Company: Engility, Chantilly, VA
Company Description: Engility is a pure-play government services contractor providing highly skilled personnel wherever, whenever they are needed in a cost-effective manner. Headquartered in Chantilly, Virginia, Engility is a leading provider of specialized technical consulting, program and business support services, engineering and technology lifecycle support, information technology modernization and sustainment.
Nomination Category: Information Technology Categories
Nomination Sub Category: Technical Professional of the Year

Nomination Title: Aparna Radhakrishnan, Computational Expert

1. Tell the story about this nominee's achievements since January 1 2013 (up to 525 words). Focus on specific accomplishments, and relate these accomplishments to past performance or industry norms. Be sure to mention obstacles overcome, innovations or discoveries made, and outcomes:

Climate change is a pressing topic of political and policy debate worldwide. To guarantee that global climate change is properly understood and addressed, the United Nations commissioned the Intergovernmental Panel on Climate Change (IPCC) to objectively assess studies and research from the scientific community. The IPCC relies on the solid science and technical skills of talented technologists to digest the enormous amount of data generated in climate research.

Engility’s Aparna Radhakrishnan is one of the top performers, providing tools and analytic frameworks to help scientists explore the complex problem of climate change. In 2013, Aparna gave her client, the National Oceanic and Atmospheric Administration’s (NOAA’s) Geophysical Fluid Dynamics Laboratory (GFDL), a voice with new audiences. Her work porting, extending, and validating statistical downscaling algorithms on climate data and communicating her results at conferences greatly increased GFDL's visibility and helps preserve its reputation by providing vetted downscaled product.

Aparna’s proficiency in deploying computational statistical methods makes her one of Engility’s prime resources available to NOAA. In the last year alone, Aparna gave talks at the National Climate Predictions and Projections workshop, the American Geophysical Union, and the ExArch workshop for the Nation Centre for Atmospheric Science.

Aparna is at the forefront of innovation in climate modeling – providing deep computational insight into GFDL data for government researchers and end consumers making business decisions from downscaled GFDL data.

Climate Modeling and Big Data Publishing: Aparna prepares data for the IPCC. She is involved in metadata management services and database schema design for MySQL relational databases as part of the team for performance tuning and improved metadata access. She managed and tracked metadata collection on 500 climate variables, interacting with scientists of various domains. She also worked on data size estimation (petabytes) for IPCC. She has been instrumental in establishing data standards for statistical downscaling and National Multi-Model Ensemble projects.

Web Development and Quality Control Tools: Aparna developed and maintained a Model Development Database Interface at GFDL for secure access to experiment data and metadata for quality control and more, helping the lab/scientists with model development and model intercomparison projects.

Dealing with Data: Aparna designed and implemented tools to generate metadata catalogs for data visualization and distributed data access (OPeNDAP). She developed automated workflow deployment for seamless data transfer and developed automated data processing/transfer tools. She also developed and deployed user-developed climate analytics as a web service to promote a unified approach to inter-comparison of different climate models in the Earth System Grid Federation. For climate analytics on global data archives, she helped design and implement a template-based approach to facilitate climate analyses.

Aparna's statistical downscaling work solves another a big data problem. GFDL datasets start as gigabytes but can grow orders of magnitude bigger when statistically downscaled. Aparna has been building a framework for automating much of the work that needs to be done to prepare models and downscaled data for these evaluations.

Aparna’s efforts provide scientists with the analytic tools they need to create better models, analyze relevant results, and better estimate likely outcomes that can reach policy makers more quickly and allow them to make informed decisions on the future of our planet.

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Provide a brief (up to 125 words) biography about the nominee:

Aparna Radhakrishnan joined Engility in August 2009 and is a remote work success story. She lives in Indiana and supports her NOAA customer in Princeton, NJ. Currently, she works with the Modeling Services Team developing web services in support of lab milestones, several of which she has attained successfully. She has been focused on interactive science visualization projects that include climate analytics on big data coupled with Live Access Servers, fortran-python based CMOR, JavaScript-JSP-mySQL based MDBI (Model Development Database Interface), and CDAT-python based implementations of scientific file manipulations for the end-users/scientists. Aparna is now focused on support of inter-lab partnerships, solutions to climate analysis on big data and technology transfer, and validation work for statistical downscaling of climate data.