Professor Hridesh Rajan
Dean, School of Science and Engineering, Tulane University
Professor, Department of Computer Science
201 Lindy Claiborne Boggs Center
6823 St. Charles Avenue
New Orleans, LA 70118-5698, USA
Phone: (504) 865-5764 (work)
Email: hrajan@tulane.edu (work)

Overview

Hridesh Rajan serves as the Dean of the School of Science and Engineering at Tulane University and as a Professor in the Tulane University Department of Computer Science. Before Tulane, he was the Kingland Professor and Chair of Computer Science at Iowa State University (2019–2024) and the founding Professor-in-Charge of Data Science Programs (2017–2019).

Rajan’s research spans programming languages, software engineering, and data science. He is known for the design of the Ptolemy programming language, which advanced modular reasoning about crosscutting concerns, and for the Boa language and its infrastructure, which lowered barriers to data-driven software engineering at ultra-large scale.

His work has been recognized by the U.S. National Science Foundation with a CAREER award, by an Early Achievement in Research Award, by a Big-12 Fellowship and the Kingland Professorship, and by an Exemplary Mentor for Junior Faculty award. He is a Fellow of the AAAS, a US–UK Fulbright Scholar, and a Distinguished Member of the ACM. He also serves as a Commissioner on ABET’s Computing Accreditation Commission.

Rajan has served on the editorial boards of IEEE Transactions on Software Engineering and ACM SIGSOFT Software Engineering Notes, and currently serves on the advisory board of Proceedings of the ACM on Programming Languages (PACMPL) and on the steering committee of the ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity (SPLASH).

Guided by a collaborative, outcomes-oriented leadership style, he focuses on building high-performing teams, launching programs that meet national needs, and creating partnerships that translate research into societal impact. At Tulane, he is building an interdisciplinary-first, translational, School of Science and Engineering focused on Better Lives.

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Selected Books and Publications

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  • One of my long-term project has been to develop a new pedagogy and a textbook draft to teach programming languages and functional programming to students who start in Computer Science programs that teach an imperative language such as Java. This textbook appeared as: Hridesh Rajan, An Experiential Introduction to Principles of Programming Languages, MIT Press, Cambridge, MA, pp. 304, May 2022.

  • Hridesh Rajan and Gary T. Leavens, “Ptolemy: A Language with Quantified, Typed Events,” ECOOP ’08: 22nd European Conference on Object-Oriented Programming, July, 2008. This work addressed the debate on separating crosscutting concerns while preserving modular reasoning.

  • Robert Dyer, Hoan Anh Nguyen, Hridesh Rajan, and Tien N. Nguyen, “Boa: A Language and Infrastructure for Analyzing Ultra-Large-Scale Software Repositories,” 35th International Conference on Software Engineering, May, 2013. Boa was the first cyberinfrastructure for big data-driven discovery in software engineering.

  • Md Johirul Islam, Giang Nguyen, Rangeet Pan, and Hridesh Rajan, “A Comprehensive Study on Deep Learning Bug Characteristics,” ESEC/FSE’19: The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), August, 2019. This work provided the first rigorous taxonomy of defects and repairs in neural-network code.

  • Mohammad Wardat, Wei Le, and Hridesh Rajan, “DeepLocalize: Fault Localization for Deep Neural Networks,” ICSE’21: The 43nd International Conference on Software Engineering, May, 2021. DeepLocalize was the first approach for bug localization in deep learning models.

  • Rangeet Pan and Hridesh Rajan, “On Decomposing a Deep Neural Network into Modules,” ESEC/FSE’2020: The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, November, 2020. This was the first work on decomposition and modularity of deep neural networks, and started the sub-field.

Selected Awards and Honors

  • 2009 Early CAREER Award, US National Science Foundation
  • 2017 ACM Distinguished Member
  • 2018 Fulbright US-UK Scholar
  • 2020 AAAS Fellow

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Selected Service Roles

Contact me

You can contact me using either of the e-mail addresses below. When writing, please substitute firstname with hridesh.