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Los Alamos Distinguished Postdoc Fellows

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Meet the Lab's Current Distinguished Postdoctoral Fellows

Los Alamos National Laboratory Distinguished Fellows (pdf)

Lauren J. Beesley

Feynman Distinguished Postdoctoral Fellow
Analytics, Intelligence and Technology Division: Information Systems and Modeling, A-1
Computer, Computational and Statistical Sciences: Statistical Sciences, CCS-6


Education: PhD in Biostatistics – University of Michigan; B.S. in Mathematics – University of Kansas

Mentors: Sara Del Valle and David Osthus

Research: Lauren’s research addresses statistical challenges that arise during analysis of complex observational data, including handling of missing data, variable selection, measurement error, and selection bias. Lauren has collaborated with researchers across a variety of scientific domains, including oncologists and medical doctors, epidemiologists, human geneticists, computer scientists, biologists, and mathematicians. At LANL, Lauren’s research will focus on the common setting where researchers want to develop prediction models based on multiple different data streams (e.g., social media, satellite imagery, demographics, etc.). Data quality can vary substantially between different data sources, and issues such as missing data, measurement error, and massive data size all pose unique and consequential challenges. Lauren’s research will work to address some of these challenges, with the ultimate goal of giving better model predictions. Lauren’s work will center on two key applications, including forecasting of political instability across various spatial resolutions and addressing problems with data quality and backfill in prediction modeling of influenza outbreaks.

Bio: Lauren received her PhD in Biostatistics under the mentorship of Dr. Jeremy M G Taylor. Her dissertation research focused on handling of missing data for complicated event time outcomes, with a particular emphasis on risk prediction for survival and recurrence outcomes for patients diagnosed with cancer. After her PhD, Lauren worked with Dr. Bhramar Mukherjee as a Postdoctoral Research Fellow at The University of Michigan, where she developed statistical strategies for reducing bias due to selection and measurement error in health research using electronic health record data. In her free time, Lauren enjoys cooking/baking and crafting.

Joshua Burby

Feynman Distinguished Postdoctoral Fellow
Theoretical Division: Applied Mathematics and Plasma Physics (T-5)

Joshua Burby

Education: PhD in Plasma Physics – Princeton University; B.S. in Engineering Physics – Cornell University

Mentors: Xianzhu Tang and Luis Chacon

Research: Josh's research aims to efficiently model the intricate multiscale properties of plasmas using tools from dynamical systems theory and differential geometry. He focuses on developing broadly-applicable analytic and computational techniques for coping with the time- and space-scale separation associated with stiff plasma dynamics. Through his research, Josh recognized that phase-space-geometric objects known as slow manifolds appear and play a foundational role in a variety of reduced models for multiscale plasma behavior. Notably, he used this observation to explain how those models inherit Hamiltonian structure from more-complete descriptions of the plasma state. As he continues to explore the ramifications of slow manifolds in plasma physics, Josh is developing "slow manifold integrators" at LANL. These are simulation algorithms that use a system's slow manifold to solve the preconditioning problem inherent to implicit simulations of temporally-stiff systems.

Bio: Josh earned his PHD under the mentorship of Professor Hong Qin at the Princeton Plasma Physics Laboratory. Being more of a mathematical physicist than a traditional theoretical physicist, Josh spent his first postdoc at the Courant Institute of Mathematical Sciences as a DOE Fusion Energy Sciences (FES) Fellow. After leaving Courant and before coming to LANL, he joined the Mathematical Sciences Research Institute (MSRI) as a Viterbi Fellow during the program "Hamiltonian systems, from topology to applications through analysis."

Conrad Goodwin

Oppenheimer Distinguished Postdoc Fellow
Chemistry Division: Inorganic, Isotope, and Actinide Chemistry (C-IIAC)


Education: Ph.D. and M.S. in Chemistry – University of Manchester

Mentor: Andrew Gaunt

Research: Conrad works in the area of f-element chemistry, focusing on electronic structure, new oxidation states, and oxidation state/structure/bonding interrelations. Specifically, he is interested in exploring structure/oxidation state relationships in metal-ligand covalency, and how these factors perturb f-element properties such as magnetic response and optical phenomena. The discovery of new oxidation states throughout the f-block in recent years has opened up a new and unexplored regime where our fundamental knowledge is almost completely absent; the nature of the metal-ligand interaction, and electronic structures are not fully understood yet. Tied into this is the concept of covalency, which describes ligand-bonding throughout the periodic table, however our current knowledge of f–element and in particular trans-uranic covalency is sparse. The elucidation of this information along with how oxidation state affects these properties is a fundamental synthetic, computational and experimental challenge, and will greatly add to our understanding of these technologically relevant elements.

