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Current Fellows

2024 Fellows

Daw

Arka Daw, an Alvin M. Weinberg Fellow, earned his PhD from Virginia Tech. His dissertation focused on developing uncertainty quantification techniques for machine learning models, especially focusing on scientific applications such as solving partial differential equations, and lake modeling. His work led to the development of three different methodologies for improving uncertainty quantification techniques for the emerging field of scientific knowledge-guided machine learning (KGML), where the goal is to infuse scientific knowledge with deep learning models to improve its overall generalizability. His dissertation provided a way of explicitly enforcing physics priors such as monotonicity constraints in neural networks for meaningful uncertainty quantification; presented a more general framework for quantifying uncertainty with KGML for generic physics supervision; and studied the limitations of the commonly used physics-based loss formulation in the context of physics-informed neural networks (PINNs) and provides strategies to mitigate them. Arka’s mentors are Edmon Begoli, the founding director of the Center for AI Security Research (CAISER) under the Cyber Resilience and Intelligence Division, and Amir Sadovnik, CAISER’s research lead. 

Arka will focus his fellowship research on understanding the underlying causes behind adversarial vulnerabilities in deep learning models, and ultimately develop novel deep learning architectures and training methodologies that enhance their robustness, reliability, and trustworthiness. His project is expected to contribute significantly to the field by enhancing our understanding of the current limitations in artificial intelligence (AI) security and risk associated with state-of-the-art deep learning models. Building on this deeper understanding, the project aims to develop innovative deep learning frameworks and training methodologies to improve robustness, reliability, and trustworthiness, thus making these models suitable for deployment in critical infrastructures. Arka’s ongoing research interests include developing robust and trustworthy AI systems, specifically exploring their generalizability on out-of-distribution samples, enhancing their robustness against attacks like adversarial examples and data poisoning, and augmenting their reliability in terms of risk assessment. Arka also has a keen interest in tackling interdisciplinary problems in AI for science. 

Bhartendu Pandey

Bhartendu Pandey, an Alvin M. Weinberg Fellow, earned his PhD from Yale School of the Environment. His dissertation focused on measuring and forecasting urban inequalities, as well as assessing their human health impacts while also contemplating broader implications for global sustainable development. His dissertation research developed novel empirical approaches to study urban inequalities at scale, using detailed satellite remote sensing and census datasets. It further emphasized how infrastructure inequalities are intertwined with urbanization—and are a challenge to urban sustainability as well as global sustainable development—and highlighted the human health benefits and disbenefits of reducing some forms of urban infrastructure inequalities. Bhartendu’s mentor is Supriya Chinthavali, who leads the Critical Infrastructure Resilience group within the Geospatial Science and Human Security Division (GSHSD). Within GSHSD, he also receives mentorship from Dalton Lunga, GeoAI group leader. His cross-disciplinary mentoring panel, which also includes senior R&D staff member David McCollum (Buildings and Transportation Science Division), Plant–Soil Interactions group leader Colleen Iversen (Environmental Sciences Division), and Computational Earth Sciences group leader Forrest Hoffman (Computer Sciences and Engineering Division), offers Bhartendu a unique opportunity to engage with a diverse set of ideas and perspectives. 

Bhartendu will focus his fellowship research on advancing the science and decision-making capabilities towards equitable urban transitions under climate change, with a goal to transform our ability to advance human well-being, considering the unprecedented impacts of urbanization and climate change. His project is expected to deliver a novel understanding of generalizable aspects of spatial and social inequalities including boundary conditions, dimension-specific constraints, and future expectations, all of which are necessary to inform equitable urban transitions—and decision making surrounding these transitions—considering urbanization and climate change. Bhartendu’s ongoing research interests include urbanization and global environment change, remote sensing, geographic information, and complex systems sciences.

Rahman

Muhammad Mominur Rahman, an Alvin M. Weinberg Fellow, earned his PhD from Virginia Tech. His dissertation focused on characterizing the depth dependent structural and chemical processes in layered oxide cathodes for Na-ion and Li-ion batteries through utilizing synchrotron characterizations and formulating the design principles of stable layered oxide cathodes for these batteries. He worked to untangle the multiscale processes taking place in battery cathodes during operation and reveal the design principles of battery cathodes operating under extreme conditions such as in outer space and nuclear reactors. Mominur’s mentor is Ilias Belharouak, Electrification section head in the Electrification and Energy Infrastructure Division. 

