PhD Students

2018- Incoming Cohort


Hao Geng, MS

Education: Rice University - Statistics; Brown University - MS Epidemiology/Biostatistics

With a background in statistics and epidemiology, my research interests include chronic disease epidemiology and statistical modeling of public health data. At Dartmouth, I hope to gain a more comprehensive understanding of health research methods.

Rebecca Lebeaux, BS

Education:  Emory University - Anthropology

I am primarily interested in the epidemiology and mathematical modeling of infectious diseases and microbes. While at Dartmouth, I hope to learn new technical skills and apply them to research focusing on disease dynamics and inequities. A native to New Hampshire, in my free time I look forward to revisiting my favorite places in New England (Mt. Monadnock, Ben & Jerry’s, and Cape Cod) and exploring more (Mt. Washington, Burlington, and Portsmouth).

Joshua Levy, BA

Education: University of California, Berkeley - Physics

As a former genomics machine learning researcher and software developer from UC Berkeley, I hope to synthesize methods employed from many different disciplines to create unique solutions to society's pressing challenges. I aim to leverage big data, machine learning, and network analysis to grasp some of the underlying trends in genomics and public health and exploit this knowledge to craft tractable and effective responses. In my spare time, I enjoy training for intense obstacle course races, playing basketball, hiking and exploring nature, and reading.

Catherine Pollack, BS

Education:  University of Virginia -  Biomedical Engineering & Applied Statistics

My research interests are primarily focused on how to apply rigorous biostatistical and computational methodologies to health care policy problems, particularly as they relate to health equity.

Iben Ricket, MPH

Education: St. Mary's College - Anthropology; Tulane University -  MS Epidemiology/Biostatistics

I have a background in epidemiology and data science. My prior research focused on computable phenotype development, analytical techniques for harmonizing clinical data, and use of data collection tools and information technology in developing countries. Within the QBS program, I hope to learn and apply novel computational and analytical techniques for optimizing re-use of semi-structured and unstructured biomedical and clinical data. 

Kwame Wiredu, MA


  • University of Science & Technology (Ghana) — Human Biology and Clinical Medicine
  • University of Denver — International Relations & Global Health

To be a physician-scientist with focus on biomarker discovery through the approach of -omics analysis, data mining techniques and mathematical modeling. Specific interests include metabolomics / genomics/ secretomics as they relate to disease and/or environmental exposures.

Tiankang Xie, BS


University of Wisconsin, Madison - Mathematics

I have broad interests in computational biology and my current research interest is developing Mathematical and Statistical tools to enable large-scale computation, for example, molecular level computation, and discover exciting evidences of our bodies. I had experiences in processing medical imaging data for children suffering from autism. Outside classes, I enjoy skiing and playing badminton. 

Shiwei Xu, BS

Education: Jilin University - Biology; University of Manchester (England) Genetics

I am currently interested in applying biostatistics and bioinformatics methods to decipher genetics diseases from the perspectives of transcriptomic and proteomic studies. I see great prospects in mathematically modelling pathogenesis as well as looking for novel biomarkers to improve diagnosis and prognosis for current therapeutic approaches.


Noelle Kosarek, BS

Mentors: Michael Whitfield, PhD & Patricia Pioli, PhD

Education: Lafayette College - Biology

My research interests include gene expression and noncoding RNA analysis of patients suffering from rare autoimmune diseases and cancers. Outside of the lab I enjoy skiing, hiking, running, and hanging out with my two bunnies, Rosalind Fur-anklin and Fuzz Aldrin.

Marek Svoboda, BA(MD-PhD)

Mentors: Giovanni Bosco, PhD

Education: Columbia University-Nueroscience

Before starting my MD-PhD studies at Dartmouth, I graduated from Columbia University with B.A. in Neuroscience and Behavior. I am interested in Neurology in the clinic, and Neuroscience in the lab. More specifically, I am using both wet lab and computational techniques to study the underlying genetics, molecular interactions, and resulting phenotypic changes related to memory impairment in fruit fly and mouse models.

Yuka Moroishi, BS

Mentors: Jiang Gui, PhD & Margaret Karagas, PhD

Carnegie Mellon University - Statistics

My research interests include the statistical modeling of population health data and infectious disease epidemiology. In a time where collaboration is encouraged to produce optimal results, QBS recognizes that biostatistics, bioinformatics, and epidemiology may be integrated to make further advancements in biomedical research.

