Hridesh Rajan is the Dean of the School of Science and Engineering at Tulane, overseeing a wide range of departments and programs. Before joining Tulane, he was the Kingland Professor at Iowa State University, where he served as the Department Chair of Computer Science. He also held the role of founding Professor-in-Charge of Data Science Programs from 2017 to 2019, during which he established the annual Midwest Big Data Summer School and led several key data science educational initiatives.

As an academic, Rajan is well-regarded for his contributions to Software Engineering and Programming Languages. He is the creator of the Ptolemy programming language, which improved modular reasoning about crosscutting concerns, and the Boa programming language, which simplifies data-driven software engineering. His research has been recognized with numerous awards, including the NSF CAREER award, the LAS Early Achievement in Research Award, and the Facebook Probability and Programming Award. Rajan’s academic influence extends through his editorial work with IEEE Transactions on Software Engineering and ACM SIGSOFT Software Engineering Notes, and his advisory role with the Proceedings of the ACM on Programming Languages.

Rajan’s leadership at Iowa State University saw significant growth in the computer science department, with increases in student enrollment, faculty numbers, research funding, and philanthropic support. He spearheaded efforts in diversity and inclusion, resulting in a notable increase in female enrollment. He also led the development of new academic programs, including the M.S. degree in Artificial Intelligence and the B.S. degree in Data Science.

Educated at the University of Virginia, Rajan holds a Ph.D. and an MS in Computer Science. He earned his B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Varanasi. His professional journey includes a tenure as a Member of Technical Staff at Bell Labs, Lucent Technologies in Bangalore, India.

Rajan is a Fellow of the American Association for the Advancement of Science (AAAS), a Fulbright Scholar, and an ACM Distinguished Scientist. His ongoing research continues to push the boundaries of software engineering and programming languages, especially in making AI and ML-enabled systems more reliable and trustworthy.

Research Interests

Software Engineering and Programming Languages

Selected Books and Publications

• An Experiential Introduction to Principles of Programming Languages, MIT Press, May 2022, 304 pp., ISBN 9780262045452.
• On Decomposing a Deep Neural Network into Modules, ESEC/FSE’2020.
• Fairify: Fairness Verification of Neural Networks. ICSE’2023.

Selected Awards and Recognitions

• 2022 ISU Award for Early Achievement in Departmental Leadership
• 2020 American Association for the Advancement of Science (AAAS) Fellow
• 2020 Facebook Probability and Programming Award
• 2018-19 Fulbright U.S. Scholar
• 2017 ACM Distinguished Scientist
• 2009 US National Science Foundation (NSF) CAREER Award
• Various best paper and distinguished paper awards

Recent Service Roles

• General Chair, SPLASH 2021, the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity
• General Chair, SPLASH 2020, the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity
• Program Committee, 47th International Conference on Software Engineering (ICSE 2025)
• Program Committee, 46th International Conference on Software Engineering (ICSE 2024)
• Program Committee, 39th IEEE/ACM International Conference on Automated Software Engineering (ASE 2024)

Teaching

Programming Languages  

Object-oriented Analysis and Design

Advanced Topics in Programming Languages: Type Systems 

Selected Publications

Shibbir Ahmed, Hongyang Gao, and Hridesh Rajan, "Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment," ICSE’2024: The 46th International Conference on Software Engineering, April, 2024.

David OBrien, Sumon Biswas, Sayem Mohammad Imtiaz, Rabe Abdalkareem, Emad Shihab, and Hridesh Rajan, "Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot," ICSE’2024: The 46th International Conference on Software Engineering, April, 2024.

David OBrien, Robert Dyer, Tien Nguyen, and Hridesh Rajan, "Data-Driven Evidence-Based Syntactic Sugar Design," ICSE’2024: The 46th International Conference on Software Engineering, April, 2024.

Ali Ghanbari, Deepak-George Thomas, Muhammad Arbab Arshad, and Hridesh Rajan, "Mutation-based Fault Localization of Deep Neural Networks," ASE’2023: 38th IEEE/ACM International Conference on Automated Software Engineering, September, 2023.

Samantha Syeda Khairunnesa, Shibbir Ahmed, Sayem Mohammad Imtiaz, Hridesh Rajan, and Gary T. Leavens, "What Kinds of Contracts Do ML APIs Need?," Empirical Software Engineering, March, 2023.

Shibbir Ahmed, Sayem Mohammad Imtiaz, Samantha Syeda Khairunnesa, Breno Dantas Cruz, and Hridesh Rajan, "Design by Contract for Deep Learning APIs," ESEC/FSE’2023: The 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, December, 2023.

Giang Nguyen, Sumon Biswas, and Hridesh Rajan, "Fix Fairness, Don’t Ruin Accuracy: Performance Aware Fairness Repair using AutoML," ESEC/FSE’2023: The 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, December, 2023.

Sumon Biswas and Hridesh Rajan, "Fairify: Fairness Verification of Neural Networks," ICSE’23: The 45th International Conference on Software Engineering, May, 2023.