Bio: Conrad Goodwin received his Ph.D. under Dr. David Mills. His thesis focused on the use of novel bis(silylamide) ligands, {N(SiR3)2} for the synthesis of extremely low coordination number f-block complexes, and the study of the electronic structures of these complexes. A major sub-theme of his work to date has been on the synthesis of designer f-block Single Molecule Magnets (SMMs), single molecules that can act as tiny bar magnets. The culmination of this work was the synthesis of a Dy(III) complex that functions as a magnet at 60 K, a world record and the closest yet to functioning at liquid nitrogen temperature (77 K). In 2018 he received the Dalton Emerging Researcher award from the RSC, as well as a School of Chemistry Outstanding Achievement Award from the University of Manchester.

Christopher Johnson

Feynman Distinguished Postdoc Fellow
Earth and Environmental Sciences Division: Geophysics (EES-17)
and Science Program Office/Applied Energy Program (SPO-AE)  


Education: Ph.D. and M.S. in Earth, Atmospheric and Ocean Sciences - University of California Berkeley
B.S. in Geophysics - Georgia Tech

Mentors: Paul Johnson, George Guthrie and Andrew Delorey

Research: Chris studies the crustal response of earthquake activity from transient forces to decompose the mechanical processes of active faulting. Earthquake triggering is the occurrence of an event during a quantifiable stress transient. Studying these events advances our knowledge of what makes earthquakes nucleate. His research uses seismic measurements to detect earthquakes and non-tectonic sources of ground motion. He incorporates geodetic measurements, or how the surface of Earth deforms, to characterize stress perturbations that promote earthquake activity. The enhancement of earthquake catalogs and detecting new observations of weak ground motions using dense seismic arrays is his latest research focus. Applying data driven machine learning techniques is allowing more information to be extracted from seismic waveforms that can be analyzed in conjunction with existing geodetic networks. Current research at Los Alamos National Laboratory is to utilize machine learning algorithms for seismic noise analysis to characterize signals related to earthquake nucleation. Analyzing these observations with new techniques that enhance the resolution of the observations will advance our understanding of what makes an earthquake start rupturing.

Bio: Chris completed his Ph.D. with a NSF graduate research fellowship at the Berkeley Seismological Laboratory at UC Berkeley. His dissertation work was advised by Roland Bürgmann with a focus on transient stress changes in the crust and the dynamics of earthquake triggering. He was awarded a NSF postdoctoral fellowship and spent 2.5 years at UC San Diego and Uni. of Southern California utilizing machine learning techniques to identity weak signals in dense seismic array data to enhance earthquake detection. Prior to entering a 4 year university as a non-traditional student, Chris worked as a diesel technician on heavy duty trucks before attending community college and transferring to Georgia Tech to study Geophysics. During his undergraduate studies he was involved in research exploring the dynamics of crustal strain that led to pursuing a graduate degree.

Arshan Nasir

Oppenheimer Distinguished Postdoc Fellow
Theoretical Division: Theoretical Biology & Biophysics (T-6)

 arshan nasir

Education: Ph.D in Informatics and M.S. in Bioinformatics -University of Illinois at Urbana-Champaign; B.S. in Bioinformatics – COMSATS University

Mentors: Thomas Leitner and Ethan Romero-Severson

Research: Arshan has developed and utilized protein structure-based phylogenomic methods to advance research on viral origins and evolution. His research has shown that viruses originated multiple times in evolution from ancient cells that once co-existed with the ancestors of modern organisms, Archaea, Bacteria, and Eukarya. He has also shown that virus-to-cell gene transfer may transcend known host boundaries and the concept of virus host is rather ill-defined. In addition, he has associated the presence and absence of viral lineages in host organisms to major evolutionary transitions that shaped the diversification of life. His research is highly collaborative in nature with teams in USA, France, and Korea, and has been featured in popular science magazines and websites such as BBC Earth, Popular Science, Scientific American, among many others. Recently, he completed editing a special issue on ‘Viruses, genetic exchange, and the tree of life’ on the invitation of Frontiers in Microbiology (https://www.frontiersin.org/research-topics/7867/viruses-genetic-exchange-and-the-tree-of-life) alongside Professors Gustavo Caetano-Anollés (University of Illinois at Urbana-Champaign) and Jean-Michel Claverie (Aix-Marseille Université, France). He also co-led the development of HGTree, a novel database to detect horizontally transferred genes in prokaryotes in collaboration with Seoul National University in Korea. The database is available online (http://hgtree.snu.ac.kr/) and has been frequently used by microbiologists worldwide to monitor the spread of genes within bacteria. At LANL, he will be focusing on studying HIV evolution and spread in human populations and developing resources to combat its threat along with advancing his earlier work on reconstructing the deep evolutionary history of organisms and viruses.