Quang Nguyen, BS

Mentors: Anne Hoen, PhD & Rob Frost, PhD

Education: Bates College - Biological Chemistry and Mathematics

I am interested in using bioinformatics and statistical methods to tackle epidemiological questions relating to the infant gut microbiome.  Working with Dr. Hoen and Dr. Frost, I hope to develop new methods utilizing multi-omics datasets to investigate different ways to look at the microbiota from an ecosystem perspective.  I hope to then integrate these methods to existing epidemiological models to address questions about early childhood exposure and subsequent health outcomes.  

Robert Quon, BS, MHS

Mentors: Barbara Jobst, PhD, MD

Education: Creighton University, Biology and Psychology, •Johns Hopkins University, MHS Mental Health, Certificate in Gerontology

My research interests are in decoding how the brain works, in order to outline the etiology of neuropathology. I will utilize my skills in biostatistics, bioinformatics, and epidemiology to enhance the detection of chronic neurological conditions with the hope of delaying or preventing its progression.

Xin Ran, B.Eng, MS

Mentors: James O'Malley, PhD

Education: Beijing Jiaotong University - Biomedical Engineering, Certificate in Interpreting • University of Pennsylvania - MS Bioengineering

My research interest lies in biostatistics especially the topics of tackling with high dimensional data and missing data. When I was working on my Master's thesis, I became interested in biostatistics and realized the importance for Bioengineers to be equipped with statistical skills. I'm looking forward to life in New Hampshire and the diverse outdoor activities.

Benjamin Ricard, BS, MS

Mentors: Saeed Hassanpour, PhD

Education: Texas State University, Biochemistry •Texas State University, MS Biochemistry

I am interested in application of statistical methods to understand contemporary problems in data science, particularly the 'omic' fields and finance.


  • Graduate student of the year, Department of Chemistry and Biochemistry, Texas State University
  • Chartered Financial Analyst (CFA) Global Competition Regional Finalist
  • William Lowell Putnam Mathematical Competition Representative of Texas State University

Qingyuan Song, BS, MS

Mentors: Saeed Hassanpour, PhD

Education: University of Pittsburgh, Biology • Carnegie Mellon University, MS Computational Biology

My research interests include the study of genetic diseases such as cancers, using the combination of computational, statistical and machine learning methods, along with my background knowledge in biological sciences. Besides, I'm looking forward to go camping, kayaking, ice skating, skiing and explore nature around New Hampshire.

Yiwei Yuan, BS

Mentors: Michael Whitfield, PhD

Education: Fudan University, Biological

My research interests are human health and biomedicine-associated data mining and analysis. I would like to explore biological and health problems in interdisciplinary way and am happy to have the chance to work with a variety of faculty members in QBS.


Carly Bobak, BA, MSc

Mentors: Jane Hill, PhD and James O'Malley, PhD

Education: University of Guelph - Applied Mathematics and Statistics with a Co-op Option, Certificate in Business, University of Guelph - MSc Applied Mathematics

While studying applied mathematics and statistics at the University of Guelph, I quickly realized that mathematical thinking provides important insight in a variety of disciplines, but particularly in the realm of biomedical science. Ever since I've been passionate about data-driven approaches to research in human health, particularly in the realm of infectious disease. When I'm not thinking about science (do we ever really stop thinking about science?) you can usually find me hanging out with my dog, throwing spontaneous dinner parties, or dragging my peers out to various different adventures throughout the New England area.

Guanqing Chen, BS, MA

Mentor: James O'Malley, PhD

Education: Nanyang Technological University, Singapore - Mathematics and Statistics, University of Rochester - MA Statistics

My research interests are causal inference, network analysis and longitudinal data analysis. I like QBS because this integrated interdisciplinary program in biostatistics, bioinformatics and epidemiology will broaden my knowledge base, strengthen my skills in translational sciences and lay a solid foundation for pursuing my career in biomedical and translational research.

Monica Espinoza, BS

Mentor: Michael Whitfield

Education: University of California Irvine - Biology

My research interests include genomics, biostatistics, rare diseases, and the human microbiome- interests that I have combined in my work with Dr. Michael Whitfield. The Whitfield lab studies Scleroderma, a rare autoimmune disease characterized by fibrosis and heightened immune response in various organ systems of the body. In his lab, I am currently exploring the potential associations of the epithelial microbiome with the host immune response presented in patients with Scleroderma (SSc). This is part of an investigative effort to elucidate the potential environmentally-driven etiology of SSc. As a 2016-2017 Burroughs Wellcome Scholar, I was given the opportunity to explore the possibility of a hybrid PhD, one that includes laboratory science and data science training. These opportunities only became available to me through the encouragement of cross-training in the multidisciplinary space that QBS offers. Outside of school, I can be found socializing with friends or exploring the New England area.