Sayem Mohammad Imtiaz, Fraol Batole, Astha Singh, Rangeet Pan, Breno Dantas Cruz, and Hridesh Rajan, "Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement," ICSE’23: The 45th International Conference on Software Engineering, May, 2023.

Usman Gohar, Sumon Biswas, and Hridesh Rajan, "Towards Understanding Fairness and its Composition in Ensemble Machine Learning," ICSE’23: The 45th International Conference on Software Engineering, May, 2023.

David OBrien, Sumon Biswas, Sayem Mohammad Imtiaz, Rabe Abdalkareem, Emad Shihab, and Hridesh Rajan, "23 Shades of Self-Admitted Technical Debt: An Empirical Study on Machine Learning Software," Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, November, 2022.
 

Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, and Hongyang Gao, "A Global Convergence Theory for Deep ReLU Implicit Networks via Over-Parameterization," ICLR’22: The 10th International Conference on Learning Representations, April, 2022.

Sumon Biswas, Mohammad Wardat, and Hridesh Rajan, "The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large," ICSE’22: The 44th International Conference on Software Engineering, May, 2022.

Rangeet Pan and Hridesh Rajan, "Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules," ICSE’22: The 44th International Conference on Software Engineering, May, 2022.

Mohammad Wardat, Breno Dantas Cruz, Wei Le, and Hridesh Rajan, "DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs," ICSE’22: The 44th International Conference on Software Engineering, May, 2022.

Giang Nguyen, Johir Islam, Rangeet Pan, and Hridesh Rajan, "Manas: Mining Software Repositories to Assist AutoML," ICSE’22: The 44th International Conference on Software Engineering, May, 2022.

Menglu Yu, Bo Ji, Hridesh Rajan, and Jia Liu, "On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenan GPU Clusters with Communication Contention," Proc. ACM MobiHoc, October, 2022.
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Shibbir Ahmed, Md Johirul Islam, and Hridesh Rajan, "Semantics and Anomaly Preserving Sampling Strategy for Large-Scale Time Series Data," ACM/IMS Transactions on Data Science, January, 2022.

Sumon Biswas and Hridesh Rajan, "Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline," ESEC/FSE’2021: The 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, August, 2021.

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.

Hamid Bagheri, Andrew J. Severin, and Hridesh Rajan, "Detecting and correcting misclassified sequences in the large-scale public databases ," Oxford Bioinformatics, August, 2020.

Dr. Zhang's research interests lie at the intersection of Earth and environmental sciences, focusing on the biogeochemical cycling of global contaminants. He combines mechanistic insight and observational data to develop Earth System Models for different environmental compartments and their interfaces. His studies elucidate key environmental processes, establish comprehensive budgets, assess the impact of human activities on environmental quality, and project the influences of climate change in both historical and future contexts. Current projects target mercury (Hg), (micro)plastics, PFAS, antibiotics, radionuclides, and other legacy and emerging pollutants. For more information visit https://ebmg.tulane.edu.

Selected Publications

Sun et al. 2024. Calcite carbonate sinks low-density plastic debris in open oceans. Nature Communications 15 (1), 4837.

Yuan et al. 2024. Potential decoupling of CO2 and Hg uptake process by global vegetation in the 21st century. Nature Communications 15 (1), 4490.

Fu et al. 2023. Modeling atmospheric microplastic cycle by GEOS-Chem: An optimized estimation by a global dataset suggests likely 50 times lower ocean emissions. One Earth 6, 705-714.

Wu and Zhang, 2023. Toward a Global Model of Methylmercury Biomagnification in Marine Food Webs: Trophic Dynamics and Implications for Human Exposure. Environmental Science & Technology 57(16) 6563-6572.

Zhang et al. 2023. An updated global mercury budget from a coupled atmosphere-land-ocean model: 40% more re-emissions buffer the effect of primary emission reductions. One Earth 6(3), 316-325.

Zhang et al. 2023. Plastic Waste Discharge to the Global Ocean Constrained by Seawater Observations. Nature Communications 14(1) 1372.

Wang et al. 2023. Climate-Driven Changes of Global Marine Mercury Cycles in 2100. PNAS 120(2) e2202488120.

Song et al. 2022. Modeling Mercury Isotopic Fractionation in the Atmosphere. Environmental Pollution 307,119588.

Peng et al. 2021. Plastic waste release caused by COVID-19 and its fate in the global ocean. PNAS 118(47) e2111530118.

Zhang et al. 2021. Global Health Effects of Future Atmospheric Mercury Emissions. Nature Communications 12, 3035.

Zhang et al. 2020. A global model for methylmercury formation and uptake at the base of marine food webs. Global Biogeochemical Cycles 34(2), e2019GB006348.

Wagner et al. 2019. A Global 3-D Ocean Model for PCBs: Benchmark Compounds for Understanding the Impacts of Global Change on Neutral Persistent Organic Pollutants. Global Biogeochemical Cycles 33(3) 469-481.

Wang et al. 2017. Trade-driven relocation of air pollution and health impacts in China. Nature Communications 8, 738.

