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2017 HANDBOOK


FRONTIER DEVELOPMENT LAB 2017

CONTENTS WELCOME TO FDL

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DELIVERY TEAM

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BRIEFING 08 MISSIONS 10 PLANETARY DEFENSE MISSION 01 TEAM LONG PERIOD COMETS

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PLANETARY DEFENSE MISSION 02 TEAM RADAR 3D SHAPE MODELING

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SPACE RESOURCES MISSION 01 LUNAR WATER AND VOLATILES

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SPACE WEATHER MISSION 01 SOLAR-TERRESTRIAL INTERACTIONS

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SPACE WEATHER MISSION 02 SOLAR STORM PREDICTION

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HOW FDL WORKS

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ACCELERATOR METHODOLOGY

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OVERVIEW 50 SPEAKERS 51 SCHEDULE 52 LODGING 60 MAPS 62


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PLANETARY DEFENSE

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NASA FRONTIER DEVELOPMENT LAB IS AN APPLIED RESEARCH ACCELERATOR DESIGNED TO ENHANCE NASA’S CAPABILITIES BY COMBINING THE EXPERTISE OF NASA, ACADEMIA, AND THE PRIVATE RESEARCH COMMUNITY. — 8 WEEKS AT NASA AMES & SETI INSTITUTE


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WELCOME TO FDL PLANETARY DEFENSE

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JAMES PARR | FDL DIRECTOR I’d like to extend a warm welcome to all our researchers and partners for our second FDL this Summer. In my career, I have never seen such firepower (both intellectual and computational) gathered together around an enroling cause. It is not an understatement to say that this year’s challenges have potential to affect every human being in the solar system and for that I would also like to say thank you on behalf of the FDL Steering Team. I wish you all an inspirational FDL 2017.

BILL DIAMOND | PRESIDENT & CEO, THE SETI INSTITUTE The SETI Institute is proud to once again be hosting NASA’s Frontier Development Lab, which explores the application of deep learning techniques to mission-critical science questions, with the objective of achieving accelerated research results. It is particularly exciting to be expanding FDL 2.0 beyond Planetary Defense to include new challenges in space weather modeling and space resource exploration. SETI Institute scientists will join research colleagues from around the world in providing mentoring for FDL teams and we are excited about the prospects for another breakthrough program!

BRUCE PITTMAN | CHIEF SYSTEMS ENGINEER, NASA ARC SPACE PORTAL NASA Ames is delighted to be bringing back the summer study series that we started back in 1975, and we are excited about the results that will come from this 8 week effort from such a talented group of participants.


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YOU TO OUR PARTNERS THANKSTHANK TO OUR PARTNERS


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FDL FACES JAMES PARR

BILL DIAMOND

FDL DIRECTOR

CEO,THE SETI INSTITUTE

BRUCE PITTMAN

JONATHAN KNOWLES

CHIEF SYSTEMS ENGINEER, NASA SPACE PORTAL

FDL IDEATION DIRECTOR

SARA JENNINGS

ERIC DAHLSTROM

FDL FACILITATOR

FDL FACILITATOR

GRAHAM MACKINTOSH

JASON KESSLER

EXECUTIVE PROJECT MANAGER, IBM

FDL PARTNERSHIP DIRECTOR

DEBBIE KOLYER

DARLENE WEIDEMANN

GRANTS MANAGER, THE SETI INSTITUTE

PLANETARY SUSTAINABILITY, NASA

ARMINE SAROIAN HR DIRECTOR, THE SETI INSTITUTE

CHIARA MIELE NASA.AI COORDINATOR

ALISON LOWNDES ARTIFICIAL INTELLIGENCE DEVELOPER RELATIONS, NVIDIA

LEO SILVERBERG DIGITAL LIAISON


FRONTIER DEVELOPMENT LAB 2017

BRIEFING ARTIFICIAL INTELLIGENCE HAS ALREADY PROVEN ITSELF TO BE A USEFUL TOOL FOR THE SPACE SCIENCES, OPENING UP OPPORTUNITIES IN DATA CAPTURE, ANALYSIS AND DECISION SUPPORT. THE GOAL OF FDL IS TO EXPLORE THE LIMITS OF THESE EMERGING TECHNIQUES THROUGH INTERDISCIPLINARY APPROACHES - IN THE PROCESS BROADENING BOTH OUR KNOWLEDGE AND OUR IMAGINATION ABOUT WHAT IS POSSIBLE. Silicon Valley has a storied history in developing new technologies useful to the space program. The microprocessor helped reduce the size and power requirements of computers during Apollo. More recently the advent of the Graphics Processing Unit (GPU) is enabling dusty theory on neural nets to hit pay dirt in the form of ‘Artificial Intelligence’, It makes sense therefore, that Silicon Valley be the location for NASA’s Frontier Development Lab (FDL) - an experiment in public / private partnership designed to find breakthroughs of material benefit to the space program. Based at the SETI Institute - a stone’s throw away from leaders in AI and Big Data such as IBM, Nvidia, Google, Kx, Lockheed Martin and Intel, NASA FDL is a

research accelerator established to close ‘knowledge gaps’ by inviting interdisciplinary teams to tackle unresolved possibilities that lend themselves to emerging AI approaches. FDL 2016 looked at opportunities within NASA’s Asteroid Grand Challenge (AGC), which has the stated goal of, “finding all asteroid threats to human populations and knowing what to do about them”. Potentially Hazardous Asteroids (PHAs) are objects above 140m which have orbits that cross the orbit of Earth and will potentially collide with our planet some time in the future. Last year’s teams developed breakthrough solutions of relevance to planetary defense, including meteorite discovery - informing asteroid composition, automated radar shape modeling of asteroids - crucial for any deflection strategies - and a tool


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called, ‘The Deflector Selector’ designed to help decision makers determine the correct strategy, in the event that a PHA be detected on its way to Earth.

To continue the successes of last year, FDL 2017 is bigger and better, exploring additional unresolved challenges suited for tackling with AI.

FDL 2017 will again be hosted by the wonderful team at the SETI Institute and NASA Ames who provide a home to FDL’s researchers in Silicon Valley for 8 weeks over the summer, as well as scientific oversight to project work. Needless to say, we’re thrilled about the line-up for FDL 2017 and are looking forward to some fascinating outcomes.

As well as two problems in Planetary Defense, we’re adding two Space Weather challenges and a Space Resources challenge to the mix. As well as expanding the content focus, we’re also doubling the people power and bringing vastly enhanced compute resources, thanks to our private sector and academic partners, who are providing massive cloud compute resources, hardware, dedicated software tools, AI training and specialist know how to help our teams as they dive deep into their given challenges.

FDL 2016: The Meteorite Detection team teach a drone to discover fresh falls.