Bio: During his undergraduate education, he developed a strong interest in utilizing computational approaches to solve biological problems. He completed an undergraduate thesis studying the possible transmission routes of mouse mammary tumor virus into human populations. This increased his research interest and enthusiasm in studying and combating viruses and he continued with virus evolution research during his MS and PhD education and training under the guidance of Prof. Gustavo Caetano-Anollés. At Illinois, he was part of an international evolutionary genomics collaborative between USA, France, and Korea to study virus origins and evolution using a novel approach based on protein structures. After the completion of his PhD, he returned to his home country of Pakistan and served at the COMSATS University in Islamabad.

Johanna Palmstrom

Reines Distinguished Postdoc Fellow
Materials Physics & Applications Division: National High Magnetic Field Laboratory (MPA-MAGLAB)


Education: Ph.D. and M.S. in Applied Physics – Stanford University
B.S. in Physics – University of California Santa Barbara

Mentors: Ross McDonald

Research: Johanna’s research is focused on understanding unconventional superconductivity and the phase diagrams in which this exotic phase occurs. Her research leverages the relationship in solids between the electronic symmetries of a material and the symmetry of the underlying crystal lattice by using strain as a powerful tool to both probe and tune emergent phenomena and phase transitions. In her graduate work, Johanna investigated the large electronic nematic instability found in one family of unconventional superconductor, the Fe-based superconductors, via measurements of the elastoresistivity (the induced resistivity response to strain). At LANL she brings symmetry resolved measurements and strain to the extreme environment of pulsed magnetic fields to study broken symmetry phases and symmetry breaking fluctuations in strongly correlated electron systems.

Bio: Johanna’s interest in science and research began at a young age when her father, a materials scientist, took her into lab for a “Bring Your Child to Work Day.” She assisted with a thin-film single crystal growth and assembling toy model crystal structures. She was a Regents Scholar at the University of California, Santa Barbara where she pursued a B. S. degree in the College of Creative Studies Physics program. She was actively involved in research throughout her undergraduate studies where she worked with Prof. James Allen and Prof. Omar Saleh and was awarded the Arnold Nordsieck Award as a graduating senior for her promise in scientific research. She completed her Ph. D. at Stanford University under the advisement of Prof. Ian Fisher. For her dissertation research she investigated the role of electronically driven rotational symmetry breaking in iron-based superconductors. During her graduate studies she was honored to receive the G. J. Lieberman Fellowship, the Gabilan Stanford Graduate Fellowship, the National Science Foundation Graduate Research Fellowship, and to attend the 66th Lindau Nobel Laureate Meeting. Johanna joined Los Alamos National Laboratory as a Frederick Reines Postdoctoral Fellow in 2020.

Loreen Stromberg

Reines Distinguished Postdoc Fellow
Chemistry Division: Physical Chemistry and Applied Spectroscopy (C-PCS) and Inorganic, Isotope, and Actinide Chemistry (C-IIAC)

Loreen Stromberg

Education: Ph.D. in Biomedical Engineering – University of New Mexico; B.S. in Biochemistry – University of New Mexico

Mentors: Harshini Mukundan and Stosh Kozimor

Research: Loreen is interested in studying methods for simulating and creating complex biomimetic membranes to observe the interactions of pathogenic biomarkers at the cell surface. Her work currently focuses on developing precision patterned membranes and studying how different lipid and protein membrane compositions and architectures affect the interactions of amphiphiles such as lipopolysaccharide, lipoarabinomannan, and mycolactone with said membranes. Understanding these interactions is critical as it adds to the global knowledge base for mechanisms of innate immune recognition and vaccine technology which furthers our abilities to detect and fight infectious diseases.

Bio: Loreen’s research has always fundamentally focused on developing biomedical solutions to address human health and disease. Her undergraduate research with Dr. Pavan Muttil (University of New Mexico) worked to develop assays to evaluate the toxicity of novel drug carriers for cancer treatment. Under the supervision of Drs. Harshini Mukundan, Gabriel Montaño (Los Alamos National Laboratory), and Steven Graves (University of New Mexico) she began studying membrane interactions during her doctoral studies as a means to develop and improve detection methods for pathogenic E. coli. As a postdoc in mechanical engineering at Iowa State University, she worked with professors Jonathan Claussen and Carmen Gomes as well as Jeroen De Buck (University of Calgary) to develop an array of rapid, disposable diagnostics for various targets such as cancer, Salmonella, E. coli, and immunoglobulins. Their work ultimately led to the founding of the startup biotech company, NanoSpy, Inc., that Loreen co-founded and served as the CEO until returning to Los Alamos National Laboratory as a Postdoctoral Research Associate.