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Rajesh Kalyanam

Rajesh Kalyanam's Profile Photo

Senior Research Scientist

Rajesh Kalyanam is a Senior Research Scientist in the Scientific Solutions Group in RCAC. He leads and works on several federally funded projects that are at the intersection of advanced computing and science and engineering. Rajesh also has over 15 years of experience as a full stack application developer and has worked on science gateway projects for a variety of domains including geosciences, cybersecurity, communication, and anthropology. Since 2016, Rajesh has worked on over 20 grant proposals and currently serves as CoPI on five NSF-funded grants including Anvil, a Category I capacity system funded by the NSF in 2020 and operated by RCAC. He is also the Software Architect for GeoEDF, a plug-n-play data framework that simplifies the data wrangling challenges in geospatial research workflows.

Rajesh's graduate research was on the use of automated reasoning for planning tasks. His thesis focused on the application of an interactive theorem prover to the task of interactively verifying state invariant properties and recursive program-like generalized plans for automated planning domains. As part of this research he devised various performance improvements to the inference engine that made it possible to verify the state invariants in two benchmark domains with no human intervention.


  • B.Eng., Computer Science and Engineering, National Institute of Technology, Karnataka, India
  • Ph.D., Computer Engineering, Purdue University


  • NSF ACSS: Category I: Anvil - A National Composable Advanced Computational Resource for the Future of Science and Engineering (CoPI, $22.5M, 10/2020 – 9/2026)
  • NSF CCRI:ENS: Collaborative Research: Open Computer System Usage Repository and Analytics Engine (Co-PI, $1,183,897, 10/2020 – 9/2023)
  • NSF CSSI: Elements: Data: U-Cube: A Cyberinfrastructure for Unified and Ubiquitous Urban Canopy Parameterization (Co-PI, $600,000, 01/2019 – 12/2022)
  • NSF DGE: Collaborative Research: CHEESE: Cyber Human Ecosystem of Engaged Security Education (Co-PI, $350,000, 07/2018 – 06/2022)
  • NSF III: Medium: Collaborative Research: Deep Generative Modeling for Urban and Archaeological Recovery (Co-PI, $1M, 10/2021 – 09/2024)
  • NSF CSSI: Elements: Science-i Cyberinfrastructure for Forest Ecosystem Research (Co-PI, $588,985, 09/2023 - 08/2026)


  • 2017, 2020, 2023 Bravo Award, Purdue University recognizing employee achievements and excellence
  • 2017 Science Gateways Community Institute Young Professional of the Year award
  • 2019 Faculty Best Paper award (joint with Professor Sorin Matei), International Communication Association


  • Guest Editor, Concurrency and Computation: Practice and Experience, Special Issue on Science Gateways, 2020
  • Paper Tracks Co-Chair, Gateways 2018, Gateways 2019 conferences
  • Mentor Science Gateways Community Institute Hackathon, 2018
  • Mentor Anvil REU Program, 2023

Selected Publications

  • R. Kalyanam, L. Zhao, C. X. Song, V. Merwade, J. Jin, U. Baldos, J. Smith. GeoEDF: An Extensible Geospatial Data Framework for FAIR Science. In Practice and Experience in Advanced Research Computing (PEARC ’20), July 27–31, 2020. ACM, New York, NY, USA.
  • Kalyanam, R., Zhao, L., Song, C.X., Biehl, L., Kearney, D., Kim, I.L., Shin, J., Villoria, N. and Merwade, V. 2018, October. MyGeoHub - A Sustainable and Evolving Geospatial Science Gateway. Future Generation Computing Systems (FGCS), special issue on science gateways.
  • Kalyanam, R., Yang, B., Willis, C., Lambert, M. and Kirkpatrick, C., 2020, October. CHEESE: Cyber Human Ecosystem of Engaged Security Education. In 2020 IEEE Frontiers in Education Conference (FIE) (pp. 1-7). IEEE.
  • Matei, S., Kalyanam, R., Zhao, L. and Song, C., 2018. Social media modeling of human behavior in natural emergencies. In Proceedings of the Practice and Experience on Advanced Research Computing (pp. 1-8).
  • Bhatt, M., Kalyanam, R., Nishida, G., He, L., May, C., Niyogi, D. and Aliaga, D., 2020. Design and Deployment of Photo2Building: A Cloud-based Procedural Modeling Tool as a Service. In Practice and Experience in Advanced Research Computing (pp. 132-138).