| title | subtitle | layout | show-avatar |
|---|---|---|---|
People |
Members and Affiliates of the Hubbard Group |
page |
false |
Prof. Alan Hubbard
Biography: Dr. Alan Hubbard is Professor of Biostatistics, Head of the
Division of Biostatistics at UC
Berkeley, and Head of data analytics core at UC Berkeley
SuperFund. His current research interests
include causal inference, variable importance analysis, statistical machine
learning, estimation of and inference for data-adaptive statistical target
parameters, and targeted minimum loss-based estimation. Research in his group is
generally motivated by applications to problems in computational biology,
epidemiology, and precision medicine.
GitHub: ahubb40
Homepage: ahubb40.github.io
Jeremy Coyle
Biography: Jeremy Coyle is a postdoctoral scholar in Biostatistics at UC Berkeley.
His research interests include cross-validation, resampling estimators, and
optimal treatment parameters. Jeremy has applied machine learning methods to a
variety of applications, including stove use monitoring, treatment assignment
for victims of traumatic injury, and the translation of raw sensor data into
meaningful estimates.
GitHub: jeremyrcoyle
Wilson (Weixin) Cai
Biography: Wilson is a second-year graduate student in the Division of
Biostatistics at UC Berkeley and is jointly advised by Profs. Alan Hubbard and
Mark van der Laan. His research interests lie in statistical machine learning
and causal inference. Prior to Berkeley, he obtained a Bachelor's (B.Sc.)
degree in Statistics from the Univeristy of Hong Kong.
GitHub: wilsoncai1992
Nima Hejazi
Biography: Nima is a Ph.D. student in the Division of Biostatistics, where he
is jointly advised by works Profs. Alan Hubbard and Mark van der
Laan. His research interests encompass
varied aspects of causal inference and nonparametric statistics, with a focus on
the development of robust methods for addressing inference problems arising in
precision medicine, computational biology, survival analysis, and clinical
trials.
GitHub: nhejazi
Twitter: @nshejazi
Homepage: nimahejazi.org
Departmental: stat.berkeley.edu/~nhejazi
Chris J. Kennedy
Biography: Chris is a biostatistics Ph.D. student with interests in RCTs,
machine learning, and targeted causal inference applied to precision medicine,
cancer, and public health. He works with Alan on the varimpact R
package and health prediction for trauma
patients (e.g. traumatic brain injury). He also co-maintains the SuperLearner R
package, employs high performance
computing (Savio cluster, Amazon EC2, XSEDE), and is affiliated with
D-Lab, Berkeley Institute
for Data Science, and the Integrative Cancer Research Group.
GitHub: ck37
Twitter: @c3K
Homepage: ck37.com
Jonathan Levy
Biography: Jonathan is a musician returning to his mathematical roots,
pursuing a renaissance-view of marrying the endeavors of humanity in the face
of practical specialization. His interests within biostatistics revolve around
being an advocate for scientists who have critical questions and for those who
need a voice from someone trained in the field of statistics, who will look at
the science and literature as well as issues not related to science, to shed
light on health issues, rather than simply taking refuge in the most highly
promoted establishment views.
GitHub: jlstiles
Homepage: jlstiles.com
Ivana Malenica
Biography: Ivana is a second-year graduate student in the Division of
Biostatistics at UC Berkeley. Broadly, her research interests span causal
inference, high-dimensional data, machine learning, and semiparametric
theory.
GitHub: podTockom
Google Scholar:
profile
Sara Moore
Biography: Sara is a Biostatistics Ph.D. candidate in her final year of study
at UC Berkeley. She received her B.A. in Computer Science and Psychology from
Duke University and subsequently worked as a researcher in brain imaging labs
at Duke and Emory Universities. Her current research focuses on machine
learning methodology for the prediction of adverse health-related outcomes in
trauma care patients, prediction of mass trauma events using social media data,
data visualization, and statistical software package development. She also
currently works as a consultant at Genentech in South San Francisco.
GitHub: saraemoore
Twitter: @sara_e_moore
Homepage: saraemoore.com
Rachael V. Phillips
Rachael is a Biostatistics Ph.D. student. She received an MA in Biostatistics in May 2018 from UC Berkeley. She graduated with Cum Laude honors from Texas Tech University in 2015, receiving a BS in Biology with a Chemistry minor and a BA in Mathematics with a Spanish minor. Rachael’s current research involves the application of machine learning methods, nonparametric statistical estimation, statistical computing, and causal inference to large biological datasets to solve real-world problems in human health, molecular biology, and meta-analysis. She is also passionate about online mediated education and responsible conduct in research. Rachael actively works with the UC Berkeley Superfund Research Center and the National Cancer Institute Division of Cancer Epidemiology and Genetics.
GitHub: rachaelvphillips
Andre Kurepa Waschka
Biography: Andre is a fourth-year Ph.D. student in Statistics at UC Berkeley.
He finished his M.A. in Biostatistics under Dr. Hubbard in 2016. He graduated
from North Carolina State University with a B.S. in Applied Mathematics, B.S.
in Economics, and a minor in Statistics.
GitHub: akwaschka
Yue You
Biography: Yue is a Biostatistics Ph.D. student at UC Berkeley where she is jointly advised by Prof. Alan Hubbard and Prof. Mark van der Laan. Her research interests are targeted learning, machine learning, causal inference and statistical computing. She received her M.A. in Biostatistics from UC Berkeley in 2018, and her B.S. in Statistics and B.A. in Chinese Language and Literature from Fudan University, China in 2016.
GitHub: Yue-You
LinkedIn: yue-you
Prof. Romain Pirracchio
Biography: Prof. Pirracchio is a French M.D., Ph.D., hailing from Paris. He
obtained his M.D. in 2003, with a specialization in Anesthesiology and Critical
Care Medicine. In 2008, he obtained a Master's degree in Medical Research
Methodology and Biostatistics. He completed his doctoral studies in the
Department of Biostatistics and Medical Informatics (DBIM, unité INSERM U-1153)
at Hôpital Saint Louis, Paris, France in 2012 under the guidance of Prof.
Sylvie Chevret. In 2012-2013, He spent a year as a postdoctoral fellow in
Biostatistics in the School of Public Health at the University of California,
Berkeley, where he worked under the supervision of Prof. Mark J. van der Laan
and Prof. Maya L. Petersen. Back in Paris, he was the director of the surgical
and trauma ICU at European Hospital Geroges Pompidou (2013-2015) and a
researcher in Biostatistics at the INSERM U-1153 unit. In January 2015, Dr.
Pirracchio joined the Department of Anesthesia and Perioperative care at the
San Francisco General Hospital & Trauma Center (UCSF) as Associate Professor.
Since September 2016, he has been at the European Hospital Geroges Pompidou in
Paris, serving as Full Professor and Vice Chair for ICUs. He is also Adjunct
Associate Professor at UCSF and affiliate to the Division of Biostatistics at
UC Berkeley.
Homepage: romainpirracchio.org
Lucas Carlton
Administrative and Research Assistant
Colford-Hubbard Research Group
775 University Hall
Berkeley, CA 94720
Phone: 510-643-0238
Melanie Gendell
Administrative Manager
Colford-Hubbard Research Group
787 University Hall
Berkeley, CA 94720
Phone: 510-643-5742