Prof. David Lary

•  May 2010 
  A Global Context for Health Issues Using Remote Sensing Data
•  Sep 2009 
  AeroStat: Online Platform for the Statistical Inter-comparison of Aerosols
•  Sep 2009 
  Characterizing Pelagic Habitats within U.S. Gulf of Mexico Coastal Waters Using Satellite Derived Da
•  Sep 2009 
  Chemical Modeling Studies with Aura MLS Measurements Addressing Partitioning, Consistency, and Long-

Bio: David Lary completed his education in the United Kingdom. He received a First Class Double Honors B.Sc. in Physics and Chemistry from King’s College London (1987) with the Sambrooke Exhibition Prize in Natural Science, and a Ph.D. in Atmospheric Chemistry from the University of Cambridge, Churchill College (1991). His thesis described the first chemical scheme for the ECMWF numerical weather prediction model. David then held post-doctoral research assistant and associate positions at Cambridge University until receiving a Royal Society University Research Fellowship in 1996 (also at Cambridge). The Royal Society is the world’s oldest scientific academy, founded in 1660. From 1998 to 2000 David held a joint position at Cambridge and the University of Tel-Aviv as a senior lecturer and Alon fellow. An Alon Fellow is the highest award Israel can give a young scientist. In 2000 the chief scientific adviser to the British Prime Minister and Head of the British Office of Science and Technology, Professor Sir David King, recommended David to be appointed as a Cambridge University lecturer in Chemical Informatics. In 2001 David joined UMBC/GEST as the first distinguished Goddard fellow in earth science at the invitation of Richard Rood. His automatic code generation software, AutoChem, has received five NASA awards and has been recommended for the NASA Software of the Year Award. David is currently involved with NASA Aura validation using probability distribution functions and chemical data assimilation, neural networks for accelerating atmospheric models, the use of Earth Observing data for health and policy applications, and the optimal design of Earth Observing Systems. The thread running through all the research is the use of observation and automation to facilitate scientific discovery. His application of machine learning to bias detection and proxy inference led to the creation of the first global seamless record of atmospheric chlorine and received recognition as a NASA Aura mission science highlight, was selected as NASA GSFC Atmospheric Chemistry and Dynamics Branch selected publication, and a JCET science highlight. David has received three prestigious fellowships, four editorial commendations, around five million dollars in research funding, six NASA awards, and has seventy-one publications with over a thousand citations in the peer-reviewed literature with a Hirsch Index of sixteen and on average 20.2 citations per publication.