FRONTIER DEVELOPMENT LAB 2017

THE MISSIONS PLANETARY DEFENSE

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MISSION 01 LUNAR WATER & VOLATILES DETERMINE THE LOCATION AND MOST PROMISING ACCESS POINTS FOR VITAL LUNAR H2O, IN TERMS OF COST EFFECTIVENESS AND ENGINEERING CONSTRAINTS.


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MISSION 02 SOLAR STORM PREDICTION DISCOVERING NEW RELATIONSHIPS AND AGENTS TO HELP PREDICT MAJOR SOLAR EVENTS.

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AI VISION WHITE PAPER AI & THE SPACE SCIENCES EXPLORING THE APPLICATION OF AI AS A BREAKTHROUGH CAPABILITY FOR THE SPACE PROGRAM, INFORMED BY THE EXPERIENCE OF FDL AND OUR PARTNER NETWORK.


FDL 2017 | LONG-PERIOD COMETS

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LONG-PERIOD COMETS

PROVIDE MORE WARNING TIME FOR LONG-PERIOD COMET IMPACTS BY APPLYING DEEP LEARNING TO METEOR SHOWER OBSERVATIONS. In planetary defense, long period comets have remained a class by themselves. They are recognized as the potentially most devastating threat (i.e. “extinction level events”). But any new comet discovered on an impact trajectory would likely only be discovered as it passed Jupiter, just a few years before impact. However, with machine learning, meteor showers may offer a clue. The proposal: replace the data analyst in the ‘CAMS’ meteor shower survey program by deep learning algorithms and thus enable a global expansion and temporal coverage of a camera network that can detect the dust trails of those potentially hazardous long period comets that came close to Earth’s orbit in the past ten millennia. The goal is to add years of extra warning time by providing comet searchers directions on where to look for comets when they are still far out. This task is particularly suited to a machine learning approach because of the large scale of data, the need for integration of surveys from around the globe without human intervention, and the need to operate for a long period of time. The deep learning algorithms would be used to recognize meteors amongst false positives (e.g., satellites), and can triangulate the meteor trajectory in Earth’s atmosphere, its entry speed, and the pre-impact orbit in space through combining different camera perspectives to the same meteor.


FDL 2017 | LONG-PERIOD COMETS

LONG-PERIOD COMETS // MENTORS PLANETARY SCIENCE MENTOR PETER JENNISKENS petrus.m.jenniskens@nasa.gov Peter Jenniskens is a senior research scientist and meteor astronomer with the SETI Institute. He is best known for recovering, with students and staff of the University of Khartoum, the first meteorite samples from an asteroid studied in space. He is author of the 790 page book “Meteor Showers and their Parent Comets” [Cambridge University Press]

DATA SCIENCE MENTOR SIDDHA GANJU siddhaganju@gmail.com Siddha is a Deep Learning Data Scientist at DeepVision. She graduated from Carnegie Mellon University with a Master’s in Computational Data Science. Her work ranges from Visual Question Answering to gathering insights from CERN’s petabyte scale data. She has been a speaker at Strata+Hadoop & StrataAI conferences, and is a member of the Open Leadership Cohort, Mozilla Science Lab.

SPECIALIST ADVISOR PETER GURAL peter.s.gural@leidos.com Pete Gural is a retired program manager and software engineer for Leidos Inc, who worked on image processing exploitation for the intelligence community. Once a hobby, meteor astronomy is now his full time passion, involved in ground/airborne meteor storm campaigns, designed a meteor mirror tracker, developed software variants of transient event detectors in video, including the CAMS software suite.


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PROGRAM MENTOR YARIN GAL yg279@cam.ac.uk Yarin is a Research Fellow at the University of Cambridge, and part-time Fellow at the Alan Turing Institute, the UK’s national institute for data science. He obtained his PhD from the Cambridge machine learning group, working with Prof Zoubin Ghahramani and funded by the Google Europe Doctoral Fellowship.

PROGRAM MENTOR JL GALACHE jlgalache@gmail.com J.L. Galache, PhD, is an asteroid astronomer turned NewSpace entrepreneur. He is the CTO of Aten Engineering, an asteroid prospecting startup. He has been the Acting Deputy Director of the Minor Planet Center, a consultant to NASA, founding mentor of FDL, and advisor to Deep Space Industries.


FDL 2017 | LONG-PERIOD COMETS

MEET THE TEAM: LONG-PERIOD COMETS ANTONIO ORDOĂ‘EZ PLANETARY SCIENTIST antonio.j.ordonez@gmail.com

Antonio OrdoĂąez began his career in astronomy in the physics department at the University of Central Florida. There he studied the physics of low-energy particle collisions through laboratory experiments to inform planet and ring formation models. From there, he went to obtain his Ph.D. from the University of Florida where he focused on studying pulsating variable stars in nearby dwarf galaxies. Utilizing Hubble Space Telescope imaging for this work, he gained experience analyzing time-series photometry and now seeks to apply those skills for use in the Planetary Defense FDL challenge.

SUSANA ZOGHBI COMPUTER SCIENTIST susana.zoghbi@cs.kuleuven.be

Susana received a PhD in Computer Science in December 2016 from the University of Leuven (KU Leuven) under the supervision of Prof. Sien Moens. Her research interests lie at the intersection of computer vision and natural language processing, and include deep learning, topic modeling and graphical models. Specifically, she is interested in developing end-to-end learning architectures to jointly detect finegrained attributes on both images and text. Since 2013, Susana has been a teaching assistant for the Text- Based Information Retrieval course at KU Leuven. Before her PhD, she obtained two Masters degrees, one in Mechanical Engineering, where her research focused on human-robot interaction technologies, and one in Mathematical Physics, where she focused on gravitational fluctuations in Domain Wall Spacetimes. In 2014, Susana was awarded a Google Anita Borg Scholarship.


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MARCELO DE CICCO PLANETARY SCIENTIST decicco10@gmail.com

Marcelo was born in Rio de Janeiro - Brazil and since childhood he has possessed a great passion for Astronomy. Marcelo joined a local amateur astronomical society (CARJ) when he was 14, where he learned to make home built telescopes and decided to be an astronomer. He studied at Observatorio do Valongo/UFRJ (OVUFRJ), and now is starting his PhD studies at Observatorio Nacional (ON), where he also completed his Master of Astronomy. Marcelo works in a governmental body called INMETRO (Brazilian National Metrology Institute) as researcher on DITEL (Division of Metrology for Information and Communication Technology), conducting studies on astrometry related to time and frequency.

ANDRES C. PLATA STAPPER COMPUTER SCIENTIST astapper@stanford.edu

Andres was born in Bogota, Colombia, where as a child he fell in love with earth and space biology. He obtained his undergraduate degree in biology in 1999 and his master’s degree focusing in medical microbiology in 2003, at Florida International University in Miami. During this time he met his wife, Heather Gamper, who was also a graduate student. During his master’s training, he was a visiting graduate student at the Copenhagen University Hospital and the Danish Technical University. Andres then joined the Florida State University PhD program, where he received his doctoral degree in 2013, concentrated in molecular and population genetics. It was during his PhD studies that his interests in planetary science and space biology where reignited. Andres joined Stanford University School of Medicine as a postdoctoral researcher scholar in 2013, where he studies the molecular mechanisms of inner ear organogenesis at Stefan Heller’s Lab using computational tools.


