Connor Geudeker
Laboratory seismology uses a scale-model approach to complement the wealth of research on in situ earthquakes that cannot be observed directly. A simple mechanical system applies shear stress to two blocks with a roughened interface, such that it produces stick-slip behavior with energy signatures matching in situ earthquakes. Lab scale seismic sensors allow us to apply typical seismological analyses. Additional instruments provide measurements not available in the field, which are used to expand our understanding of the underlying processes as well as the results and limits of the seismological methods.
Yuniba Yagues
The ability to measure vibrations is a vital engineering problem. From measuring pulse for health diagnostics to sensing pressure on a touch screen for a smart phone, the applications vary far and wide. In our group we study the use of polymer-based devices called piezoelectrets to measure pressure signals for a variety of applications. Our microfabricated polymer approach yields superior flexibility, piezoelectric coefficients, and costeffectiveness when compared to traditional ceramic material competitors. The devices themselves also vary in material composition and geometry depending on the application. In this project we […]
Vivian Li
The firing properties of a neuron are not only influenced by the electrical and chemical signals it receives, but also by the physical properties of its environment. Their ability to detect stimuli such as pH, temperature, and mechanical pressure allows a neuron to change its excitability in response. Two-pore domain potassium (K2P) ion channels are of particular importance because they are crucial in hyperpolarizing and modulating the resting membrane potential. Deviations from normal resting membrane potentials lead to unexpected consequences, including mental illness.The purpose of this research project is to […]
Soumil Jain
What makes a smart building smart? Does a smart building or space trigger behavioural changes in users and their interactions with the space? Transformation in health and medicine calls for innovation and integration of information science and engineering approaches to revolutionize healthcare delivery systems, including high-performance wireless communication and sensing technologies. This study is part of an NSF-funded project and will focus on developing event-based behavioural models to simulate building-user interactions in hospital settings, to predict human behaviour in a hospital and optimize design.
Siyang Li
Fast Radio Bursts (FRB) are high-energy millisecond duration radio signals of unknown astrophysical origins whose localizations are limited by the inherently low resolutions of radio telescopes. Recent theories propose that the origins of FRB may also produce nanosecond duration optical counterparts which, if observed with higher resolution optical telescopes, would allow astronomers to localize and identify the origins of FRB. Due to their extragalactic distances, optical counterparts to FRB can also be used to learn more about the fundamental properties and evolution of the Universe through probing the missing Baryonic […]
Nicole Mizrahi
The Cretaceous-Paleogene (K-Pg) mass extinction (~66 million years ago) is hypothesized to have been caused by environmental effects of the Chicxulub asteroid impact and/or Deccan Traps flood volcanism in India. Both potentially caused major climatic change through increased sulfate aerosol production, which would have caused significant global cooling and/or acid rain. Sulfur released by each of these events has a distinguishable isotopic composition. To characterize changes to the sulfur cycle across the K-Pg boundary and investigate the role each catastrophic event played in the extinction, I will measure sulfur abundance […]
Hunter Martin
One of the principal probes of cosmology is weak gravitational lensing whereby gravitational effects of mass bend the path of light. This causes small but correlated distortions in the images of distant galaxies which we can measure and then use to study the distribution of matter over cosmological distances and time scales. However, one of the fundamental assumptions of this method is that galaxy shapes (which we can model as ellipses) are randomly oriented in the universe, and that these distortions serve to align them. But what happens when the […]
Joshua Lin
Over the summer, we propose to investigate the root multiplicities of (generalized) Kac-Moody Algebras. Our plan is to create an open-source computer package that allows for the computation of root multiplicities of Kac-Moody algebras, building upon the existing tools available to computational mathematicians, for instance, the popular library sage-math. Once we have developed and verified this package against known tables of root multiplicities, we aim to start investigating the root multiplicities of simple graphs, and attempt to address some outstanding conjectures on the distributions of root multiplicities. A greater understanding […]
Chris Randall
Over the summer, we propose to investigate the root multiplicities of (generalized) Kac-Moody Algebras. Our plan is to create an open-source computer package that allows for the computation of root multiplicities of Kac-Moody algebras, building upon the existing tools available to computational mathematicians, for instance, the popular library sage-math. Once we have developed and verified this package against known tables of root multiplicities, we aim to start investigating the root multiplicities of simple graphs, and attempt to address some outstanding conjectures on the distributions of root multiplicities. A greater understanding […]
Zitong Yang
The explosively growing size of data in cyberspace with low-value density creates a pressing need for data processing, information extracting, and knowledge refinement. Many applications thus appear, such as personalized recommendation and pinpointing advertisement, by exploring hidden value behind massive amounts of data. More concretely, my project considers the problem of learning a complete (orthogonal) dictionary from sparsely generated sample signals. Unlike conventional methods that minimize one norm to exploit sparsity and learn the dictionary one column at a time, we propose an alternative sparse promoting operator to learn the […]