Yasmin Kamal, BS (MD-PhD)

Mentors: Christopher Amos, PhD and Robert Frost, PhD

Education: Smith College - Biochemistry and Neuroscience

My research interests are cancer immuno-genomics. The Amos lab in genomic medicine was a perfect fit for me given my interests in genomics. Dr. Amos and my co-mentor Dr. Robert Frost have been excellent mentors. Working in the Amos lab, I was able to mesh my biochemistry and medical background to design a project focused on the application of immunotherapy in various types of cancer. Specifically, I am examining the interaction of immune cells in the tumor microenvironment with neoplastic cells using sequencing data and determining the impact of immune cells on driving cancer pathophysiology�specifically identifying unique immune signatures indicative of metastasis. In the Amos lab, I am able to collaborate with clinicians, immunologists, surgeons, and bioinformaticians, and am challenged to use a variety of tools to tackle key questions in cancer immunology.

Jai Woo Lee, BS, MS

Mentor:Jiang Gui, PhD

Education: Carnegie Mellon University - Mathematics and Computer Science, Dartmouth College - MS Computer Science

I am originally from South Korea, and I usually enjoy walking or hiking, and/or listening to any kind of music or political podcasts. Before entering graduate programs at Dartmouth College, I mainly focused on graph theory and its application with/to computational methods in Operations Research in the field of Theoretical Computer Science. My current research interests lie in utilizing and developing statistical and computational methods in Bioinformatics, Biostatistics, or Machine Learning to analyze biomedical data related to various fields of Epidemiology. Thanks to enthusiastic faculty and broad scope of interesting research areas in Quantitative Biomedical Sciences (QBS) program, I have worked on statistical and computational methods to study protein-protein interaction, to learn more about the application of Multifactor Dimensionality Reduction (MDR), and to analyze placental metal concentrations data collected by the New Hampshire Birth Cohort Study.

Jennifer Luyapan, BS

Mentors: Christopher Amos, PhD and Michael Passarelli, PhD

Education: University of California Davis - Cell Biology

My research interests include genetic epidemiology and cancer prevention. My research background includes genetics, protein biochemistry, cancer biology and clinical trial research. I am studying the association of genetic variations of folate metabolism genes and colorectal adenoma recurrence to better understand folate metabolism and how it can influence colorectal adenoma development.

Daniel Mattox, BS

Mentor: Christopher Bailey-Kellogg, PhD

Education: University of North Carolina at Chapel Hill - Quantitative Biology

My research is focused around integrating computational and experimental approaches to protein design. More specifically, I am interested designing and applying novel computational tools to aid and supplement experiments. In the Bailey-Kellogg Lab, I am working to better understand glycan-protein interactions and possible roles for lectins in bioengineering. Outside of research, I enjoy exploring the beautiful New England countryside through any number of outdoor sports.


  • NIH-Dartmouth Big Data to Knowledge (BD2K) Fellow​

Meghan Muse, BS

Mentors: Brock Christensen, PhD and Diane Gilbert-Diamond, ScD

Education: Dartmouth College - Biology

I am interested in studying maternal and child health through the lens of bioinformatics and epidemiology. I chose the QBS program at Dartmouth because it provides the unique opportunity to be cross trained in these fields as well as the field of biostatistics. Outside of the lab, I enjoy running, hiking, and taking advantage of all the other outside activities that New Hampshire has to offer.

Xingyu Zheng, BS

Mentors: Christopher Amos, PhD and Robert Frost, PhD

Education: Fudan University - Biology

My research interests are bioinformatics and biostatistics, especially cancer genomics and statistical genomics. I chose QBS because it's an interdisciplinary program which is so exciting and I enjoy analyzing big data. I'm working in the Amos lab. Dr. Amos and Dr. Robert Frost co-mentor me and give much help and advice to me. Outside of the lab, I like walking around and really love the trees all around here which bring surprises in all seasons.


