• IEEE.org
  • IEEE CS Standards
  • Career Center
  • About Us
  • Subscribe to Newsletter

0

IEEE-CS_LogoTM-orange
  • MEMBERSHIP
  • CONFERENCES
  • PUBLICATIONS
  • EDUCATION & CAREER
  • VOLUNTEER
  • ABOUT
  • Join Us
IEEE-CS_LogoTM-orange

0

IEEE Computer Society Logo
Sign up for our newsletter
IEEE COMPUTER SOCIETY
About UsBoard of GovernorsNewslettersPress RoomIEEE Support CenterContact Us
COMPUTING RESOURCES
Career CenterCourses & CertificationsWebinarsPodcastsTech NewsMembership
BUSINESS SOLUTIONS
Corporate PartnershipsConference Sponsorships & ExhibitsAdvertisingRecruitingDigital Library Institutional Subscriptions
DIGITAL LIBRARY
MagazinesJournalsConference ProceedingsVideo LibraryLibrarian Resources
COMMUNITY RESOURCES
GovernanceConference OrganizersAuthorsChaptersCommunities
POLICIES
PrivacyAccessibility StatementIEEE Nondiscrimination PolicyIEEE Ethics ReportingXML Sitemap

Copyright 2026 IEEE - All rights reserved. A public charity, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

  • Home
  • /Profiles
  • Home
  • /Profiles

Laxmikant V. Kale

Award Recipient

Featured ImageLaxmikant "Sanjay" Kale is the director of the Parallel Programming Laboratory and a Professor of Computer Science at the University of Illinois at Urbana-Champaign. Prof. Kale has been working on various aspects of parallel computing since 1983. His focus is on enhancing performance and productivity via adaptive runtime systems, which support automatic dynamic load balancing, fault tolerance, and power management. He developed the "migratable objects" parallel programming model and its implementation in the Charm++ parallel programming system. In addition to the traditional HPC platforms, the adaptivity of this model is well-suited for cloud environments. Underlying his work is the belief that only interdisciplinary research involving multiple applications, in science and engineering as well outside of it, can bring back well-honed abstractions into computer science that will have a long-term impact on the state-of-art. His collaborations include the widely used Gordon-Bell award winning (SC'2002) biomolecular simulation program NAMD, as well as collaborations on developing computational cosmology code ChaNGA, quantum chemistry (OpenAtom),  agent based Simulation (EpiSimdemics), weather and climate codes, rocket simulation, space-time meshes, and other unstructured mesh applications. He takes pride in his group's success in distributing and supporting software embodying his research ideas, including Charm++, Adaptive MPI and associated tools. His team won the HPC Challenge award at Supercomputing 2011, for their entry based on Charm++.

Kale received a B.Tech degree in Electronics Engineering from Benares Hindu University in 1977, and a M.E. in Computer Science from Indian Institute of Science, Bangalore, in 1979.  He received a Ph.D. in computer science from State University of New York, Stony Brook, in 1985.

He worked as a scientist at the Tata Institute of Fundamental Research from 1979 to 1981. He joined the faculty of the University of Illinois at Urbana-Champaign in 1985. Prof. Kale is a fellow of the IEEE.

Awards

2012 Sidney Fernbach Award
“For outstanding contributions to the development of widely used parallel software for large biomolecular systems simulation.”
Co-recipient with Klaus Schulten
Learn more about the Sidney Fernbach Award

LATEST NEWS
Fueling Innovation: Highlights from the Astro Code 2026 Hackathon in Jordan
Fueling Innovation: Highlights from the Astro Code 2026 Hackathon in Jordan
Episode 8 | How to Build a Career That Actually Matters to You
Episode 8 | How to Build a Career That Actually Matters to You
Computing’s Top 30: Vishnupriya S. Devarajulu
Computing’s Top 30: Vishnupriya S. Devarajulu
When AI Writes More Code, Safety Becomes the Bottleneck:  A Refactoring Playbook
When AI Writes More Code, Safety Becomes the Bottleneck: A Refactoring Playbook
Why Most AI Failures Are Systems Failures, Not Model Failures
Why Most AI Failures Are Systems Failures, Not Model Failures
Read Next

Fueling Innovation: Highlights from the Astro Code 2026 Hackathon in Jordan

Episode 8 | How to Build a Career That Actually Matters to You

Computing’s Top 30: Vishnupriya S. Devarajulu

When AI Writes More Code, Safety Becomes the Bottleneck: A Refactoring Playbook

Why Most AI Failures Are Systems Failures, Not Model Failures

Software Engineers: Have You Outgrown Your Role?

Computing’s Top 30: Oluwakemi Temitope Olayinka

Agentic AI in OT: New Capabilities, Emerging Risks, and Governance Challenges

Get the latest news and technology trends for computing professionals with ComputingEdge
Sign up for our newsletter