New Faculty - Winter 2021
Ganesh S. Anand, associate professor of chemistry, is a structural biologist who studies a variety of proteins, including multiprotein complexes and membrane proteins involved in cell signaling and proteins that form the capsid, or outer shell, of viruses. He uses an imaging technique called hydrogen/deuterium exchange mass-spectrometry (HDX-MS) in combination with molecular simulations to study protein dynamics.
In 2011, the Waters Corporation recognized Anand’s lab as one of its Centers for Innovation—the first such center in Asia. Anand’s research has been published in scientific journals such as Nature Communications, PLoS Computational Biology, and the Biophysical Journal.
Prior to joining the faculty at Penn State, Anand served as assistant professor and then associate professor of biology and director of the Protein and Proteomics Centre at the National University of Singapore and SingMass (Singapore National Laboratory for Mass Spectrometry) from 2006 to 2019 and as a postdoctoral fellow at the University of California, San Diego, from 2000 to 2006. He earned a bachelor’s and a master’s degree in biological sciences at the Birla Institute of Technology and Science in Pilani, India, in 1992 and a doctoral degree in biochemistry at Rutgers University in 2000.
Stephen Berg, assistant professor of statistics, works to develop statistical tools for data with spatial and temporal dependencies, particularly of the kind arising in environmental data. His research areas include simulation-based inference (especially Markov chain Monte Carlo and stochastic approximation methods), modeling in landscape ecology and for wildlife disease, and numerical optimization.
Prior to joining the faculty at Penn State, Berg earned a doctoral degree and a master’s degree in statistics at the University of Wisconsin–Madison in 2020 and 2017, respectively. He earned a bachelor’s degree in mathematics at Iowa State University in 2013.
Zhen Bi, assistant professor of physics, is a theoretical physicist working in quantum condensed matter physics. He is particularly interested in understanding exotic quantum phases and phase transitions in strongly correlated quantum materials. A deeper understanding of these topological phases and phase transitions could help in the design of powerful new materials that could provide venues for quantum applications in the future.
In 2017, Bi was awarded a Pappalardo Fellowship—a postdoctoral program that identifies, recruits, and supports the most talented and promising young physicists at an early stage of their career—from the Massachusetts Institute of Technology (MIT).
Prior to joining the faculty at Penn State, Bi was Pappalardo Fellow at MIT from 2017 to 2020. He earned a doctoral degree in physics at the University of California, Santa Barbara, in 2017 and a bachelor’s degree in physics at Peking University in 2012.
Nikki Crowley, assistant professor of biology, uses techniques from electrophysiology, systems neuroscience, and behavioral health to study the cellular basis of alcohol addiction. Additionally, she studies the interplay of alcohol addiction with neuropsychiatric disorders and how addiction differs between sexes and across the lifespan, with the ultimate goal of informing new sex- and age-specific treatments.
Crowley has published more than 20 papers in journals such as Nature Neuroscience, Cell Reports, Neuron, and the Journal of Neuroscience. Her work is funded by the National Institute on Alcohol Abuse and Alcoholism and the Brain & Behavior Research Foundation.
Crowley joined the faculty at Penn State as an assistant research professor of biobehavioral health in 2017 and served as a postdoctoral research fellow at Penn State from 2016 to 2017. She previously served as an Intramural Research Training Award Fellow at the National Institute on Alcoholism and Alcohol Abuse. Crowley earned a doctoral degree in neurobiology at the University of North Carolina in 2015, a master’s degree in psychology at the University of North Carolina Wilmington in 2011, and a bachelor’s degree in psychology at James Madison University in 2008.
Ian Czekala, assistant professor of astronomy and astrophysics and Institute for Computational and Data Sciences Faculty Fellow, uses radio interferometry—a technique that combines signals from multiple telescopes to make high-resolution images—to study the disks of gas and dust from which planets form. He frequently uses the Atacama Large Millimeter/submillimeter Array (ALMA), which is an array of 66 antennas in northern Chile built by an international collaboration. Czekala is interested in improving inference methods for analysis of complex spatiokinematic astronomy data and other astrostatistical challenges.
Czekala was honored with certificates of distinction in teaching in 2013 and 2014 from Harvard University. He has authored or coauthored more than 35 scientific papers in journals such as the Astrophysical Journal and the Astronomical Journal and has given more than 30 invited research talks at institutions across the United States, Europe, and Asia.
Prior to joining the faculty at Penn State, Czekala was a NASA Hubble Fellowship Program Sagan Postdoctoral Fellow at the University of California, Berkeley, from 2018 to 2020 and a Porat Postdoctoral Fellow at Stanford University from 2016 to 2018. He earned a doctoral degree and a master’s degree in astronomy and astrophysics at Harvard University in 2016 and 2012, respectively, and a bachelor’s degree in aerospace engineering and astronomy at the University of Virginia, where he was a Jefferson Scholar, in 2010.
Zoltan Fodor, professor of physics, studies elementary particle physics and nuclear physics. He is interested in the properties of fundamental subatomic particles, like quarks and gluons, and of hadrons, which include protons and neutrons and are made up of quarks and gluons. He studies quantum chromodynamics, a quantum field theory exploring strong interactions between these subatomic particles, as well as the properties of dark matter.
Fodor’s research calculating the mass of some subatomic particles was named one of the top 10 scientific breakthroughs of the year in 2008 by the editors of the journal Science. His research has been published in journals such as Nature, Science, Physical Review, and the Journal of High Energy Physics. Fodor was honored with the Computerworld Award in 2000 and the Prize of the Hungarian Academy of Sciences in 1998. Fodor is a Fellow of the European Physical Society and an honorary member of the Hungarian Academy of Sciences.
