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Current Fellows

2019 Fellows

Friederike Bock, a Eugene P. Wigner Fellow, earned her PhD through a joint program of Lawrence Berkeley National Laboratory and the University of Heidelberg. Her dissertation focused on heavy ion physics and establishing the point at which the quark-gluon plasma can be seen during heavy nucleus collisions. Friederike’s work established new techniques aimed at reducing uncertainty in collision systems with variable thermal signal strengths. Her project represented the first effort to look at direct photons in proton–proton and proton–lead collisions at the Large Hadron Collider at CERN, the European Organization for Nuclear Research, in Switzerland. Friederike’s mentor is Tom Cormier, a group leader in the Physics Division.

Friederike’s fellowship research in the Heavy Ion Reactions Group will focus on producing very precise measurements of the photon signal in heavy ion and intermediate collision systems and on building a new detector that she hopes will unveil a new state of matter, gluonic matter, in currently uncharted phase space areas. Her ongoing research interests also include understanding photons from a more phenomenological perspective, thus bridging the gap to theoretical calculations.

Victor Fung, a Eugene P. Wigner Fellow, earned his PhD from the University of California–Riverside. His dissertation focused on using computational chemistry techniques to identify the best methods for converting alkanes such as methane and propane into useful industrial feedstocks. His work revealed the catalytic active sites and mechanisms for breaking alkane chemical bonds to deliver the most energy-efficient conversions. Victor’s mentor is Bobby Sumpter, a group leader in the Center for Nanophase Materials Sciences (CNMS).

Victor is based at CNMS’s Nanomaterials Theory Institute. His fellowship research involves developing high-throughput screening techniques that will provide valuable chemical predictions for nanomaterials at a level of accuracy not yet accomplished in current materials databases. Victor will also explore potential chemical/catalytic applications of quantum materials using ORNL-developed Quantum Monte Carlo techniques and ORNL’s Summit supercomputer. His research interests lie at the intersection of probing physical and chemical phenomena such as chemical bonding and developing computational tools that guide scientists to the most promising materials for physical study.

Gang Seob “GS” Jung, a Eugene P. Wigner Fellow, earned his PhD from the Massachusetts Institute of Technology. His dissertation focused on developing multiscale models to understand fracture and synthesis processes of 2D materials such as graphene, tungsten disulfide, and molybdenum disulfide. He examined computationally how these materials behave when such 2D crystals structurally fail or form grain boundaries at the atomic level, to understand fundamental mechanisms and continuum-scale properties. GS’ models have effectively explained and predicted 2D material behaviors observed in experiments. His mentor is Stephan Irle, a computational soft matter scientist in the Computational Sciences and Engineering Division.

In the Computational Chemical and Materials Sciences Group, led by Bobby Sumpter, GS develops integrated multiscale models that enable predictive design and simulation of materials of interest at ORNL. He explores atomic-, mesoscale-, and continuum-scale characteristics of materials to understand how multiscale properties and behaviors define performance. GS’ research interests include building a virtual lab where materials can be synthesized and characterized by combining and bridging advanced computational methods at different scales using ORNL’s world-leading high-performance computing resources.

Jason Nattress, an Alvin M. Weinberg Fellow, earned his PhD from the University of Michigan. His doctoral research, which examined how spectroscopic neutron and photon radiography and delayed neutron signatures could be combined to accurately identify special nuclear material, provided a process map by which an individual could determine whether an unknown material is benign or a nuclear weapon. Jason’s work represented the first instance in which a low-energy, nuclear reaction–based active interrogation source was used to perform dual-mode, multiple-energy transmission radiography. He demonstrated that using neutron and photon transmission radiography in combination achieves higher sensitivity to changes in elemental composition across the periodic table compared to using the two methods individually. Jason’s  mentor is Paul Hausladen, a Distinguished Staff Scientist in the Isotope and Fuel Cycle Technology Division.

Working in the Radiation Detection and Imaging Group, Jason is developing a combined fast-neutron/gamma-ray radiography system that can distinguish between high‑Z materials and produce 3D tomographic images. His project is expected to provide useful new material identification/inspection techniques to improve scanning times for ocean-going cargo containers. Jason’s research interests include detection techniques for nuclear security and nonproliferation, specifically detection of nuclear materials in transit, development of novel neutron detectors, and neutron and photon spectroscopy.