Mominur’s fellowship will focus on materials development aided by advanced characterizations for beyond Li-ion batteries with a focus on sulfur cathodes and lithium-metal anodes. His research will tackle the fundamental issues facing these batteries such as polysulfide dissolution and lithium-metal anode reactivity, taking advantage of the state-of-the-art characterization facilities and battery manufacturing facilities available at ORNL. The project will contribute to the development of next-generation high-energy batteries utilizing cheap and abundant sulfur cathodes and high-energy lithium-metal anodes to secure the supply chain of battery manufacturing and ensure the widespread application of batteries in electric vehicles. Mominur’s ongoing research interests include electrochemistry and materials chemistry for electrochemical energy storage devices as well as advanced synchrotron characterization of battery materials. 

 

Yang

Daryl Yang, a Liane B. Russell Fellow, earned his PhD from Stony Brook University. His dissertation focused on the development and use of novel, multiscale remote-sensing technologies to understand the spatial and temporal complexity of high-latitude ecosystems and their response to climate change. Daryl’s research led to the design of novel remote-sensing platforms, including drones and time-lapse cameras with advanced sensing technologies (e.g., optical, hyperspectral, and thermal), to enable accurate and autonomous measurements of vegetation distribution, function, and seasonality from leaf-to-landscape scales and development of computational tools to scale them up to large airborne and satellite platforms. New, cross-scale understandings of the fundamental mechanisms and processes that drive vegetation dynamics and change in the Arctic and its high spatial and temporal variability across the landscape resulted from his work. Daryl’s mentor is Colleen Iversen, Plant–Soil Interactions group leader in the Environmental Sciences Division and principal investigator for DOE’s NGEE Arctic (Next Generation Ecosystem Experiment Arctic) project. 

Daryl’s fellowship research will focus on combining multiscale remote-sensing, fundamental ecology, and ecosystem models to understand fire-driven ecosystem transition and its impacts on soil–land–atmosphere  interactions across Arctic and boreal ecosystems. His work is expected to improve our ability to monitor and model fire-impacted ecosystems in the circumpolar Arctic. Daryl’s ongoing research interests include integrating novel Earth observations, fundamental ecological theories, and process models to advance our understanding of the interconnections between ecosystem dynamics and climate change. 

Fehmi Yasin

Fehmi Yasin, an Alvin M. Weinberg Fellow, earned his PhD from the University of Oregon. His dissertation focused on the development of a new kind of electron interferometer within a scanning transmission electron microscope (STEM) capable of quantitatively measuring the full specimen transmission function, amplitude and phase. His dissertation enabled the measurement of both amplitude and phase of electrostatic and magnetic materials, which is critical for characterizing materials and functional devices at atomic resolution. His work utilized inexpensive commercially available silicon nitride membranes as amplitude-dividing electron beam-splitters in order to decrease the coherence requirements of the electron source and enable interferometric imaging in any commercially available STEM. Fehmi’s mentor is Andrew Lupini, Scanning Transmission Electron Microscopy Group leader in the Center for Nanophase Materials Sciences.  

Fehmi's research will aim to expand ORNL’s world-class electron microscopy research to include magnetic imaging at temperatures ranging from room temperature down to liquid helium temperatures. He will focus on imaging the magnetic states in quantum materials that host emergent, topologically nontrivial real space spin textures (e.g., magnetic skyrmions), as well as their dynamics under external stimuli such as electric and heat currents. Fehmi’s ongoing research interests include using electron microscopy to help solve material science’s biggest mysteries as well as to identify new materials hosting properties that may help improve the human quality of life. Techniques he likes to explore include (S)TEM and electron interferometry technique development, in-situ electron microscopy imaging at cryogenic temperatures, transport measurements, focused ion beam fabrication of novel device geometries, and simulation techniques for both electron optical imaging and micromagnetics. 

2023 Fellows

Bertels

Luke Bertels, a Eugene P. Wigner Fellow, earned his PhD from University of California–Berkeley. His dissertation focused on theoretical chemistry with a specialization in molecular electronic structure theory. His work explored the role of zeroth-order representations for correlated wavefunction calculations. Luke’s mentor is Ryan Bennink, Quantum Computational Science group leader in the Computational Sciences and Engineering Division.

