PhD Research Rotation
First year Department of Physics PhD students may use this form to select their research rotation preferences.
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Research Rotations
| Faculty Name | Type | Research Area | Research Title | Research/Project Short Description |
|---|---|---|---|---|
| Steve Pressé | Theoretical | Biological and Soft Matter Physics, Nanoscience and Materials Physics | Statistical mechanics meets AI/ML | We live in an age where data abound and there is an explosion of new tools (AI/ML) inspiring us to think quantitatively about these data. Yet these tools, often inspired by developments in Mathematics and CS, are often black boxes and not suitable for applications within the Natural Sciences. Our goal is to advance computational tool, appropriate for the Natural Sciences, critical in gathering insights on life's processes observed through advanced microscopy techniques or astronomical events observed using modern telescopes. In particular, we develop tools of AI and machine learning, many grounded in computational statistics, to glean insights about our physical universe otherwise unavailable using traditional analysis techniques. For example, of particular interest, is unraveling the collective dynamics of molecular machines (i.e., transcription factors) operating cohesively at gene loci to read DNA's instructions. Unraveling these dynamics is especially complex as most events of interest occur on length scales far smaller than the light we use to observe them. Thus from a smattering of photons in space, of wavelength hundreds of times larger than the objects we care to characterize, must be derived insight on life's fundamental processes. Students working on this project will quickly become experts in state-of-the-art tools of AI and machine learning. |
| Wenwei Zheng | Theoretical | Biological and Soft Matter Physics | Elucidating the mechanism of interactions involving intrinsically disordered proteins | Intrinsically disordered proteins (IDPs), characterized by the absence of a well-defined folded structure, assume pivotal roles in diverse intracellular activities. Their functional significance often arises from a disorder-to-order transition during interactions with other biomolecules. However, there is a growing body of evidence emphasizing the indispensable contribution of conformational flexibility and dynamics in the regulation of biological activities. Resolving this structural complexity solely through experimental techniques is challenging, given the diverse conformations explored within the limited experimental time resolution. We aim at developing computational methods tailored to unravel the roles of structural flexibility when IDPs interact with a broad spectrum of biomolecules. This project is supported by an NIH R35 grant. |
| Wenwei Zheng | Theoretical | Biological and Soft Matter Physics | Advancing biodegradation of emerging contaminants | An increasing amount of synthetic chemicals released into the environment deteriorate the water quality. Bacteria living in nature deploy enzymes capable of breaking down certain pollutants and utilizing them as carbon sources. However, the inherent pace of the natural biodegradation process often proves insufficient in eliminating these contaminants. This project aims to enhance the efficiency of bacterial enzymes by systematically modifying and optimizing them using a combination of experimental and computational methods, thereby accelerating their degradation rates. Our approach involves harnessing collaborative experimental findings to inform the development of a computational model. This model will simulate the intricate interactions between these engineered enzymes and the targeted contaminants. Through this synergy of experimentation and computation, we aim to unravel the underlying physical mechanisms governing the enzyme-contaminant interplay, identifying key parameters for optimizing enzyme activities. The development of this integrative framework is supported by an NSF collaborative grant. |
| William Terrano | Experimental | Cosmology, Particle, and Astrophysics | Quantum control with nuclear spins. | We are developing new techniques to more precisely control the quantum state of nuclear spins. These developments can be used in sensors of beyond the standard model physics, and quantum sensors of magnetic fields and rotations. |
| Xihong Peng | Theoretical | Nanoscience and Materials Physics | Quantum mechanical computations of material properties | Prof. Peng’s group performs first-principles electronic structure calculations to explore novel materials and seek their application in nanoelectronics and renewable energies, as well as to gain a fundamental understanding of the materials’ properties at the atomic level. Her key research interests are first-principle calculations of mechanical, electronic properties of group IV, III-V, II-VI nanostructures including one- and two-dimension for potential application in nanoelectronic devices, and investigation of novel materials for photocatalysts and high capacity Li-ion battery electrodes. Dr. Peng has close collaboration with experimental groups and students will have an opportunity to work or closely interaction with researchers in experimental labs. Funding for hiring students as summer research assistant is possible. |
| Xihong Peng | Theoretical | Nanoscience and Materials Physics | Clathrates as Anodes for Li-ion Batteries | Types I and II Si/Ge clathrate materials recently have been studied for their electrochemical properties as potential anodes for lithium-ion batteries due to their unique cage structures and ability to incorporate extrinsic guest atoms. This project is to investigate the electrochemical and structural properties of clathrates through a concerted theoretical and experimental approach to understand the electrochemically obtained structures. Prof. Xihong Peng’s group performs First-principles density functional theory (DFT) calculations and Prof. Candace Chan’s lab synthetizes and characterizes the electrochemical properties of the materials. Students participated in this project will have an opportunity to work and closely interaction with researchers in both theoretical and experimental labs. This project is funded by NSF. Funding for hiring students as research assistant is possible. |