The Han Lab Team Members

Summer Han, PhD
Principal Investigator

Dr. Han is an Associate Professor of Neurosurgery, Medicine, and Epidemiology & Population Health in the Stanford School of Medicine. She holds a PhD in Statistics (Yale, 2009) with a 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
Instructor

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
Postdoctoral Fellow

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
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.

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. 

Yann Le Guen, Ph.D.
Senior Bioinformatician

Yann graduated in 2015 from both Telecom Paris and Imperial College London, respectively, with an MSc in Computer Science and an MSc in Biomedical Engineering. Then, he received a PhD in 2018 focusing on imaging genetics at Neurospin (Paris-Saclay University), analyzing MR images and genomicsdata to decipher the genetic causes underlying the well-characterized brain asymmetries that support human language processing. In the Han Lab, Yann is working on developing an analytic pipeline for polygenic risk score analyses for various second primary cancers using UK Biobank data.

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.

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.

Jane Hua, B.S.
Graduate Student

Jane Hua obtained her bachelor’s degree in biochemistry from Wellesley College in 2021, and subsequently joined Stanford School of Medicine for her master's degree in Epidemiology and Clinical Research. Her research interest is in lung cancer, including risk prediction, diagnosis, and treatment response. She is currently working on several projects to evaluate racial disparity in the risk of second primary lung cancer and critically assess the causal association between various types of cancer and Alzheimer's disease.

Ines Dormoy, B.S.
Graduate Student at the Institute for Computational and Mathematical Engineering

Ines is a master's student at the Institute for Computational and Mathematical Engineering at Stanford. She holds a bachelor's degree in applied mathematics from école CentraleSupélec in France. Her prior experience includes work in the fields of Natural Language Processing, fine-tuning Language Models(LLMs), and Multimodal Deep Learning. At present, her research focuses on the integration of causal inference and deep learning techniques to assess surveillance strategies for lung cancer using electronic health record (EHR) data. 

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.

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

Megan is a master’s student in epidemiology and clinical research at Stanford. She completed her undergraduate education at Pomona College (Claremont, CA) in May 2023, where she majored in Molecular Biology and minored in Music. Currently, Megan is abstracting patient data to help develop NLP models that can assess tumor burden levels to aid in lung cancer treatment decision-making.

Rakshit Kaushik
Undergraduate Student

Rakshit is an undergraduate student at Stanford University and is engaged in the study of Mathematicsand Computer Science. With a profound interest in data science and artificial intelligence, he hasshown versatility by contributing to both academic research and industry projects. His expertise lies in applying computational methods to solve complex problems. Presently, Rakshit is involved in the Tumor Burden project, where he is applying his skills in data analysis to advance research in this critical area.

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.

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