Jaganmohan Chandrasekaran

According to our database, Jaganmohan Chandrasekaran authored at least 14 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Test & Evaluation Best Practices for Machine Learning-Enabled Systems.

Jaganmohan Chandrasekaran, Tyler Cody, Nicola McCarthy, Erin Lanus, Laura J. Freeman

CoRR, 2023

A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning.

Padmaksha Roy, Jaganmohan Chandrasekaran, Erin Lanus, Laura J. Freeman, Jeremy Werner

CoRR, 2023

Synthetic Data Generation Using Combinatorial Testing and Variational Autoencoder.

Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn

Proceedings of the IEEE International Conference on Software Testing, Verification and Validation, ICST 2023, 2023

2022

A Combinatorial Approach to Fairness Testing of Machine Learning Models.

Ankita Ramjibhai Patel, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn

Proceedings of the 15th IEEE International Conference on Software Testing, 2022

Enabling AI Adoption through Assurance.

Jaganmohan Chandrasekaran, Feras A. Batarseh, Laura J. Freeman, Raghu Kacker, Mohammad S. Raunak, Rick Kuhn

Proceedings of the Thirty-Fifth International Florida Artificial Intelligence Research Society Conference, 2022

DeltaExplainer: A Software Debugging Approach to Generating Counterfactual Explanations.

Sunny Shree, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn

Proceedings of the IEEE International Conference On Artificial Intelligence Testing, 2022

2021

A Combinatorial Approach to Testing Deep Neural Network-based Autonomous Driving Systems.

Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the 14th IEEE International Conference on Software Testing, 2021

A Combinatorial Approach to Explaining Image Classifiers.

Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the 14th IEEE International Conference on Software Testing, 2021

Evaluation of T-Way Testing of DNNs in Autonomous Driving Systems.

Jaganmohan Chandrasekaran, Ankita Ramjibhai Patel, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the 2021 IEEE International Conference on Artificial Intelligence Testing, 2021

2020

Effectiveness of dataset reduction in testing machine learning algorithms.

Jaganmohan Chandrasekaran, Huadong Feng, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the IEEE International Conference On Artificial Intelligence Testing, 2020

2018

A Method-Level Test Generation Framework for Debugging Big Data Applications.

Huadong Feng, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Applying Combinatorial Testing to Data Mining Algorithms.

Jaganmohan Chandrasekaran, Huadong Feng, Yu Lei, D. Richard Kuhn, Raghu Kacker

Proceedings of the 2017 IEEE International Conference on Software Testing, 2017

2016

Evaluating the Effectiveness of BEN in Localizing Different Types of Software Fault.

Jaganmohan Chandrasekaran, Laleh S. Ghandehari, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the Ninth IEEE International Conference on Software Testing, 2016

2015

BEN: A combinatorial testing-based fault localization tool.

Laleh Shikh Gholamhossein Ghandehari, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn

Proceedings of the Eighth IEEE International Conference on Software Testing, 2015