FDL 2017 | RADAR 3D SHAPE MODELING

PLANETARY DEFENSE MISSION O2

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RADAR 3D SHAPE MODELING

INVERTING RADAR IMAGES: SCALING RESOLUTION AND AUTOMATION OF SHAPE MODELING NEAR EARTH OBJECTS. Radar imaging has provided detailed information on the shapes and spins of dozens of near-Earth asteroids, but radar data is being collected faster than it can currently be analyzed. During FDL 2016 the radar shape modeling team studied ways to accelerate and better automate analysis of delay-Doppler radar images of asteroids obtained by the Arecibo and Goldstone planetary radars. Bayesian optimization and VAE (Variational Auto Encoder) neural net approaches were implemented showing promising results. The VAE approach in particular suggests futher opportunity for producing more detailed shape models from delay-Doppler data and identifying specific features. Two things are worth considering here: firstly, to investigate how the performance of the VAE network architecture scales as the number of latent variables is increased (while reducing runtime on an actual data sets and in terms of the network training time required). Secondly, to investigate other architectures used in machine vision and remote 3D modeling applications and determine if they have additional value to planetary defense.


FDL 2017 | RADAR 3D SHAPE MODELING

RADAR 3D SHAPE MODELING // MENTORS SHAPE MODELING MENTOR MICHAEL BUSCH mbusch@seti.org Michael received his BS in physics and astronomy at the University of Minnesota in 2005. He went to Caltech for grad school, where he had the fortune to be advised by the late Steve Ostro and by Shri Kulkarni, and to have a graduate fellowship through the Hertz Foundation. Michael completed his PhD in planetary science in 2010, and did postdocs at UCLA and at the National Radio Astronomy Observatory - under the Jansky Fellows program before starting as a research scientist at SETI in September 2013.

DATA SCIENCE MENTOR CHEDY RAISSI chedy.raissi@inria.fr Chedy received his doctorate in computer science from the University of Montpellier and the Ecole des Mines d’Alès, France in 2008. He has worked on topics such as data streams and sequential pattern mining. Chedy also worked at the National University of Singapore as a post-doctoral researcher on privacy-preserving data mining.

SPECIALIST ADVISOR MARINA BROZOVIC marina.brozovic@jpl.nasa.gov Jet Propulsion Laboratory


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PROGRAM ADVISOR ATILIM GUNES BAYDIN gunes@robots.ox.ac.uk Gunes is a postdoctoral researcher in the Machine Learning Research Group at the University of Oxford. His work mainly involves probabilistic programming and machine learning. Before Oxford, he was working as a postdoc in Ireland at the Brain and Computation Lab.


FDL 2017 | RADAR 3D SHAPE MODELING

MEET THE TEAM: RADAR 3D SHAPE MODELING AGATA ROŻEK PLANETARY SCIENTIST ar377@kent.ac.uk

Agata Rożek is a Post Doctoral Research Associate at the University of Kent (Canterbury, UK). She is interested in physical and dynamical characterisation of small bodies of the Solar System. Agata was an undergraduate at the Adam Mickiewicz University in her home-town (Poznań, Poland). She was a member of the Poznan Spectroscopic Telescope, performing observations of variable stars. She obtained her MSc in astronomy in 2010, with a thesis on asteroid orbital dynamics supervised by S. Breiter. This was followed by two years at AMU developing theory of the Yarkovsky-O’KeefeRadzievskii-Paddack effect, non-gravitational torque affecting asteroids.

ADAM COBB COMPUTER SCIENTIST adam.cobb@worc.ox.ac.uk

Adam is a PhD student in Machine Learning at the University of Oxford. His interest lies in applying machine learning techniques in areas such as Signal Processing, Reinforcement Learning and Deep Learning. Adam’s Master’s thesis focused on exoplanet detection in Kepler Mission Data using Gaussian processes to remove noise. His current research seeks to infer attractive regions of an animal’s landscape from its GPS readings. Outside of his academic work, Adam enjoys running, swimming and playing soccer. He also likes to learn languages and has studied Chinese, German and French. As an avid space enthusiast, Adam looks forward to working with FDL to tackle challenging and worthwhile problems.


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GRACE C. YOUNG COMPUTER SCIENTIST grace.young@some.ox.ac.uk

Grace C. Young is an MIT graduate in Mechanical & Ocean Engineering dedicated to developing technologies that help us better understand and manage the ocean. Recently named a 2017 National Geographic Emerging Explorer, she is currently a PhD candidate and Marshall Scholar at University of Oxford. Her work experiences include developing software for CERN and MIT, and helping design, build, and test submersible and aerial robots for Woods Hole Oceanographic Institution and NOAA. Robots she helped develop have deployed in the Arctic, Antarctic, Atlantic, and Pacific Oceans, creating 3D maps of ice shelves to better measure climate change, monitor marine protected areas, and survey endangered species.

SEAN MARSHALL COMPUTER SCIENTIST seanm@astro.cornell.edu

Sean Marshall specializes in using data from radar and lightcurve observations of near-Earth asteroids to characterize their shapes, sizes, and rotation states. He also uses infrared observations to determine asteroids’ thermal properties. Sean is a graduate student in Cornell University’s Department of Astronomy, advised by Donald Campbell. Sean is originally from southeastern Pennsylvania. He did his undergraduate studies at Arizona State University, double majoring in physics and astronomy while working in ASU’s Mars Space Flight Facility under the guidance of Phil Christensen. When not studying killer asteroids, Sean enjoys helping with astronomy-related public outreach activities, reading, exploring bicycle trails, and cheering for sports teams from Cornell University, Arizona State University, and the city of Philadelphia.


FDL 2017 | LUNAR WATER & VOLATILES

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LUNAR WATER & VOLATILES

DETERMINE THE LOCATION AND MOST PROMISING ACCESS POINTS FOR VITAL LUNAR H2O, IN TERMS OF COST EFFECTIVENESS AND ENGINEERING CONSTRAINTS. Space Resources is another way of saying, “living off the land”, as we build the new Frontier. Our solar system is abundant with mineral resources. The Moon in particular is a key asset in new era of exploration where deep space missions and future space settlers use what’s there to manufacture habitats, life-support, energy and fuel. However, to unlock this future we need to know where to look, get the economics right and ultimately, determine the most effective methods to usefully extract and process these resources in challenging environments. DNN techniques could be deployed to identify candidate locations in cold regions under the right conditions (such as shadow and lattitude). Known lunar ice locations could also serve as a training set for image recognition and other data fusion techniques factoring radiation, Earth-Moon communications, slope and other variables required for determining ideal locations on the lunar surface.