Prior to joining the faculty at Penn State, Fodor was a professor of physics at the University of Wuppertal in Germany from 2003 to 2020 and an associate professor and then professor of physics at Eotvos Lorand University in Budapest, Hungary, from 1998 to 2003. Prior to that, he held research positions at the High Energy Accelerator Research Organization (KEK) in Tsukuba, Japan, the Deutsches Elektronen-Synchrotron (DESY) in Hamburg, Germany, and the European Organization for Nuclear Research (CERN) in Geneva, Switzerland. He completed a master’s degree and a doctoral degree in physics at Eötvös Loránd University in 1987 and 1990, respectively.
Pierre-Emmanuel Jabin, professor of mathematics, is known for his work in partial differential equations and kinetic theory. He is particularly interested in the theory of transport and advection phenomena and in systems with many interacting particles or agents, which have applications in the fields of physics and biosciences.
Jabin has published more than 70 scientific articles and has presented many invited talks, including as an invited speaker at the International Congress of Mathematicians in Rio de Janeiro in 2018. He serves as editor-in-chief of the journal Networks and Heterogeneous Media and serves on the editorial board of several other journals, including Mathematical Models and Methods in Applied Sciences, Kinetic and Related Models, and the SIAM Journal on Mathematical Analysis.
Prior to joining the faculty at Penn State, Jabin was a professor at the University of Maryland, where he served as director of the Center for Scientific Computation and Mathematical Modeling. Prior to that, he was a professor at the Université Nice-Sophia Antipolis in France from 2004 to 2011 and an assistant professor at the École normale supérieure in France from 2000 to 2004. While a student at the École normale supérieure, Jabin earned a doctoral degree in mathematics in 2000, a master’s degree in mathematics in 1997, and a bachelor’s degree in mathematics and physics in 1996 at the Pierre and Marie Curie University, also known as the University of Paris VI.
Nicole Lazar, professor of statistics, studies how statistics affects scientific practice, including fundamental problems in statistics such as model selection, multiple testing problems, and likelihood theory, specifically in the context of modern large-scale data analysis. She is also interested in the analysis of functional neuroimaging data, including from functional magnetic resonance imaging (fMRI). Lazar takes a cross-disciplinary approach to her research and has been involved in the application of topological data analysis methods to questions of interest in psychology and climatology.
In 2008, Lazar authored the book The Statistical Analysis of Functional MRI Data, published by Springer. Additionally, a column she wrote for CHANCE Magazine was published in the 2014 edition of the Princeton University Press book The Best Writing on Mathematics. Lazar served as the president of the Caucus for Women in Statistics in 2019. She is an elected member of the International Statistical Institute and a Fellow of the American Statistical Association.
Prior to joining the faculty at Penn State, Lazar was an associate professor and then professor of statistics from 2004 to 2020 at the University of Georgia, where she also served as interim department head from 2014 to 2016. She was an assistant then associate professor at Carnegie Mellon University from 1996 to 2004. Lazar earned a doctoral degree in statistics at the University of Chicago in 1996, a master’s degree in statistics from Stanford University in 1993, and a bachelor’s degree in psychology and statistics at Tel Aviv University in 1988.
Joel Leja, assistant professor of astronomy and astrophysics and Institute for Computational and Data Sciences Faculty Fellow, focuses his research on understanding the processes of galaxy formation through the use of large surveys and statistics. He specializes in fitting flexible models to galaxy photometry and spectra, building and exploring analytical and theoretical models of galaxy evolution, and astrostatistics.
Leja was awarded the Brouwer Prize at Yale University in 2019, which is awarded to a student for a contribution of unusual merit to astronomy during their doctoral thesis. He has authored or coauthored 47 scientific papers in journals such as The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.
Prior to joining the faculty at Penn State, Leja was a National Science Foundation Astronomy and Astrophysics Fellow from 2017 to 2020 and a postdoctoral fellow from 2016 to 2017 at the Center for Astrophysics | Harvard & Smithsonian. He earned a doctoral degree and a master’s degree in astronomy at Yale University in 2016 and 2012, respectively, and a bachelor’s degree in physics and astrophysics at the University of California, Berkeley, in 2010.
Hyebin Song, assistant professor of statistics, focuses on developing methods to overcome statistical and computational challenges in modern data sets, which are often complex, large-scale, and high-dimensional. She is particularly interested in developing statistical techniques to help improve our understanding of biological structures from data, especially protein and gene data.
Prior to joining the faculty at Penn State, Song worked as a statistician at the Bank of Korea. She earned a doctoral degree in statistics at the University of Wisconsin–Madison in 2020 and a bachelor’s degree in applied statistics from Yonsei University in Korea in 2012.
Xiang Zhu, assistant professor of statistics, develops statistical and computational tools at the interface of statistics and genetics to study the genetic basis of human complex traits and diseases. Specifically, his interdisciplinary research centers on developing novel statistical methodology and computational frameworks to extract useful information and produce novel insights from large-scale genetic association scans of complex traits and high-throughput functional measurements of the human genome.
Zhu has authored or coauthored scientific papers in journals including Nature Genetics, Nature Communications, and the Annals of Applied Statistics.
Prior to joining the faculty at Penn State, Zhu was a Stein Fellow at Stanford University from 2017 to 2020. He earned a doctoral degree in statistics at the University of Chicago in 2017 and a bachelor’s degree in statistics at Nankai University in China in 2012. He has been a biostatistician (without compensation) at the VA Palo Alto Health Care System since 2018.