 All right. So I work at the Space Sciences Lab at UC Berkeley. The first thing you need to know is that we are not a department in the general sense. We are a so-called organized research unit, which means we don't have our own students or our own faculty. We don't teach courses at the Space Sciences Lab, and we are basically all on soft money and have to get our funding through grants and awards primarily from NASA and NSF. We are located up the hill close to Grizzly Peak Boulevard. So if you look up the mountain here, Lawrence Berkeley Lab, then Lawrence Hall of Science, and then even higher up, there are two buildings that you see there, and one of that is one of our buildings. We have the facilities and rooms to build instrumentation for space research, and even build full, complete scientific satellites. At the very bottom here is a picture that was taken seven years ago when we had five identical spacecraft put together in our clean room. They are now in space. They've been flying around for seven years. Two of them are circling Earth, two of them are circling Moon, and we have all the calibration and test facilities, vacuum chambers where we can test these instruments or satellites on the ground so that we make sure they work on orbit. We also have our own ground station. We can communicate with several of our satellites and send commands up and receive the data down here at SSL. So we do primarily, or we do space research, and all the data that we collect in space are mostly time series data, and the questions in the field of data science that we answer are mostly all related to the analysis of time series of data, finding certain signatures in the data, extracting information out of data streams, and finding correlations or certain signatures where you need specific data analysis tools to find changing properties or spikes or correlations in different properties that we measure. Our scientific satellites, most of the time, measure electric fields, magnetic fields, and the properties of particles, electrons, and ions and protons in space, which then tell us a lot about the processes that occur in the plasma in space and how things interact with each other. One of the things that is very specific for our field is that all our data are open, publicly open. We don't have any proprietary period that is a requirement that has come from primarily NASA over the past something like 20 years or so. So whenever we collect data and have confirmed that the calibration is correct, that the data quality is good, then we have to make it public to anybody in the world. We have a number of projects, and I list a couple of those projects here just to give you a little bit of a feeling of what we have, and then at the very bottom and at the end, I will also talk about a few software projects that we have at Space Sciences Lab. But let me start with these projects here. So for instance, we are part of a larger collaboration which is called the Center for Integrated Space Weather Modeling, so where we take the measured data and feed them into models of certain processes, mostly within the solar system. So we have two major groups, one that I am also part of, deals with science just within the solar system, and then we also have an astrophysical group that really looks into the very, very far distance. But this integrated space weather modeling deals with the processes around Earth and how we can first of all match the observations with predictions by models or then also improve models by finding differences in when we feed models with data and get different responses out of that than what we actually measure and see and then we need to improve the model somehow. Another thing, so many years ago, that was actually my very first project that I started with at Space Sciences Lab was the image spacecraft that was launched in 2000. We had a camera on board to observe the aurora from space. One of the data science problems was to identify violent eruptions and brightening of the aurora, which is called substorms in the images that we collected over five and a half years. Another instrument, the visual that's imager for sprites and upper atmospheric lightning, you all are very familiar with lightning, these lightning strikes that come from clouds down to the Earth and can knock out trees or power lines. There's a similar phenomenon of almost like lightning from the clouds going up into space. These things have different names, sprites, jets, elves, halos and so on, and we built an instrument to observe these things from space and then you collect thousands of images and want to find a way of automatically identify these different things, which is a mix between image processing and signal processing to find increases in signal strength in time series of measurements. MAVEN is a more recent project. It's a satellite that was launched to Mars approximately a year ago and the Space Sciences Lab built several of the instruments to measure and to analyze the particles around Mars with the final goal to find out why Mars many million years ago actually had an atmosphere similar to our atmosphere and it lost it over hundreds of thousands or millions of years, but we don't really know why and this project tries to find out why Mars lost its atmosphere. A new star is a telescope that observes the sun and it... Sorry, no. New star actually is an astronomical telescope that looks at x-rays from supernovae or neutron stars to find out why these things go off. Resi, this is the solar telescope which this instrument actually is in this respect special that every single photon that is collected by that instrument is analyzed and the information about that photon is sent down to Earth and so it does not really take an image as such as you are used with your camera but it gets the information about each individual photon and then on the ground you can generate your own image by just saying, okay, I want to select these photons that were collected during this time series or the photons that were collected with a very specific wavelength and all those things and that makes the analysis of the data stream coming from that satellite very special. City at home, you may have heard about this. This is a search for extraterrestrial signals from extraterrestrial civilizations in radio signals and the point is here that because we collect so many data it is almost impossible to analyze it on your own but they developed software that volunteers can sign up and over the night at home when their PCs are not doing anything and their PCs crunch the data in the background and collect and generate information if they can find any signs of radio signals in the data that they analyze. Them is that was this five satellite mission that I showed in the picture. Here one of the things is that we find violent changes in the properties of electric and magnetic fields in space and want to find when in time do they happen and what can we actually see about them and what can we analyze and timed this is a mission that has been in space for quite some time now and looks down at the upper atmosphere and we try to find signatures of changes in the brightness of the upper atmosphere that is caused by so-called atmospheric gravity waves. So these are just a few of the projects and then at the bottom here I list four software developments because BITS also deals with software tools development and open science and reproducibility and so on and so BOING is this Berkeley open infrastructure for network computing which was the basis for this distributed computing that is used in SETI at home and some other similar projects. Megalip is a medium energy gamma ray astronomy library which was developed at Space Sciences Lab and then given out to other researchers at other institutions. SolarSoft is the system for the Resi data analysis where they take these individual photons and the information and put together images or analyze streams of when these photons were emitted and wear on the sun and the space physics environment data analysis software is a recent development where we generated a suite of software tools that is now being used by at least six or eight different space missions to read the raw data, display raw data, analyze raw data and extract information out of that. So these are the major projects and software developments at Space Sciences Lab and I hope I gave you a little bit of an idea of what we are doing.