FDL 2017 | LUNAR WATER & VOLATILES

LUNAR WATER & VOLATILES // MENTORS LUNAR PROSPECTING MENTOR BRAD BLAIR planetminer@gmail.com Brad Blair holds degrees in geology, mining engineering and mineral economics. His professional experience ranges from mineral exploration and engineering to space resource economics. He has consulted to NASA, DARPA, Raytheon, Bechtel and the Canadian Space Agency on lunar and asteroid mining architectures, ISRU technologies, real-time 3D engineering

LUNAR PROSPECTING MENTOR PHIL METZGER philip.metzger@ucf.edu Dr. Philip Metzger is a planetary physicist who recently retired from NASA’s Kennedy Space Center, where he co-founded the KSC Swamp Works. He is now at the University of Central Florida -but still a part of the Swamp Works team -- performing research related to solar system exploration: predicting how rocket exhaust interacts with extraterrestrial soil, investigating the mechanics of soil, characterizing lunar and martian soil simulants, modeling the migration of volatiles on airless bodies, etc. While at NASA he led the Agency’s work in rocket blast effects for human-class missions.

SPECIALIST ADVISOR HAMED VALIZADEGAN hamed.valizadegan@nasa.gov As a NASA research scientist with specialty in data mining and machine learning, I am involved with making sense of increasing size of data NASA collects every day.


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SPECIALIST ADVISOR SHASHI JAIN shashi.jain@intel.com Focused on Corporate Innovation and working in the Internet of Things (IoT) and 3D Printing. Early stage startup advisor. Professional Speaker. Teacher of entrepreneurship. My work at Intel uses Lean Startup, Customer Development and Design Thinking to build new IoT products. I work with startups to accelerate these innovations to market. I bring a diverse skill set and 20 years experience in business development, engineering integration, rapid prototyping, and community building to my work.

PROGRAM MENTOR YAN LIU yanliu.cs@usc.edu Yan Liu is an associate professor in Computer Science Department at University of Southern California. She holds the Philip and Cayley MacDonald Endowed Early Career Chair and the director of USC Machine Learning Center. Before joining USC, she was a Research Staff Member at IBM Research. She received her M.Sc and Ph.D. degree from Carnegie Mellon University in 2004 and 2007. Her research interest includes developing scalable machine learning and data mining algorithms for time series data and structured data with applications to health care, sustainability and social network analysis.


FDL 2017 | LUNAR WATER & VOLATILES

MEET THE TEAM: LUNAR WATER & VOLATILES ELENI BOHACEK PLANETARY SCIENTIST horto.hortor@gmail.com

Eleni was born in Surrey and educated in Kent, United Kingdom. She graduated with a first class degree in Earth Sciences from University College London in 2014, with a specialism in Planetary Science. Currently Eleni is a member of the UCL-Cambridge Centre for Doctoral Training in Integrated Photonic and Electronic Systems, and completed her MRes degree in Integrated Photonic and Electronic Systems in 2015. Her MRes research projects included simulations of lasers for a space based interferometer, and the characterisation of inhomogeneities in InGaN-based light emitting diodes.

NADER MOUSSA COMPUTER SCIENTIST nwmoussa@icloud.com

Nader is an adventurous engineer excited by mathematics. For the last few years, he has been employed by a small Silicon Valley startup, where he has delivered image processing software to over one billion devices. In previous adventures, Nader has studied electromagnetic theory for wave propagation in the plasma environment not very far from Earth; used sonic energy to create three dimensional pictures of the Earth and its moon; and programmed powerful computers to help keep airplanes safe. Nader has a unique appreciation of autonomous and intelligent technologies, especially when they are incarnated as programmable digital electronic computers. Machines fail, and perhaps equally menacingly, machines sometimes succeed.


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TIMOTHY SEABROOK COMPUTER SCIENTIST timothy.seabrook@pmb.ox.ac.uk

Timothy graduated in MEng Intelligent & Robotic Systems at Lancaster University in 2014 and co-founded a Sharing Economy limited partnership in the same year. Since then, he has completed two years of DPhil CDT Autonomous Intelligent Machines and Systems at the University of Oxford and has begun developing his research into Distributed Learning of Dynamical Systems under Guarantees. Timothy’s overarching objective is to develop responsible machine learning and robotic solutions to benefit humankind.

DIETMAR BACKES COMPUTER SCIENTIST dietmar.backes@uni.lu

Dietmar is a Geoinformatics enthusiast with a broad range of knowledge in related disciplines from Geodesy and Surveying to Geoformation Science, Earth Observation, Remote Sensing and Photogrammetry. As a teaching fellow at University College London, Dietmar had the opportunity to acquire 12 years of experience in inspiring postgraduate education as well as innovative research in the field of 3D imaging ranging from small to large scale applications using active and passive sensing technologies deployed from a variety of platforms. During the last years, he has been focusing on terrestrial Laser scanning, Geospatial Application of Micro UAVs/Drones, Building Information Modelling (BIM) and Geospatial Big Data.

ANTHONY DOBROVOLSKIS PLANETARY SCIENTIST anthony.r.dobrovolskis@nasa.gov

Anthony Dobrovolskis (Tony Dobro for short) did his thesis at Caltech on “The Rotation of Venus”, and has specialized in celestial mechanics with a ``minor’’ in atmospheric dynamics ever since. He did postdocs at Cornell and in France, and worked at JPL for a few years before coming to work for UCSC at NASA Ames. For the last several years he has been working for the SETI Institute.


FDL 2017 | SOLAR-TERRESTRIAL INTERACTIONS

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SOLAR-TERRESTRIAL INTERACTIONS

IMPROVE UNDERSTANDING OF SOLAR INFLUENCE ON EARTH’S MAGNETOSPHERE AND ATMOSPHERE. The term ‘Space Weather’ generally refers to conditions on the sun and in the solar wind, interacting with our planet’s magnetosphere and upper atmosphere and in turn impacting the performance and reliability of space and ground based technological systems. The opportunity offered by AI techniques is remote sensing and in situ measurements from NASA’s Heliophysics System Observatory (e.g. magnetic field and coronal images from SDO and solar wind data from L1 missions) exploring the connections between solar forcing, heliospheric changes and manifestations of space weather in the Earth’s magnetosphere and atmosphere.  Potential breakthroughs include finding evidence for solar influence on lightning patterns, major improvements in the ability to predict the duration and strength of geomagnetic storms and the ability to predict ionospheric changes during major solar storms. 


FDL 2017 | SOLAR-TERRESTRIAL INTERACTIONS

SOLAR-TERRESTRIAL INTERACTIONS // MENTORS HELIOPHYSICS MENTOR MARK CHEUNG cheung@lmsal.com Mark Cheung is an astrophysicist at Lockheed Martin Solar & Astrophysics Laboratory and Stanford University. His scientific interests cover the Sun, space weather, cool stars and plasmas and magnetic fields pervading the universe. He is the Principal Investigator for the Atmospheric Imaging Assembly on board NASA’s Solar Dynamics Observatory. He loves having thousands of computers work for him.

