Teaching basic lab skills
for research computing

Demographics (part two)

Here are summaries (slightly edited) of what people taking the course do. There's quite a range...

  • Stem cell biology, high-throughput screening, high-content analysis.
  • My research aims to improve the resolution of ultrasonic images created during ultrasonic inspections of thin metal sheets and metal welds though the use of digital signal processing algorithms.
  • I am currently working on learning Django to create websites. I am also developing new course content in programming and scientific computing for a 4-year degree in GIS.
  • I do simulations of protein folding and assembly for naturally disordered proteins, the kind that are implicated in degenerative diseases like Alzheimer's and Parkinson's. I also use dimensionality reduction techniques to find clusters in the conformation spaces of the proteins.
  • I am working on computational simulation, trying to understand the basic rules underlying protein dynamics
  • I am currently working on modeling the accretion disks of cataclysmic variable stars. I also study High Mass XRay Binaries, as well as Low Mass XRay Binaries.
  • We build and maintain global databases of fisheries statistics and analyze this information to uncover ways by which we can manage global fishery resources more sustainably.
  • Use classical molecular dynamics running on clusters and supercomputers to simulate the dynamics of individual proteins from a variety of species. In particular I focus on proteins that are embedded in the cell membranes as these are involved in many different important physiological functions e.g. transport and cell signalling.
  • Technical solutions to health and safety problems
  • I am a molecular biologist and study how different genes affect cellular phenotypes. For example, I switch off specific genes (alone or in combination) using RNAi. Typically, I perform thousands of experiments using automated liquid handling stations (robots) and record the resulting phenotypes (typically as numbers). In addition, I study how gene expression is affected using next-generation sequencing techniques (RNAseq).
  • Chemical health and safety, mostly data analysis of biological monitoring (that's urine and blood samples); creating software tools to help non-mathematicians run mathematical models (check out http://www.advancedreachtool.com/); some PBPK modelling (systems of differential equations of how chemicals move through the body).
  • We study how information about sensory stimuli is transduced, transformed, and represented in the central nervous system. At present we focus on such processes in the early visual system.
  • I am currently working on the fluid dynamics of blood droplet impact using a simulation method called Smoothed Particle Hydrodynamics. I am currently writing my code in Matlab, but may need to move to C or C++ to increase the speed of the computations.
  • Developing algorithms for neuroimaging data analysis. This involves implementation of image processing algorithms as well as statistical tools.
  • I am using statistical downscaling, which involves different types of multi-variate regressions, to predict surface observations from information provided by course resolution global climate models. Currently I am working on a project in which we are using downscaling to make future projections of the severity and likelihood of wildfire in BC. I am using R almost exclusively for this project.
  • Running hydrologic models in a unix environment. Coding in R to analyze outputs including plotting and mapping. Querying data from netcdfs and adjusting code in a statistical downscaling model that can be in c, fortran, or shell.
  • On the bioinformatics front I am comparing the evolution of the overlapping regions of the 4 genes from Hepatitis B Virus. I have used python to cut, copy and curate the sequences downloaded from Genbank to get a useable and well annotated dataset. Quite a task considering the sorry state of the data in the HBV database.
  • I do research to understand how we recognize speech and how we learn to recognize speech. By speech recognition, I mean the mapping from the real-valued speech signal to abstract linguistic structure, like sentence structure and meaning. Methodology includes recording speakers of different languages, running psychological speech perception experiments on adults and infants, and computational modeling using machine learning algorithms.
  • My research is in the fields of hydrology and aquatic ecology. I use both field and model approaches to understand the linkages between physical and chemical hydrologic processes and the resulting impact on aquatic ecosystems.
  • At Census Bureau: Small area estimation for local government surveys. Ongoing: Statistical applications of specialized optimization methods; statistical modeling of systems of differential equations.
  • Working on a Brownian dynamics simulation of secreted protein mass transport from adherent mouse embryonic stem cell (mESC) culture with perfusion of laminar flow; culturing mESCs for self-renewal or differentiation induces the secretion of many different signalling proteins.
  • I'm working with a database of location and health information for 20,000 diabetes patients in California and trying to evaluate how/if their health condition is related to their neighborhood environments. I work with GIS to characterize their access to healthy and unhealthy food resources, parks, public transportation, and other environmental factors as the data becomes available.
  • Applied Statistics with focus on Statistical Genetics.
  • Numerical simulation of an impacting drop on to a solid surface with an open cavity which has a wide range of application such as optimizing the production cost of water repellent fabrics, predicting the quality of arc welding, improving printing quality... Long story short, application of CFD in simulation of multiphase fluids processes.
  • The physics for blood flight in blood pattern analysis. Ultimately we're trying to create a program that can recognize blood stains and draw the path of their flight back to their source.
  • Attention and working memory. Currently attempting to program a useful field of view task, and an experiment that tests memory for facial features.
  • I study stem cell bioengineering, but try to bring a computational twist into things. So I'm working on models of cell proliferations and differentiation, and starting to look at some optimization methods to help with the engineering aspects of many projects within the lab.
