Registered user since Wed 1 Oct 2014
Hridesh Rajan is a Professor and Chair of Computer Science at Iowa State University, where he has been since 2005. Professor Rajan earned his MS and Ph.D. from the University of Virginia in 2004 and 2005 respectively. Professor Rajan’s recent research and educational activities are aimed at decreasing the barrier to entry to data-driven sciences to broaden participation. His work on the Boa project is aimed at the invention and refinement of programming languages and cyberinfrastructures that democratize data-driven science & engineering, including software engineering. His work on the Midwest Big Data Summer School is experimenting with broadly accessible data science curricula. Professor Rajan was the founding general chair of the Midwest Big Data Summer School. Professor Rajan’s research interests also include programming language design and implementation, and software engineering. He leads two research projects: Panini, whose goals are to enable modular reasoning about concurrent programs, and Boa that was established in Summer 2012 as an end-to-end infrastructure for analyzing large-scale software repositories and other open data sets. Professor Rajan is the director of the Laboratory for Software Design at Iowa State University, director of graduate admissions and recruitment for the Department of Computer Science. He serves as the department chair of the Department of Computer Science and served as the Professor-In-Charge of the Data Science education programs at Iowa State University from 2017-2019, and chair of the information technology committee for the university from 2015-2019. Professor Rajan served on the steering committee of the Midwest Big Data Hub, a consortium of universities in the Midwest region of the United States focused on promoting data science activities. Professor Rajan is a recipient of the National Science Foundation CAREER award in 2009, LAS Award for Early Achievement in Research in 2010, a Big-12 Fellowship in 2012. He is a 2018-19 Fulbright U.S. Scholar, a AAAS fellow, a distinguished member of the ACM, and a member of IEEE. He is also the inaugural holder of the Kingland Professorship in the Department of Computer Science.
Mining Software Repositories
- Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement
- Towards Understanding Fairness and its Composition in Ensemble Machine Learning
- Artifact for the paper - "Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement"
- Fairify: Fairness Verification of Neural Networks
- Replication Package of the ICSE 2023 Paper Entitled "Fairify: Fairness Verification of Neural Networks"
- Artifact for the ICSE 2023 Paper Entitled "Towards Understanding Fairness and its Composition in Ensemble Machine Learning"
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