DATA SCIENCE MENTOR GRAHAM MACKINTOSH mackintg@us.ibm.com Graham Mackintosh is a pioneer in the field of advanced analytics and has applied his thought leadership into multiple new domains for big data analysis, high performance cloud computing, AI and Deep Learning. As a member of IBM’s Emerging Technology Group, he is currently spearheading the challenge of applying Apache Spark, deep learning methodologies, and other cloud services to address complex business and scientific analytic needs.


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SPECIALIST MENTOR MONICA BOBRA mbobra@stanford.edu. Monica Bobra is a scientist at Stanford University in the W. W. Hansen Experimental Physics Laboratory, where she studies the Sun and space weather as a member of the NASA Solar Dynamics Observatory science team. She previously worked at the Harvard-Smithsonian Center for Astrophysics, where she studied solar flares as a member of two NASA Heliophysics missions called TRACE and Hinode. Monica Bobra received a B.A. in Astronomy from Boston University and a M.S. in Physics from the University of New Hampshire.


FDL 2017 | SOLAR-TERRESTRIAL INTERACTIONS

MEET THE TEAM: SOLAR-TERRESTRIAL INTERACTIONS CASEY HANDMER COMPUTER SCIENTIST caseyhandmer@gmail.com

Casey Handmer studied physics and mathematics at the University of Sydney and gravitational waves at Caltech, where he earned his PhD in 2015. He has published in optics and numerical relativity. He left academia the same day gravitational waves were first directly detected and has since worked at Hyperloop One, developing levitation, propulsion and route optimization technology. He is passionate about transportation, geology, space exploration, aviation, and wilderness.

BURCU KOSAR COMPUTER SCIENTIST burcu.kosar@nasa.gov

Burcu is a space plasma physicist and a space enthusiast. She received her PhD degree in Physics from Florida Tech in May 2015. Burcu also holds a B.S. in Physics and M.S. in Space Sciences from the same institution. The focus of her PhD work was studying the electrical coupling between thunderstorms and the Earth’s middle and upper atmosphere through computational modeling. She joined the Aurorasaurus project in early 2016 and is currently being hosted at NASA/GSFC as a postdoctoral researcher. Burcu is applying her computational and plasma physics expertise from lightning related atmospheric discharges to study space weather phenomenon such as aurora. Specifically, she analyzes space weather data together with the citizen science data and incorporates results into a nowcast model of the aurora using data assimilation techniques. Burcu is very interested in data science and learning about state-of-the-art machine learning and AI algorithms and applying them to scientific problems.


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GEORGE GERULES COMPUTER SCIENTIST gwgkt2@mail.umsl.edu

George Gerules is a PhD. Candidate in Applied Mathematics with an emphasis in computer science at University of Missouri -- St. Louis, where has also been an adjunct instructor in computer science. His current research interest, while finishing his dissertation, is in improving the use and implementation of automatically defined functions in Genetic Programming, a specialized field in Evolutionary and Genetic Algorithms. He has additional interests in computer languages, image processing, hyper spectral data processing, computer graphics, foundations of mathematics, AI, machine learning, distributed computing, parallel algorithms and computer architecture.

BALA PODUVAL PLANETARY SCIENTIST bpoduval@spacescience.org

Bala is a research scientist in Space Weather, affiliated with the Space Science Institute, Boulder, CO. Currently; she is investigating the sources of errors in space weather forecast and working on improving the accuracy of predicted ambient solar wind using magnetostatic models of the solar corona extrapolating the observed solar magnetic field out into the corona and into the heliosphere.


FDL 2017 | SOLAR STORM PREDICTION

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SOLAR STORM PREDICTION

DISCOVERING NEW RELATIONSHIPS AND AGENTS TO HELP PREDICT MAJOR SOLAR EVENTS. There have been 26 significant solar storm events affecting Earth over the last 50 years. In serious cases, these solar events can cause significant damage to human infrastructure. Solar storms are particularly significant as we begin to think about moving out of LEO into deep space exploration, permanently crewed facilities on the Moon, cis-lunar space and NASA’s goal to visit Mars within the next two decades. Emerging AI tools offer the opportunity to analyze variations in the solar magnetic field and solar corona using data from the Solar Dynamics Observatory (SDO, surface vector magnetograms and EUV images), in order to discover relationships between the observed magnetic activity in the photosphere and corona and to identify the agents that drive solar eruptive events (flares and coronal mass ejections). Potential breakthroughs include improved predictive models of major solar events, the emergence of new sunspot groups and models that predict the state of the Sun tomorrow. 


FDL 2017 | SOLAR STORM PREDICTION

SOLAR STORM PREDICTION // MENTORS HELIOPHYSICS MENTOR ANDRES MUNOZ amunozj@boulder.swri.edu Andres is a Colombian scientist that loves innovative techniques of interrogating and visualizing data, and loves to mentor and empower students and young scientists to become the best possible version of themselves. He believes that talent is not something that we are born with, but something acquired through hard work and constant practice. His research focuses on understanding how solar activity changes in time and how this affects the Earth and our technological infrastructure.

DATA SCIENCE MENTOR TROY HERNANDEZ troy.hernandez.phd@gmail.com Troy Hernandez is an American statistician and data scientist from Chicago, IL. He obtained his PhD in statistics and machine learning from the University of Illinois at Chicago in 2013. Troy has applied his machine learning expertise to diverse fields such as digital advertising, economic modeling, and virology. He is currently employed by IBM and remains an active community volunteer.


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SPECIALIST ADVISOR RYAN MCGRANAGHAN ryan.ghan@jpl.nasa.gov Ryan McGranaghan is a NASA Living With a Star postdoctoral fellow at the Jet Propulsion Laboratory, where he passionately blends space physics and data science to investigate the solarterrestrial connection. He received his Ph.D. in Aerospace Engineering from the University of Colorado at Boulder in 2016.


FDL 2017 | SOLAR STORM PREDICTION

MEET THE TEAM: SOLAR STORM PREDICTION ALEXEY ISAVNIN PLANETARY SCIENTIST alexey.isavnin@helsinki.fi

Alexey is a solar and space physicist from the University of Helsinki, Finland. His major research interest is space weather forecasting, especially in relation to coronal mass ejections and interplanetary shocks. Alexey received his PhD in 2014 and engaged in Post Doctoral work in the HELCATS project afterwards. In the past couple of years he developed a flexible 3D model of CMEs called FRi3D, the largest database of interplanetary shock waves IPShocks and machine learning algorithm for their detection. In his free time he likes to play tennis and guitar – he is also a bassist in a rock band.

