The Han Lab Team Members
Summer Han, PhD
Dr. Han is an Assistant Professor of Neurosurgery and Medicine in the Stanford School of Medicine. She holds a PhD in Statistics (Yale, 2009) with concentration on statistical genetics. Dr. Han's research focuses on developing novel statistical methods for understanding the interplays between genes and the environment and for evaluating efficient screening strategies based on etiological understanding. She is the Principal Investigator of the NIH funded project for conducting GWAS, building risk prediction models, and developing decision analysis for cancer screening for second primary lung cancer (SPLC).
Eunji Choi, MPH, PhD
Eunji completed her undergraduate education in Economics at Emory University in 2012. Subsequently, she obtained a M.P.H (2016) and a Ph.D. in Public Health (2020) from National Cancer Center Korea, Graduate School of Cancer Science and Policy. Her prior research focus was on evaluating the effectiveness and the performance quality of organized cancer screening programs in South Korea. Currently, Eunji is working on developing and evaluating risk-stratified screening strategies for second primary lung cancer among lung cancer survivors.
Aparajita Khan, PhD
Aparajita completed her Ph.D. in Computer Science and Machine Learning from Indian Statistical Institute in 2021. Her dissertation focussed on integrative clustering of multi-view data using graph approximation, subspace projection, and manifold learning-based approaches. Her research interests include machine learning and pattern recognition, computational biology, multi-omics data analysis, and optimization over Euclidean and non-Euclidean spaces. Currently, Aparajita is working on developing statistical methods to analyze single-cell RNA sequence data and integrating multi-omic data for the prediction of brain metastases and recurrence in lung cancer patients.
Justin Lee, MPH
Justin completed his MPH degree at the University of Miami where he mostly focused on data management and statistical analyses of infectious diseases with UM’s Clinical and Translational Sciences Institute and the Miami-Dade County Health Department. He is currently working on numerous projects that include developing predictive models for second primary lung cancer and parallelizing GWAS through Stanford’s computer cluster (Sherlock) with The Han Lab.
Victoria Ding, M.S.
Victoria completed her M.S. in Biostatistics at the University of Washington, where she engaged in collaborative research pertaining to mental health and gerontology. She is currently working on several risk modeling projects for second primary lung cancer and is developing an R Shiny app for the prediction models.
Anna Graber-Naidich, Msc, PhD
Anna obtained her PhD in healthcare operations research from the University of Toronto, focusing on Canadian primary care services. She has a MSc in biostatistics and developed estimation techniques for survival analysis for correlated and missing data for breast cancer patients. Her current research projects include developing and evaluating risk-stratified screening strategies for second primary lung cancer among breast cancer survivors.
Chloe Su, B.S.
Graduate Student in Epidemiology and Clinical Research
Chloe is a Ph.D. student in Epidemiology. She completed her B.S. in Molecular, Cell and Developmental Biology with a minor in Biomedical Research at UCLA, where she worked on hematopoietic stem cell development. Prior to Stanford, she was a Staff Research Associate at UCLA Health, managing clinical trials in early lung cancer detection and prediction. Currently, she is working on various projects for building prediction models for brain metastases and recurrence in lung cancer patients.
Co-Term Student in Epidemiology & Population Health
Sophia is a Co-Term Master's student in Epidemiology (and an undergraduate student majoring in Computation Biology) at Stanford. Currently, she is working on several projects for evaluating the impact of smoking cessation on second primary lung cancer and for developing prediction models for lung cancer based on ethnically diverse populations.
Anya Fries, B.S.
Graduate Student in MS&E
Anya is a Master's student in the Department of Management Science and Engineering Program at Stanford. She graduated from École Polytechnique in France with a double major in Computer Science and Mathematics and completed a thesis in stochastic optimization methods for the inverse optimal transport problem. Her current research involves developing and applying statistical learning methods for personalized outcome prediction. Specifically, she is working on extending existing dynamic risk profiling methods for cancer patients.
Julie Wu, M.D., Ph.D.
Medical Oncology Fellow
Julie is a Stanford medical oncology fellow specializing in thoracic malignancies. She completed her undergraduate education in Molecular Biology with a certificate in Biophysics at Princeton University and went on to UCSF for MD/PhD, where her PhD focused on cancer cell biology. She then completed internal medicine residency at Vanderbilt University, where she led a project on tumor drivers in metastasis. Currently, she is working on genomics of brain metastasis development in lung cancer patients and development of a predictive model of brain metastasis with the goal of optimizing brain MRI surveillance.
Jacqueline Aredo, MD
Resident at UCSF
Hugo Kitano, MS
Software Engineer in Seer
Eric Chow, MS
Medical student at Chicago Medical School in Rosalind Franklin University
Matthieu de Rochemonteix, MS
Quantitative Research Analyst at Citadel
Nilotpal Sanyal, PhD
Natasha (Purington) Shamas, MS
Senior Data Scientist at Genentech