in biochemistry and molecular biology and a Ph.D. in biostatistics. His research interests include statistical genetics, statistical computation and Bayesian analysis and the analysis of high-throughput sequencing data for the modeling of tumor heterogeneity and tumor evolution during tumor development, metastasis and the development of drug resistance.
Cancer Bio Rotation Student
BS University of California, Los Angeles
Summer Student (Computer Science, MIT)
Summer Student (Biochemistry, UCLA)
Emma Pierson, MSc
Graduate Student (Rotation), Computer Science
Emma Pierson earned a MSc in computer science at Stanford and an MSc in statistics at Oxford and is now a PhD student in computer science.
Summer Student (Evergreen Valley High School, San Jose, CA)
Oscar Rueda, PhD
Visiting Scientist (University of Cambridge)
Andrea Sottoriva, PhD
Group Leader, Institute for Cancer Research London
Former Postdoc Curtis Lab