ANAMARIA BEREA COMPUTER SCIENTIST artsciami@gmail.com

Anamaria holds a PhD in economics (2010) and computational social science (2012) and her current research is focused on the emergence of communication in biological and social networks, by applying theories and methods from economics, complex systems and data science to reinterpret historical, anthropological, biological and artistic data regarding the fundamental aspects of communication on our planet, from signaling in simple biological organisms to complex human and computer languages. She is an interdisciplinary scientist and uses a wide range of computational methods (agent-based modeling, network analysis, predictive analytics, natural language processing techniques, Bayesian Networks, semantic analyses and machine learning) as well as complexity science and economic modeling to study heterogeneous, noisy, complex systems phenomena. Anamaria hopes to develop further the current research in communication into hybrid, coevolving natural-computational techniques necessary for next generation AI technologies that will open new possibilities for space exploration and search for life in space.


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DATTARAJ DHURI PLANETARY SCIENTIST dbdhuri@gmail.com

Dattaraj is a doctoral student at Tata Institute of Fundamental Research, Mumbai, India. His research focuses on understanding solar magnetic activity and large scale magnetic phenomena. In an ongoing project, Dattaraj is working on the prediction of solar flares using support vector machines.

SEAN MCGREGOR COMPUTER SCIENTIST smcgregor@seanbmcgregor.com

Sean defended his PhD in Machine Learning at Oregon State on June 16th under the direction of Thomas Dietterich. Sean’s machine learning and visualization research focuses on the optimization, testing, and interpretation of reinforcement learning policies. In March Sean joined the XPRIZE Foundation to provide technical management to the IBM Watson AI XPRIZE. Between his research and non-profit work, Sean participates in a variety of academic and development communities. He has spoken during the conferences and workshops of NIPS, RLDM, AAAI, OSCON, VL/HCC, CompSustNet, OpenSourceBridge, and TA3M Amsterdam.


FDL 2017 | NASA.AI VISION

AI & THE SPACE SCIENCES

NASA.AI VISION


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AI & THE SPACE SCIENCES EXPLORING THE APPLICATION OF AI AS A BREAKTHROUGH CAPABILITY FOR THE SPACE PROGRAM, INFORMED BY THE EXPERIENCE OF FDL AND OUR PARTNER NETWORK.

SPECIALIST MENTOR MARIA NAVAS-MORENO maria.navas29@gmail.com I am a physicist fascinated by the use of data to understand and improve how things work, whether in physics, biology or the day-to-day life. I have a Ph.D. from the University of Utah and I have 10 years of experience developing imaging tools and sensing methods for various applications in medicine and biological research. While my area of expertise is Raman spectroscopy and imaging, I have a thorough understanding of statistics and unsupervised machine learning methods. Because I believe entrepreneurship is the highway for research and technology to reach people’s live, I am deeply involved in entrepreneurship outreach. In the last 2 years, I’ve organized 5 Startup Weekend events where for a weekend people can try the startup culture, validate ideas and network.


FDL 2017 | NASA.AI VISION

MEET THE TEAM: AI & THE SPACE SCIENCES JUSTIN HAVLOVITZ justinhav@gmail.com

Justin is an analytically-minded technology enthusiast. He has a great appreciation for learning and understanding systems and how they work; as a result he likes to build and tinker with his own personal computers. Additionally, Justin has completed personal projects in computer networking, programming, data modelling and forecasting in furtherance of his affinity for tinkering. Justin completed his undergraduate work in Ohio for business analytics & intelligence at Bowling Green State University in December 2016.

JACK COLLISON jack10@stanford.edu

Jack Collison, originally from Wisconsin, is a rising Sophomore at Stanford University. He is interested in studying Computer Science on the Artificial Intelligence track. He is also exploring interests in Data Science and Statistics as well as Economics. This year, Jack served on the Culturemesh team at Code the Change, developing a Facebook free-basics website for the non-profit. Further, he has an interest in languages, and has taken four years of Chinese and Spanish. He was also a two-time Intel ISEF Finalist, researching mammographic density and its association with genetics risk and axillary lymph node status.


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MORGAN HENDERSON morgan.james.henderson@gmail.com

Morgan is a graduate of the University of Montana, with Bachelor’s of Arts degrees in Physics (option in Astronomy) and Mathematics (option in Applied). His previous research includes exoplanetary science, specifically exoplanet detection, as a member of Project MINERVA (MINiature Exoplanet Radial Velocity Array) at the University of Montana, and circumstellar disk evolution as a member of the SETI Institute’s 2016 summer REU program. When Morgan isn’t conducting research, he likes to play games and solve puzzles, read, and spend time outdoors hiking and backpacking. Some of his future goals are to attend graduate school and go to space.

ZACHARY WERGINZ zachary.werginz@snc.edu

Zachary graduated from St. Norbert College in 2016 with a double major in physics and mathematics. In the summer of 2015, he participated in a research internship at Montana State University where he began his research in heliophysics. Zachary has continued that research over the past year as a research assistant at Georgia State University working alongside Dr. Andres Munoz-Jaramillo. During that time, he has discovered that his professional interests lie with data science. Zachary enjoys analyzing data in both his professional and personal life, and is particularly interested in learning more about machine learning and A.I.. His non-academic interests include heavy metal, video games, and the occasional bout of K-pop. And yes, his beard is specially cultivated to survive harsh Wisconsin winters.


FRONTIER DEVELOPMENT LAB 2017

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FRONTIER DEVELOPMENT LAB 2017

FDL METHODOLOGY 1. START WITH LASER-FOCUSED PROBLEM DEFINITION By starting with a tightly articulated goal, FDL contributors can more effectively search for relevancy - in other words, focus matters - especially as a team learns to work together. 2. TEAMS OF INTERDISCIPLINARY EXPERTS Breakthroughs invariably happen when domain specialties collide, or to use a visual metaphor, at the edges of the bell curve. Psychologists point to group think, attention blindness and other cognitive biases (such as the Asch conformity bias) as the reasons why seasoned experts often can’t see what fresh eyes can. 3. CO-OPETITION Rather than working competitively on the same problem (without sharing resources), our FDL teams are tasked to work on related but adjacent challenges within a culture of co-operation and open discussion - building on each other’s work in a generative way. The net result is a much broader set of skills - and fresh heads applied to the challenges at hand. 4. ENCOURAGE OBLIQUE DISCOVERY THROUGH RAPID ITERATION Doing things, iterating, making mistakes and learning comprise the unspoken engine of invention. However, as Stephen Covey points out in his book, ‘Where good ideas come from’, chance favors the prepared mind. Where experience has immense benefit is the ability to see the value in a wrong turn or accidental (‘oblique’) discovery. Everything from Superglue to the Big Bang was discovered this way. Hence we are supporting our FDL teams with seasoned mentors and coaches.