Alexander Titus, BS, BA

Mentor: Brock Christensen, PhD

Education: University of Puget Sound - Biology, Biochemistry

I'm interested in data integration methods for 'omic' analyses. There is a growing volume of federally funded, publicly available data that were collected on different technologies. I develop methods to integrate these data sets together for analysis. Specifically, I'm interested in the prospects of combining genomic, transcriptomic, and proteomic data to identify the effect of miRNA-related genetic variation on disease phenotypes. Im also interested in reference-based and reference-free cell mixture deconvolution, using cell type specific methylation markers as additional parameters in modeling

Awards, Abstracts, and Poster Presentations

  • NIH-Dartmouth Big Data to Knowledge (BD2K) Fellow​
  • Titus AJ*, Houseman EA*, Johnson KC, Christensen BC (2016) methyLiftover: cross-platform DNA methylation data integration. Bioinformatics. 32(16):2517-9. *co-first
  • Titus AJ, Faill R, Das AK (In Press) Automatic identification of co-occurring patient events. Proceedings of the 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. 579-86.
  • Titus AJ, Faill R, Das AK (2016) Automatic identification of co-occurring patient events. Workshop on Methods and Applications in Healthcare Analytics. 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM, Seattle, WA, USA. Oral Presentation.
  • Titus AJ, Houseman EA, Johnson KC, Christensen BC (2016) methyLiftover: cross-platform DNA methylation data integration. Computational Life Sciences Workshop @ Bayer. Berlin, Germany. Poster

Jason Wells, BS

Mentor: Todd Miller, PhD

Education: University of California, Davis - Genetics

I have a background in genetics and genomics research. Previous projects that I have worked on mainly focused on muscular dystrophy from a genomics perspective. My current interests include using genomic and bioinformatic approaches to study various aspects of cancer.

Lia Harrington, BS, MS

Mentors: Saeed Hassanpour, PhD and Matthew Havrda, PhD

Education: Bucknell University - Nueroscience • University of Montana - MS Psychology

My research interest is in leveraging big data and bioinformatics tools to understand diseases, such as cancer. My current project is developing better predictive models of colon cancer risk via information text extraction from electronic medical data. In addition, through the Burroughs-Wellcome Fellowship, I am working with Dr. Havrda to better understand the biological basis of Parkinson's disease.

Katherine Antosca, BS

Mentor: Todd MacKenzie, PhD and George O'Toole, PhD

Education: University of New Hampshire, Durham - Mathematics

My current research interests center around the function of the microbiome. I am currently evaluating the role of breastfeeding and probiotics in the development of the gut microbiome of children with Cystic Fibrosis. We hope to determine the specific mechanisms associated with better health outcomes of Cystic Fibrosis patients. I am also creating a program to provide insight into the metabolic function of unclassified microbes within the microbiome.

David Chen BS, MS

Mentor: Brock Christensen, PhD

Education: Pacific Lutheran University - BS Biology, BA Political Economy • University of Michigan-Ann Arbor -MS Biochemistry

My  research focus in the Christensen Lab is integrating epigenetic and proteo-genomic data for cancer subgroup identification and characterization using machine-learning, statistical and informatics approaches. My recent project aims to identify somatic alteration biomarkers in the aggressive triple negative breast cancer. My ongoing work includes profiling DNA methylome, transcriptome, and proteome of breast cancer and integrating multiple tumor molecular profiles for efficient predictive analytics. Through QBS and the Burroughs-Wellcome Big Data in Life Sciences training program, I also had the opportunity of volunteering as a biostatistics consultant at the Dartmouth-Hitchcock Medical Center, assisting clinicians and medical researchers with analytics, statistical inference and data visualization for publications and grant proposals. Both in QBS and at Dartmouth, I participate in the teaching of biostatistics, epidemiology, machine learning, and health data science courses at the undergraduate and graduate level, as well as help improve the QBS master’s and PhD programs as a teaching fellow. 


  • Teaching Fellowship in QBS, 2018-19
  • Burroughs-Wellcome Big Data in Life Sciences Training Grant, 2016-18
  • 4X coding competition awards, Major League Hacking hackathons at U.S. colleges/universities
  • Analytics and Big Data Summit Financial Support, 2018
  • Genome Informatics Travel Award, 2017


Jennifer Franks, BS

Mentor: Michael Whitfield, PhD

Education: Purdue University - Genetics, Applied Statistics

My research interests are human genetics, computational immunology, machine learning, and statistical methods for high-dimensional data. My current projects in the Whitfield lab focus on classifying intrinsic molecular subtypes and characterizing the immune repertoire in patients with systemic sclerosis. I really enjoy working with Michael Whitfield because I am able to generate data at the bench and also analyze results using novel computational methods. Through the Big Data in the Life Sciences Training Program funded by Burroughs-Wellcome, I am able to collaborate with Chris Bailey-Kellogg using sequence and structural models to explore cross-reactivity in the adaptive immune system.