  • Investigation into the role of international seafood trade in the expansion of the world's marine fisheries.
  • There is a lack of surface markers used to classify early cardiac progenitor cell types during differentiation from mouse embryonic stem cells. My project is to use mass spectrometry and microarrays to identify surface markers (and other proteins) involved in the differentiation process. Using bioinformatics and potential cell-cell interaction modeling, I would like to mine the data to extract potentially biologically relevant data pertaining to this process.
  • I'm studying the effects of ocean acidification on marine organisms. This involves constructing a lab to manipulate and monitor water chemistry. Currently, I'm trying to understand if growing under different chemical conditions results in biological materials with different structural properties.
  • I'm working on the molecular evolution of the small subunit of the prokaryotic ribosome. This is a structural informatics project dealing with analyzing 2 and 3-dimensional molecular structures and implementing energy algorithms for ribosomal RNA molecules. My current stage of work involves wetlab RNA production and functional assays on RNA fragments produced in the previous stage of analysis.
  • Implicit Large-Eddy Simulation (ILES) and Direct Numerical Simulation (DNS) of transition to turbulence. Looking at both the physics of transition and the numerical methods require to model it accurately.
  • I am trying to develop a new way of stimulating paralyzed muscle. I am using a technology called surface Functional Electrical Stimulation, which uses electricity to contract skeletal muscle. This method is very rough and does not give precise joint torque vectors. I am looking for a way to use this technology such that the joint torque created by the contracting is precise and repeatable.
  • I'm currently studying the mechanisms by which neurons in the superior colliculus selectively respond to some visual stimuli but not others. What are the properties of these neurons and the input they receive that allow them to respond to specific sensory features?
  • My work involves statistical downscaling, a way of relating future projections made by climate models at the large scale to the scale of weather stations. Climate models work well for broad studies of the climate system but are poor at describing small scale effects such as the climates of cities because of their low resolution (grid cells with sides on the order of hundreds of kilometres). In downscaling, statistical functions are used to relate the low resolution model data to weather station observations during past times. These functions can then be used to relate future climate projections to the smaller scales, yielding projections with much greater detail.
  • Currently focusing on Application Security; identifying Cyber threats and mitigation strategies. Would like to become more proficient in programming and design to be able to develop my own Application Security tool set.
  • A central theme in my research is the development of advanced (model-based) process control methodologies on the basis of such observed data, with a particular focus on chemical and metallurgical systems. This involves extracting complex, nonlinear regularities and trends in measured plant data. Subsequently, models are derived for the purposes of, among other, nonlinear system identification, process diagnostics, as well as insights into underlying process behavior. To this end, a number of mathematical and computational techniques are used including: * Nonparametric learning methods such as kernel methods, ensemble methods and artificial neural networks * Nonlinear time series analysis * Multivariate statistics and other exploratory data analysis techniques.
  • I primarily do Computational Fluid Dynamics (CFD) modelling of combustion systems, ranging in size and application from pilot/experimental scale to industrial/power utility scale. The experimental scale work tends to be in new technologies, such as gasification and high pressure combustion, whereas the industrial scale work tends to look at design and/or operational issues in existing systems.
  • For my PhD, I investigated a type of piezoelectric ultrasonic motor. There were two parts to my research. The first part was the coupled axial-torsional vibration of pretwisted beams; I derived beam equations to model the structure and compared the predicted resonance frequencies with results from finite element method. In the second part I studied the nonlinear dynamical system of a disk bouncing on a vibrating platform as a model of the stator-rotor interaction of the motor.
  • My current area of interest is voting behavior and party strategies. I aim to combine two assumptions about voting behavior into one more general model. Such a heterogeneous voter model can tackle many empirical puzzles and explain political outcomes of democratic processes more accurate.
  • Supporting 300+ scientists in biotech research field.
  • I am doing research in statistical genetics. It is well known that genetic variants are related to many complex diseases. My work is to develop statistical methods for analysis this type of data.
  • Many of the most pressing issues in ecology require understanding how biological systems respond to global scale changes in climate and habitat. In order to understand these impacts it is necessary to study ecology at large scales. Research in my lab focuses on using quantitative macroecological approaches, including large ecological databases, advanced statistical methods, and theoretical modeling to understand broad scale ecological patterns.
  • Supporting clinical research data management at a commercial company. I'm about to enroll in a bioinformatics masters program with Johns Hopkins University and aspire to work on microbial ecological genomics (e.g. Human Microbiome Project etc).
  • I write image and statistical analysis software in Matlab, more of statistical analysis at the moment than image analysis.The SW is a GUI tool for users (mostly our team at the moment) to run statistical analysis on neuroimages image sets. The image sets are mostly PET, MRI, and fMRI studies.
  • Working on protein sequence analysis, phylogenetics, and evolutionary models.