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5. ALLOW FOR INDIRECT INSPIRATION Indirect inspiration is the ability of our brains to see a pattern in one place and apply it in a different context to discover something completely new. This is sometimes called ‘analogous inspiration’ and is the mechanism behind methodologies such as biomimicry. At FDL we are building this into the 8 week syllabus by inviting guests and speakers from multiple industries, as well as organizing field trips and other opportunities for inspiration. 6. PLAN FOR COLLECTIVE RECOGNITION As a team makes its journey of discovery, it self-educates, creating a deeper understanding of a problem. This mature understanding allows collective recognition when a solution presents itself. Invariably true breakthroughs take this form. Rather than a light bulb moment, or lone act of genius, the team arrives at a powerful piece of thinking in the form of a ‘slow hunch’ - a breakthrough.


FRONTIER DEVELOPMENT LAB 2017

OVERVIEW OF NASA FDL 2017

OVERVIEW OF NASA FDL 2017 PROTOTYPING 26th-30th June PROBLEM PHASE

BIG IDEAS 3rd-7th July

Our five 2017 teams get to know the problem domains and the skills of the FDL 2017 faculty.

Teams are encouraged to work with their mentors to think big and broad on what could be a breakthrough in the field. “The best way to have a good idea is to have a lot of ideas”

Interim Review on Friday 30th June

CONCEPT DEFINITION 10th-14th June

DATA PREP & PROTOTYPING 17th-21st July

The teams are asked to close down to a core concept for development, scope out why it would be considered a breakthrough and what they will need to do over the coming weeks to get there. e.g. what is their training Formal Concept Review on Friday 14th June with all Mentors

The teams are encouraged to start rapidly conducting Machine Learning experiments. | “Fail quickly to succeed sooner” Friday 21st June Awards evening: “Biggest Mistake” / “Most Promising Approach”

SOLUTION PHASE

PROTOTYPING & PIVOTING 24th-28th July

Teams are given space to develop their most promising approaches and adapt and pivot if needed.

PROTOTYPING & DEMO 31st July 4th Aug

Teams are asked to produce a demo of their concept and approach.

DOCUMENT PHASE

DOCUMENT & DRAFT 7th-11th Aug

PRESENTATIONS

14th-18th Aug

‘Talent Trade’ - where team members work on other projects.

Informal first Demo with FDL close advisory.

The teams begin to prepare a 20 minute presentation, including their Demo, and paper. Presentation to senior NASA scientists on Friday 11th August.

The teams work on a polished “Ted Talk” style presentation and Demo of their work and first draft of a paper. Presentation at NASA.AI event on the 17th August


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SPEAKERS ALISON LOWNDES A.I. DEVELOPER RELATIONS NVIDIA

MARTA KWIATKOWSKA COMPUTER SCIENTIST UNIVERSITY OF OXFORD

REV LEBAREDIAN VP GAMEWORKS NVIDIA

REMUS LAZAR EXECUTIVE DIRECTOR WATSON DATA PLATFORM IBM

NAEEM ALTAF CHIEF SOLUTIONS ARCHITECT IBM

MARIANO VAZQUES HPC MECHANICS GROUP MANAGER BARCELONA SUPERCOMPUTING

FRANÇOIS CHOLLET A.I. RESEARCHER GOOGLE

GRANT BONIN CHEIF TECHNOLOGY OFFICER DEEP SPACE INDUSTRIES

ANIRUDH KOUL DEEP LEARNING DATA SCIENTIST MICROSOFT

KEVIN MURPHY RESEARCH SCIENTIST GOOGLE

JOSEPH LIM ASSISTANT PROFESSOR USC

BREAKFAST SPEAKER SLOTS: MONDAYS LUNCHTIME SPEAKER SLOTS: WEDNESDAYS EVENING EVENT: THURSDAYS


11:00

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15:00

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13:00

FDL WELCOME BBQ @ NASA ARC

LIGHTNING TALKS @ SETI INSTITUTE

MEET THE TEAMS

LUNCH BREAK

RESEARCHERS CHECK-IN @ SETI INSTITUTE

12:00

REVIEW OF 8 WEEKS

WELCOME

10:00

09:00

26th June Mon

WEEK 1 // BOOTCAMP

FIELD TRIP

A.I. DEEP DIVE @ NVIDIA XAVIER

LUNCH BREAK

A.I. DEEP DIVE @ NVIDIA XAVIER

27th June Tues

NEW SPACE RECEPTION

PLANETARY DEFENSE WORKSHOP @ NVIDIA XAVIER

LUNCH BREAK

SPACE WEATHER WORKSHOP @ NVIDIA XAVIER

LUNCH BREAK

SPACE WEATHER 101 @ NVIDIA XAVIER

INNOVATION METHODOLOGY @ NVIDIA XAVIER

INNOVATION METHODOLOGY @ NVIDIA XAVIER PLANETARY DEFENSE 101 @ NVIDIA XAVIER

29th June Thurs

28th June Weds

ASTEROID DAY @ CALIFORNIA INSTITUTE OF TECHNOLOGY

PLANETARY DEFENSE WORKSHOP @ NVIDIA XAVIER

SPACE RESOURCES WORKSHOP @ NVIDIA XAVIER

LUNCH SPEAKER

SPACE RESOURCES WORKSHOP @ NVIDIA XAVIER

INNOVATION METHODOLOGY @ NVIDIA XAVIER

30th June Fri

1st July Sat

FRONTIER DEVELOPMENT LAB 2017

WEEK 1 // BOOT CAMP


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11:00

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09:00

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

ANNOUNCEMENTS & INTRODUCTIONS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

3rd July Mon

WEEK 2 // BIG IDEAS

4th July Tues

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH SPEAKER @ SETI INSTITUTE

EVENING SPEAKER @ SETI INSTITUTE

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

6th July Thurs

5th July Weds

INTERIM CONCEPT REVIEW @ SETI INSTITUTE

LUNCH BREAK

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

7th July Fri

8st July Sat

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WEEK 2 // BIG IDEAS


21:00

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11:00

10:00

09:00

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

TEAM MEETINGS @ SETI INSTITUTE

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

11th July Tues

10th July Mon

WEEK 3 // CONCEPT DEFINITION

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH SPEAKER @ SETI INSTITUTE

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

12th July Weds

EVENING EVENT

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

13th July Thurs

FORMAL CONCEPT PRESENTATION @ SETI INSTITUTE

LUNCH BREAK

DEFINE AND PLAN W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

14th July Fri

15th July Sat

FRONTIER DEVELOPMENT LAB 2017

WEEK 3 // CONCEPT DEFINITION


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DEVELOP W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

TEAM MEETINGS @ SETI INSTITUTE

DEVELOP W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEVELOP W/ MENTORS @ SETI INSTITUTE

