The Han Lab Team Members

Summer Han, PhD
Principal Investigator

Dr. Han, PhD (Statistics, Yale), is an Associate Professor of Neurosurgery, Medicine, and Epidemiology & Population Health at Stanford and leads the Stanford Cancer Institute’s Cancer Data Science Core. Her lab develops data-science and statistical methods for cancer screening and outcomes, integrating EHRs, registries, claims, genomics, and environmental data. Current work spans LLM-based electronic phenotyping, causal inference, dynamic risk prediction/microsimulation, and lung-cancer studies—including Asian never-smokers. Dr. Han is PI on multiple NIH grants, including Oncoshare-Lung, which links state registry and health-system data to enable generalizable real-world evidence.

Sayeri Lala, Ph.D.
Postdoctoral Fellow

Sayeri completed her undergraduate and master’s education in Electrical and Computer Science from Massachusetts Institute of Technology (MIT, S.B. 2017 and MEng. 2019) and obtained her Ph.D. in Electrical and Computer Engineering from Princeton University (2024). At MIT, she conducted research on developing deep-learning-based methods to improve fetal brain MRI. For her Ph.D., she developed methods to improve the efficiency of clinical randomized controlled trials using methods based on causal inference and deep learning. Currently, Sayeri is developing solutions based on machine learning to analyze wearable-based physical activity data from spine surgery patients for improved postoperative monitoring and to analyze time-to-event data for dynamic risk prediction. 

Harry (Tae Yoon)Lee, Ph.D.
Postdoctoral Fellow

Harry obtained his MSc in Statistics and PhD in Health Outcomes Research at the University of British Columbia. For his PhD, he developed a decision-analytic framework for evaluating interventions for asthma. He is currently working on developing and evaluating risk model-based screening strategies for lung cancer.

Saskia Comess, Ph.D
Postdoctoral Fellow

Saskia completed a Master's degree in public health and statistics at Yale University and her PhD at Stanford University, concentrating on environmental epidemiology and biostatistical methods. For her PhD research, she developed Bayesian models for uncertainty propagation and spatial questions in epidemiology studies, focusing on the role of environmental exposures in reproductive health outcomes. Her current research expands on her interests in spatial statistics and Bayesian methods to investigate causal inference related to environmental contributions to lung cancer risk, particularly among Asian never smokers, utilizing electronic health records (EHRs) and advanced modeling techniques for various environmental factors.

Justin Lee, MPH
Biostatistician

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.
Senior Biostatistician

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. 

Victor Ritter, Ph.D.
Senior Biostatistician

Victor received his Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill in August of 2021 and is interested in statistical methods for non and semiparametric inference for time-to-event data with a focus on competing risks, cure rate, and multistate models. He developed methods for time-to-event analyses under complex sampling designs and has collaborations in various biomedical research areas. He has a particular interest in analyses of national health surveys, newborn medicine, and hospital pediatrics. Currently, Victor is currently working on estimating the parameters of the natural history model for second primary lung cancer using the NCI SEER cancer registry data.

Ingrid Luo, M.S.
Biostatistician

Ingrid completed her M.S. in Biostatistics at the University of Washington. Her current research projects include characterizing the tumor microenvironment of lung cancer patients with single-cell RNA sequencing.  

Yuhan Liu, M.S.
Biostatistician

Yuhan received her master’s degree in Biostatistics from Duke University. After that and prior to Stanford, she worked as a biostatistician at the Vanderbilt University Medical Center, where she worked on ophthalmology and pediatrics projects. In the Han Lab, Yuhan is working on analyzing SEER-Medicare data to evaluate the impact of cancer treatment on the risk of second primary lung cancer.

Mengrui (Ray) Zhang
Senior Biostatistician

Mengrui completed his Ph.D. degree in Statistics from the University of Georgia in May 2022. Mengrui’s research focuses on leveraging advanced statistical and machine-learning techniques to extract meaningful insights from complex biological datasets. His research interests include bioinformatics, deep learning/machine learning, statistical testing, high-dimensional data, non-parametric modeling, time series analysis, and spatial statistics. Additionally, he is also interested in developing new methods, tools, and pipelines for various kinds of biological datasets, especially in single cell, spatial transcriptome, RNA-Seq, metagenomics, and proteomics to support drug discovery and development.

Rafael Catoia Pulgrossi
Biostatistician

Rafael received his MS in Statistics from the University of California, Santa Cruz. His research focused on tailoring clustering methods for geo-spatial compositional data. Rafael is passionate about R programming and enjoys building tools and visualizations that uncover essential insights from complex data. Currently, Rafael is developing an R package that includes various indices for social determinants of health in the lab. 

Anna Graber-Naidich, Msc, PhD
Senior Data Scientist

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.