Sara N. Lundgren, BA

Mentors: Brock Christensen, PhD and Anne Hoen, PhD

Education: University of Chicago - Comparative Human Development

My thesis work focuses on the developing infant gut microbiome in the New Hampshire Birth Cohort Study, mentored jointly by Dr. Brock Christensen and Dr. Anne Hoen. . I am interested in characterizing the relation maternal factors such as diet and weight and the human milk microbiome and metabolome, and how that variation affects the gut microbiome in early life. My other research interests include epigenetics and usage of machine learning methods for integrating multiple high dimensional datasets.


Ellen Nutter, BS

Mentors:Tracy Onega, PhD, Giovanni Bosco, PhD and Jennifer Doherty, PhD

Education: University of Great Falls - Mathematics

My area of interest is translational research: participating in all the steps in the process from discovery to delivery is important to me. Here at Dartmouth I work with Jen Doherty's Cancer Epidemiology Laboratory and Tracy Onega's Population Health Laboratory. Working with both Dr. Doherty and Dr. Onega allows me to explore the spectrum of quantitative research topics. We work on a broad spectrum of topics from genetic association studies to geographic analyses pertaining to lung cancer screening usage for cancer prevention, prognosis, and treatment.

Awards, Abstracts, and Poster Presentations

  • Big Data in the Life Sciences Trainee funded by Burroughs-Wellcome Fund Program
  • Recent Publications

  Mavra Nasir, BS, MS

Mentor: Jane Hill, PhD

Education: McGill Univsersity - Biology • New York University - MS Bioinformatics

In the Hill lab, my current project is focused on developing breath-based diagnostic for cystic fibrosis patients with polymicrobial lung infections.This involves analysis of volatile organic compounds (VOCs) produced by Pseudomonas aeruginosa and Staphylococcus aureus infection in cystic fibrosis patients using GCXGC -TOFMS. Analysis of volatile organic compounds (VOCs) in the breath that can be used to distinguish between antibiotic-sensitive and antibiotic-resistant strains of S. aureus, particularly MRSA and VRSA using GCXGC -TOFMS Development and application of machine learning methods for fingerprinting VOC profiles.


See QBS Alumni


Craig MacKenzie, BS, MS

Mentor: Gevorg Grigoryan, PhD

Education: University of New Hampshire Durham - Mathematics • University of Illinois - MS Mathematics

My research involves mining massive amounts existing data on proteins for the purpose of computationally designing novel proteins. More specifically, we have determined a small set of structural motifs capable of describing almost all structural interactions found in proteins (with known structures). We are now using sequence-structure relationships from these motifs to design novel proteins. Beyond this I'm interested in computationally designing proteins (and other molecules) for use in synthetic biology, nanomaterials and therapeutics. I have a bachelor's degree in Mathematics from the University of New Hampshire. The interesting and diverse research conducted by QBS faculty drew me to the program which I joined in 2012. When I joined the program I did not plan on working in the field of protein design, but got hooked after doing rotations in the labs of Chris Bailey-Kellogg and Gevorg Grigoryan my first year.

Qian Yang, BE, MEM

Mentor: Tor Tosteson, PhD

Education: University of Michigan‐Shanghai Jiao Tong University (UM‐SJTU) Joint Institute, Shanghai Jiao Tong University - Electrical and Computer Engineering •Thayer School of Engineering, Dartmouth College- MEM Engineering Management

Now a fourth year QBS PhD candidate, I am a member of the Biomedical Statistical Science Laboratory (BSSL) directed by Dr. Tor Tosteson. My current research focuses on joint modeling of longitudinal medical cost and survival. My research interests also involve decision analytic modeling and comparative effectiveness research. I enjoy the emphasis of novel statistical methodology and their application to real healthcare data and challenges which is the hallmark of our lab.

James Rudd, BS, MS

Mentor: Jennifer Doherty, PhD

Education: North Carolina Central University - Music • North Carolina Central University - MS Computer Science

I received my MS in Computer Science from North Carolina Central University and joined the Quantitative Biomedical Sciences program in order to better integrate my computation background with biostatistical and epidemiological frameworks. My research interests involve the use of bioinformatics to solve epidemiological problems. As a member of the Doherty lab, I am working to model molecular subtypes of ovarian cancer and have been awarded an F31 fellowship from the National Cancer Institute