DEVELOP W/ MENTORS @ SETI INSTITUTE

LUNCH SPEAKER @ SETI INSTITUTE

DEVELOP W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

19th July Weds

18th July Tues

17th July Mon

WEEK 4 // DATA PREP & PROTOTYPING

EVENING EVENT

DEVELOP W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEVELOP W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

20th July Thurs

AWARDS EVENING @ SETI INSTITUTE

LUNCH BREAK

DEVELOP W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

21st July Fri

22nd July Sat

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WEEK 4 // DATA PREP & PROTOTYPING


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LUNCH BREAK

TEAM MEETINGS @ SETI INSTITUTE

DEVELOP W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEVELOP W/ MENTORS @ SETI INSTITUTE

DEVELOP W/ MENTORS + TALENT TRADE @ SETI INSTITUTE

LUNCH SPEAKER @ SETI INSTITUTE

DEVELOP W/ MENTORS @ SETI INSTITUTE

EVENING EVENT

DEVELOP W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DEVELOP W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

27th July Thurs

26th July Weds

25th July Tues

24th July Mon

WEEK 5 // PROTOTYPING & PIVOT

INTERIM REVIEW @ SETI INSTITUTE

LUNCH BREAK

DEVELOP W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

28th July Fri

29th July Sat

FRONTIER DEVELOPMENT LAB 2017

WEEK 5 // PROTOTYPING & PIVOTING


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TEST & ITERATE @ SETI INSTITUTE

LUNCH BREAK

TEAM MEETINGS @ SETI INSTITUTE

TEST & ITERATE @ SETI INSTITUTE

LUNCH BREAK

TEST & ITERATE @ SETI INSTITUTE

FDL ADVISORY DEMOS @ SETI INSTITUTE

LUNCH SPEAKER @ SETI INSTITUTE

TEST & ITERATE @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

2nd Aug Weds

1st Aug Tues

31st July Mon

WEEK 6 // PROTOTYPING & DEMO

EVENING EVENT

TEST & ITERATE @ SETI INSTITUTE

LUNCH BREAK

TEST & ITERATE @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

3rd Aug Thurs

MILESTONE REVIEW @ SETI INSTITUTE

LUNCH BREAK

TEST & ITERATE @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

4th Aug Fri

5th Aug Sat

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WEEK 6 // PROTOTYPING & DEMO


21:00

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DRAFT W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

TEAM MEETINGS @ SETI INSTITUTE

DRAFT W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DRAFT W/ MENTORS @ SETI INSTITUTE

DRAFT W/ MENTORS @ SETI INSTITUTE

LUNCH SPEAKER @ SETI INSTITUTE

DRAFT W/ MENTORS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

9th Aug Weds

8th Aug Tues

7th Aug Mon

WEEK 7 // DOCUMENT & DRAFT

MOCK PRESENTATION W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

DRAFT W/ MENTORS @ SETI INSTITUTE

10th Aug Thurs

PRESENTATIONS TO NASA STAFF

11thAug Fri

12th Aug Sat

FRONTIER DEVELOPMENT LAB 2017

WEEK 7 // DOCUMENT & DRAFT


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DELIVERY W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

TEAM MEETINGS @ SETI INSTITUTE

DELIVERY W/ MENTORS @ SETI INSTITUTE

LUNCH BREAK

PEER REVIEW ALL TEAMS @ SETI INSTITUTE

PRESENTATION PREP @ SETI INSTITUTE

LUNCH BREAK

PRESENTATION PREP @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

BREAKFAST SPEAKER @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

16th Aug Weds

15th Aug Tues

14th Aug Mon

WEEK 8 // PRESENTATIONS

FINAL PRESENTATIONS

17th Aug Thurs

FDL FINAL BBQ

WRAP UP @ SETI INSTITUTE

ANNOUNCEMENTS @ SETI INSTITUTE

18th Aug Fri

19th Aug Sat

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WEEK 8 // PRESENTATIONS


FRONTIER DEVELOPMENT LAB 2017

LODGING HOME AWAY FROM HOME Participants will be hosted at NASA Ames, Moffett Field for the duration of the Frontier Development Lab.

CHECK IN: NASA Ames, Building 19 Moffett Field, CA 94034 During the course of the program, you will live on-site at NASA Lodge Exchange. NASA offers only dormitory accommodations, with each room providing double occupancy. FDL participants will be paired-up and assigned rooms upon check-in. Each room is of good size and has two twin size beds, a microwave, full size refrigerator, basic bathroom facility, and internet access. Toiletries and items such as hair dryers and irons are not provided in the rooms.

NASA LODGE MAIL ADDRESS NASA Ames Lodge at Moffett Field PO Box 17, M/S 19-1 Moffett Field, CA 94035

FRONT DESK (650) 603-7100 or (650) 603-7101

SETI INSTITUTE: FDL HQ SETI Institute, 189 Bernardo Avenue, Suite 200 Mountain View, CA 94043

NASA ON-SITE RESTAURANTS Space Bar (Building 3) Saturday - Sunday: CLOSED Monday - Friday: 11:00am - 7:00pm The Mega Bites Cafe (Building 235) Saturday - Sunday: CLOSED Monday - Friday: 6:00am - 2:00pm

GYM The Swim Center (650) 603-8025 Monday - Friday only 10:00am - 1:00pm, 3:00pm - 6:00pm Daily fee for non-members or guests: $5.00 Westcoat and corner of Bailey Road Building #109

TRANSPORT Caltrain | www.caltrain.com (good for visiting San Francisco or San Jose) VTA | www.vta.org (Santa Clara Valley Transportation Authority) Bus 81 at stop on North Akron and Mc Cord. Every 30 min Monday - Friday, and every 60 min on Saturdays

LAUNDRY The laundry facility is located in building 547B, within walking distance from NASA Lodge. • Washing machine: $1.50


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NASA AMES RESEARCH PARK

NASA AMES LODGE CHECK-IN

ENTRANCE TO THE SETI INSTITUTE


FRONTIER DEVELOPMENT LAB 2017

GETTING TO SETI INSTITUTE NASA AMES | BUILDING 19 Moffett Field, CA 94035

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SETI INSTITUTE 189 North Bernardo Avenue Mountain View, CA 94043

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NASA AMES MAP CHECK-IN ENTRANCE TO NASA AMES Bushnell Road

CHECK IN

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ENTRANCE TO 26 RESEARCH PARK ourt West yC rr

Clark Road

Westcoat Road

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LODGING

KEY

Bldg. 26 Main Gate / Badging

Bldg. 19 NASA Lodge Registration

547b 547d

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Bldg. 547D NASA Lodge rooms

Bldg. 109 Gym

Bldg. 555 NASA Space Portal

Bldg. 67 USPS

Bldg. 547B Laundry Facility


NASA POINT OF CONTACT Darlene M. Wiedemann darlene.wiedemann@nasa.gov Office: 650.604.1857

GENERAL INFORMATION info@frontierdevelopmentlab.org

TWITTER @nasa_fdl #nasafdl17

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