Joe Paddison, a Eugene P. Wigner Fellow, earned his PhD from the University of Oxford. His dissertation involved using computational modeling techniques to predict 3D scattering data from powder data when crystals of materials under study cannot be derived. Joe’s work showed that unexpected amounts and types of information can be obtained from neutron scattering measurements. His mentor is Andy Christianson, a neutron scattering scientist in the Materials Science and Technology Division.

Joe’s work in the Scattering and Thermophysics Group will focus on using neutron scattering techniques to develop a deeper understanding of the behavior of magnetic materials such as quantum-spin liquids. He aims to explore materials for which the effects of quantum mechanics and crystalline geometry coincide to create new states of matter featuring entangled magnetic states. Joe’s research interests lie at the intersection of neutron scattering, materials’ structure and characteristics, and models of materials’ behavior.

2018 Fellows

Stephanie Galanie, a Liane B. Russell Fellow, received her PhD from Stanford University. Her dissertation focused on synthetic biochemical production of medicinal natural products in yeast. Working in a research team, she combined enzyme discovery, enzyme engineering, and pathway and strain optimization to achieve biosynthesis of opiates, semisynthetic opioids, and other benzylisoquinoline alkaloids in yeast. Prior to her fellowship, she was a scientist at Codexis, a protein engineering biotechnology company. Her mentor is Tim Tschaplinksi, who leads ORNL’s Metabolomics and Bioconversion Group.

Stephanie’s fellowship research in the Biosciences Division facilitates enzyme and pathway discovery in the Populus (poplar tree) genus to increase drought tolerance and productivity, reduce recalcitrance, and manipulate metabolic profiles. By applying high-throughput heterologous microbial expression and mass spectrometry techniques to probe metabolism and help answer systems biology questions, her research will improve our understanding of and increase our ability to enhance sustainability, robustness, and energy utility of organisms and ecosystems. Stephanie’s research interests include biosynthesis, biocatalysis, and natural products.

Omar Demerdash, a Liane B. Russell Fellow, received his PhD and MD from the University of Wisconsin–Madison. His dissertation addressed computational modeling of protein function within a single protein and among groups of proteins. Omar developed machine learning–based models for predicting the amino acids that mediate protein functional modulation, models for predicting whether proteins will bind to each other, and a coarse-graining technique that simplifies calculation of vibrational motions of solid materials including proteins and other biomacromolecules. During medical school, Omar conducted studies aimed at improving spinal cord injury treatments and doctors’ interpretations of histological and cytological samples. His mentor is Julie Mitchell, Biosciences Division director.

Omar’s fellowship research in the Biosciences Division focuses on generating improved machine learning–based computational methods that will help scientists predict which drugs are most promising for study as targeted protein modulators to bring about improved predictive methods for any human disease, including cancer. Omar’s additional research interests include improving potential energy models for biomolecules; computational prediction of biomolecular structure and function using methods that integrate first-principles physics and machine learning; and integration of biophysical techniques, machine learning, and bioinformatics to predict organismal phenotype.

2017 Fellows

Christa Brelsford, a Liane B. Russell Fellow, earned her PhD at Arizona State University. Her dissertation focused on urban water consumption. She examined the effects of population growth, infrastructure change, and conservation policy on residential water demand in Las Vegas, Nevada. Christa’s research marked the first-ever comprehensive analysis of the water-conserving effects of one of the most widely used water conservation programs in the western United States. She also implemented a new empirical method to explore counterfactual scenarios in a microeconometric context. Christa’s mentor is Budhu Bhaduri, National Security Emerging Technologies Division director.

Christa is conducting her fellowship research in the National Security Emerging Technology Division. Her research aims to develop empirical and theoretical tools to increase our understanding of urban systems, how they interact with and are influenced by the broader physical environment, and how collective social processes co-evolve with urban form. Christa’s research interests include using empirical methods, especially spatial analysis and remote sensing, to link individual choices to aggregate outcomes to build better theories about how cities and urban water systems function.