Zhang et al. 2017. North Atlantic Deep Water formation inhibits high Arctic contamination by continental perfluorooctane sulfonate discharges. Global Biogeochemical Cycles 31(8) 1332-1343.

Zhang et al. 2016. Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions. PNAS 113(3) 526-531.

My research interests include coral reefs, anthropogenic climate change, ocean dynamics, coastal biogeochemistry, and ocean acidification.

Selected Publications

Henley B.J., McGregor H.V., King A.D., Hoegh-Guldberg O., Arzey A.K., Karoly D.J., Lough J., DeCarlo T.M., & B.K. Linsley (2024). Highest ocean heat in four centuries places Great Barrier Reef in danger. Nature 632, 320-326.

Whitaker H.V. & T.M. DeCarlo (2024). Re(de)fining Degree-Heating Week: Coral Bleaching Variability Necessitates Regional and Temporal Optimization of Global Forecast Model Stress Metrics. Coral Reefs.https://doi.org/10.1007/s00338-024-02512-w

Mantanona H.C. & T.M. DeCarlo (2023). Coral growth persistence amidst bleaching events. Limnology and Oceanography Letters 8, 734-741. https://doi.org/10.1002/lol2.10340

Chen W-H., Ren H., Chiang J.C.H., Wang Y-L., Cai-Li R-Y, Chen Y-C., Shen C-C., Taylor F.W., DeCarlo T.M., Wu C-R., Mii H-S., & X.T. Wang (2023). Increased tropical South Pacific western boundary current transport over the past century. Nature Geoscience 16, 590-596. 10.1038/s41561-023-01212-4

DeCarlo T.M., Carvalho S., Gajdzik L., Hardenstine R.S., Tanabe L.K., Villalobos R., & M.L. Berumen (2021). Patterns, drivers, and ecological implications of upwelling in coral reef habitats of the southern Red Sea. Journal of Geophysical Research – Oceans 126, e2020JC016493.

DeCarlo T.M. (2020). Treating coral bleaching as weather: a framework to validate and optimize prediction skill. PeerJ8, e9449.

DeCarlo T.M., Gajdzik L., Ellis J., Coker D.J., Roberts M.B., Hammerman N.M., Pandolfi J.M., Monroe A.A. & M.L. Berumen (2020). Nutrient-supplying ocean currents modulate coral bleaching susceptibility. Science Advances 6, eabc5493.

DeCarlo T.M. & H.B. Harrison (2019). An enigmatic decoupling between heat stress and coral bleaching on the Great Barrier Reef. PeerJ 7, e7473.

DeCarlo T.M., Harrison H.B., Gajdzik L., Alaguarda D., Rodolfo-Metalpa R., D’Olivo J., Liu G., Patalwala D., & M.T. McCulloch (2019). Acclimatization of massive reef-building corals to consecutive heatwaves. Proceedings of the Royal Society B 286, 20190235.

About Professor Bankston

Victor Bankston is a Professor of Practice at Tulane University, specializing in quantum information and combinatorial designs. With a passion for exploring the intersections of these fields, Victor aims to foster a dynamic and engaging learning environment. His dedication to teaching stems from a desire to study computers as a means to understand the world more broadly, continually striving to enhance both his own knowledge and that of his students.

Research Interests

Quantum computation/information, combinatorial designs, optimization

Office

307A Stanley Thomas Hall

Teaching

Sp24, CMPS 2170/MATH 2170: Introduction to Discrete Math

Publications

Hidden Variables for Pauli Measurements (in review at Quantum Journal)

The Green Engineering Equity group focuses on developing biomaterial-based approaches to improve hematopoietic stem cell (HSC) transplantation, using sickle cell disease as a primary model system. We investigate how factors like pathology, sex, and age modify HSC function through engineered in vitro and in vivo models to inform our biomaterial design. By exploiting bone marrow physiology, our platforms aim to improve stem cell transplantation engraftment and recovery. Our ultimate goal is to develop more effective, cost-efficient procedures, creating equitable treatments for the various disorders reliant upon hematopoietic stem cell transplantation.

In tandem with our biomedical research, our educational initiatives integrate healthcare equity into engineering curricula to enhance student retention, success, and overall experience. By combining advanced technical education with an understanding of ethical and human-centered aspects of engineering, we foster a more inclusive and equitable learning environment. This approach ensures that students are not only technically proficient but also socially conscious, preparing them to tackle complex healthcare challenges and contribute meaningfully to health equity.

Selected Honors and Awards

Rising Stars in Engineering in Health Fellow (2023)
George Mason University InSPIRE Award (2023)
University of Texas at Austin Equity in Engineering Award (2023)
Society for Biomaterials Postdoc Recognition Award (2022)
Massachusetts Institute of Technology Impact Fellow (2019)
Sigma Xi Grant-In-Aid of Research Recipient (2016)       
NSF Graduate Research Fellow (2012 - 2015)  

Selected Publications

Google Scholar: tinyurl.com/4f6d67t6