  • I do modeling and theoretical work related to superconducting quantum bits. Previously, I modeled a particular design for a superconducting quantum bit. At present, I am trying to design a protocol to transfer the state of a superconducting quantum bit to another, via a superconducting transmission line.
  • I am working on methods for estimating the size of a genetic effect from large datasets in cases where the same dataset or same individuals is used for multiple purposes in sequence. Dataset sizes include 1M + variables, 2K + patients. Methods I'm using include bootstrap resampling, in which analysis of the dataset is repeated 10K-50K times.
  • My current research will provide musicians a system to compose and perform with a sound corpus by exploring a three-dimensional space by means of non-contact gestures. I am also planning to do research in automatic music recommendation and playlist generation.
  • I'm currently conducting psychiatric genetic research. This involves analyzing data from high-through DNA genotyping experiments.
  • The focus of my thesis is to develop an reinforcement learning (RL) agent for augmenting the supervisory controllers on an industrial grinding circuits. The majority of these circuits depend on expert systems (ES) for supervisory control, which are by in large more static than they are adaptive. My research is focused on augmenting these systems; specifically, to introduce online adaptability to ES using RL.
  • I am working on hydrologic modelling projects for several watersheds in British Columbia. This involves model set up, calibration (using multi-objective optimization tools), uncertaintly analysis. The models will be later forced with downscaled outputs from GCMs for future climate projections. I am also comparing the results with the RCM projections for the same catchment.
  • High throughput imaging system.
  • I am working on the connection between meteorological model output to hydrological model input for the purposes of water supply forecasting.
  • Resource modeling for healthcare systems.
  • I am a Political Scientist, working on policy processes in regional trade agreements. Statistically, I rely multivariate statistics, above all survival Models. In my most recent work I started to have a look at networks, too.
  • Clinical trail Epidemiology Study Genome Wide Association Study Data base management
  • CFD and Fluid-Structure Interaction studies of the repsonse of flexible bodies to various fluid loadings.
  • Solid state quantum computing, particularly superconducting qubits and doped diamond spin assemblies to build scalable quantum architecture.
  • I am working on Computational Fluid dynamics applied to reacting flows. Also interested in compressible flows over blunt body.
  • Customizing a Plone content management system for use in a parliamentary context, and using the Deliverance theming application to present two applications to the end user via a single unified user interface.
  • My research is focused on how neurons encode and decode odor information.
  • I am working on the background reduction for the PICASSO Experiment.
  • Human factors research. Statistical analysis on crash data. Explore driver distraction's effects on injury severities.
  • I am currently investigating different copy number algorithms by doing a large-scale evaluation of many different algorithms.
  • I am using bioinformatic methods to study microbial genomes and evaluate the effects of microbial community on ecosystem.
  • Bioinformatics support. I am responsible for the public accessible databases and maintaining and updating public tools like UCSC genome browser, Ensembl browser, Galaxy server for internal use.
  • I perform data analysis on high-throughput data from experiments designed to investigate the molecular mechanisms of how hypoxia (low oxygenation levels) in cancer tissues arises, and how cancer cells cope with this adversarial condition, with the hope that sufficient insight may eventually lead to novel therapeutic strategies. I work with both microarray and next-generation sequencing data.
  • I work in Statistical and Bioinformatics analysis of complex disease. My previous work focused on GWAS of longitudinal traits related to diabetes. Currently I work on sequence and expression analysis of head and neck cancer. My work involves a lot of figuring out how to work with massive datasets and complex algorithms.
  • I am a field ecologist switching to using digital evolution (Avida) for studies of evolutionary ecology. In my work, I look at questions related to the evolution of tolerance, group formation, and group stability, prerequisites for the evolution of sociality. My research includes developing experiments for in-silico testing of hypotheses of the evolution of cooperation and sociality which are based on in-situ observations of carnivore ecology.
  • Research on mesoscale variability in the California Current using quasi-Lagragian isobaric floats. The main focus is on westward transport off Central California coast, its kinematic characteristics and mechanisms. Besides Lagrangian data, we use satellite altimetry, model outputs, standard oceanographic data.
  • Housing market and monetary policy.
  • I have a wide range of research interests from understanding the effects of climate change to understanding anthropogenic effects on coastal systems. At the moment, I am working on developing models to help improve our understanding of the processes affecting marine snow and particle flux
  • I am developing techniques to perform deep sequencing on single cells. I am interested in how RNA transcripts partition asymmetrically after cell divisions critical in development. My research has a long-term goal of better understanding cell division processes that are typically mis-regulated in cancer cells.
  • I study phylogenetic and biogeographic relationships among terrestrial mammals. I am interested in how geography and evolutionary processes interact to produce and maintain biodiversity. I also do some research on phylogenetic methods and ways of analyzing geographically explicit DNA data.
  • 'I'm studying how agricultural practices effect microbial communities and the impact that these changes have on greenhouse gas flux from soils. I'm using metagenomic data and a microbial ecology approach to determine the diversity and composition of these communities. I'm also developing approaches to analyze metagenomic data

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