"2D hybrid organic-inorganic metal halide perovskites" are a recently discovered class of semiconductors being studied in the hopes of developing highly efficient, low-cost, stable solar cells. Metal and halogen (group VII) atoms bind together in 2D layers, which are then stacked together via organic linker molecules. We are studying these interesting and important materials through optical absorption, electric field-modulated absorption, photoluminescence (fluorescence), time-dependent photoluminescence on nanosecond time scales, and dielectric spectroscopies. This allows us to determine important properties of the electrons inside these materials, to make better photovoltaic materials.

We're working with a mechanical engineering professor (Troy Munro) to use semiconductor nanoparticles as temperature sensors. The wavelengths of light present in the nanoparticles' photoluminescence (aka fluorescence), and the time it takes for the luminescence to be emitted after the electrons have been excited both depend on the temperature. By characterizing the nanoparticles’ photoluminescence spectrum in both wavelength and time as a function of temperature, we hope to be able to use the nanoparticles as non-invasive temperature sensors in e.g. medical applications. For example, one could use the optical emission from nanoparticles injected into tissue to monitor temperatures as focused ultrasound is used to heat up and destroy tumors.

We develop and apply AI methods to the design of proteins.

We develop data science tools to understand the link between dietary intakes and health outcomes.

We train AI models for applications in the medical field, particular emphasis on automatic prostate cancer diagnosis.

One of the first steps toward understanding any given material of interest (a new superconductor, an unusual magnetic material, an energy-related compound, etc) is determining its atomic and magnetic structure. We utilize beams of x-rays, neutrons, and muons at large-scale accelerator facilities to do just that. Our primary experimental techniques include atomic and magnetic pair distribution function (PDF) analysis, conventional x-ray and neutron scattering, and muon spin relaxation/rotation. A few times a year, we visit these types of facilities to collect data, and then we come back home to analyze and make sense of it all. Through this process, we hope to shed light on the origin of the material's properties by gaining a detailed understanding of the local and average atomic and magnetic structure. If you are interested, please reach out and we can discuss if a spot is available!

Data are only useful if we can understand them, and to understand them, we often need specialized tools. We are currently developing open source, python-based software tools to analyze experimental data collected from condensed matter experiments using x-ray, neutron, and muon beams. The software will maximize research effectiveness and enable new methods of analysis not only for our own research group, but also for the wider community of condensed matter physicists using similar types of experimental methods. If you are interested, please reach out and we can discuss if a spot is available! 

Molten salt reactors (MSRs) are a promising nuclear reactor design concept in which molten ionic salts function as the coolant and/or fuel source in the reactor. MSRs have many potential advantages over standard designs in commercial use today, including greatly enhanced safety/security and the ability to produce critical medical radioisotopes in addition to vast amounts of carbon-free electricity. To make MSRs a reality, it is necessary to understand and predict the behavior of the salts in operating conditions. Gaining a detailed knowledge of the local structure of the molten salts on the atomic scale is an essential step in this direction, since the local interactions between constituent atoms determine the macroscopic properties. In this project, we use cutting-edge neutron and x-ray total scattering and computational modeling techniques to establish the structure of relevant molten salts. If you are interested, please reach out and we can discuss if a spot is available! 

We are developing AI to identify nanostructures inside of bacteria. In collaboration with Grant Jensen's lab (who has about 40,000 images taken over 20 years) we are working to understand basic life processes. Our focus includes some "standard" computer vision methods as well as new methods based on neural networks, transformers, etc. We also collaborate with Bryan Morse's lab in CS.

Large arrays of hydrophones in the ocean can be used to locate acoustic sources.  The reliability of these localization algorithms depends on the degree to which the ocean environment is correctly parameterized in the models.  

The computational models for sound propagation in the ocean depend on the ocean environment.  My work involves using sound from the ocean to estimate the ocean environment.  One part of the research works on determining the sensitivity of different seafloor parameters and determining which seafloors make a big enough difference on the sound propagation to be detected.  The other part explores optimizations and how machine learning can be used to identify seafloor properties from different types of sounds.

I am currently looking for two students to join my computational underwater acoustics research.  Research in this area will provide a strong foundation in computational skills, numerical modeling, and deep learning, all of which will prepare students for additional opportunities in industry, national laboratories, and graduate school.

Our underwater acoustics lab (U117) has a fully automated system for making acoustic measurements in our water tank (12 ft long by 4 ft wide).  Currently measurements are being made test which numerical models accurately predict sound propagation in the tank at ultrasonic frequencies.  The big upcoming goal is to be able to test machine learning algorithms for source localization and environmental variability using ultrasonic tank measurements.

I am currently looking for two students to join my underwater acoustical measurement group.  The opportunity to do experiments in a water tank at ultrasonic frequencies offers a solid foundation for students interested in studying ultrasound or other medical physics fields in graduate school.  In addition, the experience with measurement protocols, programming the robotic arms, and analyzing the data with signal processing techniques provide a good foundation for many technical jobs.

Like our Sun, other stars are known to host planetary systems. As we continued to discover many more exoplanetary systems, we learn about how these systems are put together. The "architecture" of these systems (are small planets on the inside or outside? how close are the planets to each other? etc.) gives us invaluable clues to the formation of planetary systems. I used state-of-the-art statistical and computational techniques to discover new exoplanetary systems, study existing systems, and remove the biases on their properties from our limited observational methods. There are a variety of projects available at a variety of levels and you'll be paid as Research Assistants. Please contact me for more information. The best time to contact me about available positions is about 1 month before the beginning of a semester. 

(No positions open until Fall 2023.) Beyond the orbit of Neptune lies a population of icy bodies whose orbits can reveal unique information about how our solar system formed. This region of the solar system is called the Kuiper Belt and these small icy bodies are called Kuiper Belt Objects (KBOs or sometimes Trans-Neptunian Objects or TNOs), though some are large enough to also qualify as "dwarf planets" like Pluto and Haumea. There are multiple projects available in my research group to study KBO satellites (e.g., Haumea's moons) and KBO orbits (e.g., the Haumea and other collisional families). There are a variety of projects available at a variety of levels and you'll be paid as Research Assistants. Please contact me for more information. The best time to contact me about available positions is about 1 month before the beginning of a semester.