Luke will focus his fellowship research on the development of adaptive classical and quantum machine learning approaches for studying quantum chemistry. The work will provide new, efficient methods to extend the reach of both classical and quantum simulation towards the study of strongly correlated molecules. His ongoing research interests include quantum algorithms for physical simulation and electronic structure theory of molecules and materials.

Cushman

KC Cushman, a Liane B. Russell Fellow, earned her PhD from Brown University. Her dissertation explored the use of novel remote-sensing tools for measuring 3D structure and carbon dynamics in forests. KC's work demonstrated the value of drone technology for complementing traditional field- and satellite-based measurements of forests. Using drones for targeted, landscape-scale data collection allowed her to demonstrate that optical satellite data may underestimate tropical forest disturbance frequency and to explore how new estimates of forest biomass from spaceborne lidar (light detection and ranging) can be made robust to seasonal patterns of leaf production. KC’s mentor is Anthony Walker, Ecosystems Processes group leader in the Environmental Sciences Division. 

KC will leverage ground observations, near-surface remote-sensing data, and satellite platforms to develop innovative approaches to study ecosystems across spatial and temporal scales. Her work will explore the use of emerging SAR (synthetic aperture radar) data to study ecosystem structure. Results from this project will allow scientists to better monitor, understand, and predict the effects of disturbances on natural systems. KC’s research interests include studying variation in forest structure and function across space and time; understanding and predicting global cycles of carbon, water, and nutrients through forest science; and combining remote-sensing measurements and field-based observations to understand how organismal mechanisms affect landscape-scale processes. 

Zhao

Huan Zhao, a Eugene P. Wigner Fellow, earned his PhD from the University of Southern California. His dissertation focused on the fundamental properties and device applications of 2D layered materials. His work led to the invention of the world’s most energy-efficient resistive memory device and the discovery of a material with the largest broadband optical birefringence. Huan’s mentors are Scanning Tunneling Microscopy Group Leader An-Ping Li; Benjamin Lawrie, a research scientist in the Quantum Heterostructures Group; and Nanomaterials Characterization Section Head Stephen Jesse. 

Huan will focus his fellowship research on quantum state transduction and quantum sensing. This work aims to bridge the gap between innovative quantum materials and quantum information technologies. Huan’s fellowship will enable development of key elements essential for building a quantum network. His ongoing research interests include quantum technologies, which have the potential to revolutionize our methods of communication, computing, and sensing. 

2022 Fellows

photo of JungHyun Bae
JungHyun Bae, a Eugene P. Wigner Fellow, earned his PhD from Purdue University. His dissertation focused on development of a muon spectrometer using multilayer pressurized Cherenkov gas radiators for muon tomography applications. His work delivered a new concept for measuring muon momentum in the field, resulting in improving the utility of cosmic ray muons in their applications, which have emerged as a promising nonconventional radiation probe to monitor dense and large objects, (e.g., spent nuclear fuel casks, nuclear reactor core, and magma chamber underneath volcanos). JungHyun’s mentor is Rose Montgomery, Used Fuel and Nuclear Material Disposition group leader in the Nuclear Energy and Fuel Cycle Division.   JungHyun will focus his fellowship research on designing and building a prototype of the Cherenkov muon spectrometer and momentum integrated muon tomography system to advance utility of cosmic ray muons in many engineering applications. This approach will show highly efficient, safe, and high-resolution reconstructed images of spent nuclear fuel casks. His ongoing research interests include developing an advanced muon detector in the Underground Research Laboratory to monitor long-term nuclear wastes as well as a radiation detector, nuclear security, and nuclear material management.  
Distinguished Staff Fellow

Jeff Foster, an Alvin M. Weinberg Fellow, earned his PhD from Virginia Tech. His dissertation focused on developing a methodology to leverage gaseotransmitters, specifically hydrogen sulfide, for human therapy. His work showed that hydrogen sulfide exhibits selective anticancer activity and may represent a promising alternative cancer therapy. Jeff’s mentor is Tomonori Saito, a chemist in the Chemical Sciences Division.