Fatma Gunturkun, Ph.D.
Senior Data Scientist

Fatma obtained her PhD in statistics from Dokuz Eylul University, Turkey, in 2019. Her academic interests cover several areas, such as predictive modeling, analyzing ECG signals, medical image analysis, statistical modeling, machine learning, deep learning, and data visualization for clinical decision-making. Currently, Fatma is working on abstracting recurrence after lung cancer diagnosis using CT imaging and radiology reports. 

Chloe Su, Ph.D.
Senior Data Scientist (Part-time)

Chloe received her Ph.D. in Epidemiology at Stanford. 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 to build prediction models for brain metastases and recurrence in lung cancer patients.

Annabel Tan, Ph.D.
Senior Data Scientist

Annabel obtained her PhD in Epidemiology at Stanford. She completed her Master’s in Public Health from Yale and undergraduate studies in bioengineering at Imperial College London. Her academic interests center on environmental and chronic disease epidemiology. Currently, she is working on various projects involving Oncoshare databases.

Maggie Shaw, M.S.
Data Scientist

Maggie earned an MS in Bioinformatics from Temple University (2018). At the University of Pennsylvania she focused on NGS bioinformatics in epigenetics and gene therapy. She joined Stanford in 2023 with the Curtis and Caswell-Jin labs on breast cancer studies, and now works in the Cancer Data Science Shared Resource. Her portfolio centers on LLM pipelines for EHR abstraction—pathology and radiology reports, clinical notes, and biomarkers—using human-in-the-loop curation and evaluation to produce research-grade variables for cohort discovery, trial feasibility, and real-world evidence. She leads EHR curation/extraction in Google Cloud, incorporating Oncoshare models into core infrastructure.

Emily Rodriguez
Undergraduate Student

Emily is a senior undergraduate student planning to major in Human Biology. As a pre-med student with an interest in pursuing an MD/Ph.D. program, her interest lies in the intersection between clinical practice and medical research. Currently, Emily is working to extract patient data to help develop NLP models that can assess tumor burden and help predict lung cancer metastasis and lung nodule features among Asian never smokers. 

Lydia Schwartz
Undergraduate Student

Lydia is an undergraduate student at Stanford University studying Biomedical Computation and Public Policy. She is passionate about leveraging data science and AI to improve cancer therapies and make them accessible to underserved communities like her native Eastern Shore of Maryland. Previously, at Moffitt Cancer Center, she employed predictive modeling to develop adaptive therapy regimens for skin cancer patients. Lydia is currently contributing to the development of standardized indices for measuring neighborhood socioeconomic status in cancer risk prediction.

Andrew Cheng, B.S.
Graduate Student in Computer Science

Andrew is a master's student in Computer Science at Stanford with a concentration in artificial intelligence. He completed his bachelor's degree from Rutgers University-New Brunswick with a double major in Computer Science and Biomathematics, where he worked on spatial transcriptomics and protein structure prediction. Currently, he is interested in developing advanced statistical and machine learning methods for spatially resolved transcriptomics data.

Rika Terashima, M.D.
Graduate Student in Epidemiology and Clinical Research

Rika is a master’s student in epidemiology and clinical research at Stanford. She completed medical school at Gunma University in Japan. Prior to her studies, she worked as a physician at the Center Hospital for the National Center for Global Health and Medicine located in Tokyo. Currently, she isworking on projects for assessing tumor burden levels and building prediction models for lung cancer metastases.

Judy Fan, M.S.
Research Assistant

Judy completed her BSc in Physiology at the University of British Columbia and an MS in Epidemiology at Stanford University. Currently, she is working on projects focused on lines of treatment, tumor burden, and annotation of key clinical variables for lung cancer survival in collaboration with Sutter Health residents.

Grant Nieda, B.S.
Research Assistant

Grant completed his undergraduate degree from International Christian University in Japan, where he majored in biology and minored in psychology. During his degree, he researched coral health from protein and lipid reserves under environmental stress. Now he is interested in human health and application of modern statistical methods. Grant is currently working on various LLM projects to extract patient data in oncology from PET/CT and MRI radiology reports.

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.

Eunji Choi, MPH, PhD (former postdoc/instructor)

Assistant Professor in Population Health Sciences at Cornell University

Aparajita Khan, PhD (former postdoc)

Assistant Professor in Computer Science at the Indian Institute of Technology (IIT) Roorkee 

Anya Fries, B.S. (former MS student in MS&E)
PhD Student in Statistics at ETH Zürich

Ines Dormoy, B.S. (former MS student in ICME)

Software Engineer at Waymo 

Jane Hua, B.S. (former MS student in Epidemiology)

Clinical Coordinator at Stanford University School of Medicine

Sophia Luo, B.S. and M.S.

Medical student at the Vanderbilt University School of Medicine

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

Renuka Devi Chintapalli, Medicine, MB and BChir  Postdoctoral Fellow

Megan Chang, B.A.
Graduate Student in Epidemiology and Clinical Research

Rakshit Kaushik
Undergraduate Student

Zhenjiang Fan, Ph.D. 
Postdoctoral Fellow