Jeff will focus his fellowship research on developing homogeneous, stimuli-responsive catalysts for precision polymer synthesis. His methodology will enable kinetic control over polymer sequence, providing a tool to create polymers with intentionally designed sequences. Fundamental sequence–structure–property relationships discovered during Jeff’s fellowship work will provide a framework for the design of future sustainable materials for packaging, construction, energy storage, and medicine. His ongoing research interests leverage a framework of synthetic methodology, homogeneous catalysis, and organic material science to uncover structure–property relationships, create novel materials with emergent functionality, and develop efficient and sustainable manufacturing processes.

Portrait of Brenden Ortiz

Brenden Ortiz, a Eugene P. Wigner Fellow, earned his PhD from the Colorado School of Mines. His dissertation focused on accelerating the discovery and optimization of thermoelectric materials by developing techniques that aimed to accelerate both the theoretical and experimental aspects of material science. Brenden’s work resulted in the discovery of a new family of metals, AV3Sb5 (A: K, Rb, Cs) materials, which show a unique new quasi-2D kagome lattice and exhibit superconductivity, a charge density wave, and potential nontrivial topology. The combination of these properties together on the kagome lattice had never been seen before. His study renewed interest in the examination of kagome metals by researchers around the world, with over 350 additional manuscripts being published on this family in the past 2 years. Brenden’s mentors are Michael McGuire, Correlated Electron Materials group leader, and R&D staff member Andrew May, both in the Materials Science and Technology Division.

Brenden will focus his fellowship research on developing methods to control and predict the emergence of electronic instabilities in correlated metals. His project will facilitate the design of the next generation of quantum materials through a better understanding of the connection between the electronic structure of materials, the high-dimensional chemical space, and the emergence of correlated electron properties, such as superconductivity and charge density waves. Brenden’s ongoing research interests include the connection between chemistry and thermodynamics in complex materials. He is also interested in high-dimensional chemical spaces and how the influence over alloys, dopants, and defects can radically alter material properties.

Portrait of Yue Yuan

Yue Yuan, an Alvin M. Weinberg Fellow, earned her PhD from North Carolina State University. Her dissertation focused on the challenges existing in global management of carbon dioxide emissions and recent research on applying biocatalysts, as an alternative to high-energy and high-cost traditional liquid solvents in carbon dioxide scrubbing processes. Her work introduced a new category of material that has hierarchical structure and biocatalytic function. Her study also uncovered the mechanism of enhanced catalyzed reactions at liquid–gas–solid interfaces. Yue Yuan’s mentor is Dr. Rigoberto Advincula, Macromolecular Nanomaterials Group Leader at the Center for Nanophase Materials Sciences.

Yue Yuan will focus her fellowship research on renewable macromolecular nanomaterials, particularly how their charge and hydrophobicity impact their reassembly with additive manufacturing techniques, outside the biological system. Her ongoing research interests include working on advanced functional materials, particularly bioderived and bioinspired materials, and focusing on bridging fundamental bioscience discoveries with advanced materials manufacturing through revealing the mechanisms behind the phenomena we observed in material formation.

2021 Fellows

Logan Sturm 2021

Logan Sturm, an Alvin M. Weinberg Fellow, earned his PhD from Virginia Tech. His dissertation focused on cyber-physical security for additive manufacturing systems. Logan’s thesis provided a framework for identifying and mitigating sabotage attacks on additively manufactured parts using in situ monitoring, new techniques for securely transmitting part quality information to air-gapped side-channel monitoring systems, and an impedance-based method of nondestructively evaluating additively manufactured parts for defects. Logan’s mentor is Mason Rice, Resilient Complex Systems section head in the Cyber Resilience and Intelligence Division.

Logan will focus his fellowship research on identifying cybersecurity vulnerabilities in additive manufacturing systems and developing techniques and platforms to mitigate the vulnerabilities. His work will include evaluating in‑process monitoring systems for metal laser powder bed fusion in an adversarial setting, developing new methods for improving the robustness of these systems to attacks, and investigating human factors and training to improve awareness and understanding of cybersecurity threats in manufacturing. Logan’s project is expected to provide improved security for manufacturing systems and increased awareness of the threats facing modern digital manufacturing. Logan’s ongoing research interests include in situ monitoring for additive manufacturing systems, vulnerability assessment in advanced manufacturing, data analytics for malicious defect detection, secure distributed manufacturing, unclonable security features for anticounterfeiting, and human–machine interactions in a cybersecurity context.