Jaganmohan Chandrasekaran

21 papers A* 1B 1Misc 1Journal 5Unranked 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Combinatorial Approach to Synthetic Data Generation for Machine Learning.
SN Comput. Sci.
Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn
2025 A* conf
Can an LLM Find Its Way Around a Spreadsheet?
ICSE
Cho-Ting Lee, Andrew Neeser, Shengzhe Xu, Jay Katyan, Patrick Cross, Sharanya Pathakota, Marigold Norman, John Simeone, Jaganmohan Chandrasekaran, Naren Ramakrishnan
2025 — conf
Data Frequency Coverage Impact on AI Performance.
ICSTW
Erin Lanus, Brian Lee, Jaganmohan Chandrasekaran, Laura J. Freeman, M. S. Raunak, Raghu N. Kacker, D. Richard Kuhn
2025 — conf
Evaluating Large Language Model Robustness using Combinatorial Testing.
ICSTW
Jaganmohan Chandrasekaran, Ankita Ramjibhai Patel, Erin Lanus, Laura J. Freeman
2024 B conf
A Combinatorial Approach to Hyperparameter Optimization.
CAIN
Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn
2024 J jnl
Assured Autonomy Through Combinatorial Methods.
Computer
D. Richard Kuhn, M. S. Raunak, Raghu N. Kacker, Jaganmohan Chandrasekaran, Erin Lanus, Tyler Cody, Laura J. Freeman
2024 J jnl
Leveraging Combinatorial Coverage in the Machine Learning Product Lifecycle.
Computer
Jaganmohan Chandrasekaran, Erin Lanus, Tyler Cody, Laura J. Freeman, Raghu N. Kacker, M. S. Raunak, D. Richard Kuhn
2023 J jnl
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning.
CoRR
Padmaksha Roy, Jaganmohan Chandrasekaran, Erin Lanus, Laura J. Freeman, Jeremy Werner
2023 — conf
Synthetic Data Generation Using Combinatorial Testing and Variational Autoencoder.
ICSTW
Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn
2023 J jnl
Test & Evaluation Best Practices for Machine Learning-Enabled Systems.
CoRR
Jaganmohan Chandrasekaran, Tyler Cody, Nicola McCarthy, Erin Lanus, Laura J. Freeman
2022 — conf
A Combinatorial Approach to Fairness Testing of Machine Learning Models.
ICST Workshops
Ankita Ramjibhai Patel, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn
2022 — conf
DeltaExplainer: A Software Debugging Approach to Generating Counterfactual Explanations.
AITest
Sunny Shree, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn
2022 Misc conf
Enabling AI Adoption through Assurance.
FLAIRS
Jaganmohan Chandrasekaran, Feras A. Batarseh, Laura J. Freeman, Raghu Kacker, M. S. Raunak, Rick Kuhn
2021 — conf
A Combinatorial Approach to Explaining Image Classifiers.
ICST Workshops
Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn
2021 — conf
A Combinatorial Approach to Testing Deep Neural Network-based Autonomous Driving Systems.
ICST Workshops
Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn
2021 — conf
Evaluation of T-Way Testing of DNNs in Autonomous Driving Systems.
AITest
Jaganmohan Chandrasekaran, Ankita Ramjibhai Patel, Yu Lei, Raghu Kacker, D. Richard Kuhn
2020 — conf
Effectiveness of dataset reduction in testing machine learning algorithms.
AITest
Jaganmohan Chandrasekaran, Huadong Feng, Yu Lei, Raghu Kacker, D. Richard Kuhn
2018 — conf
A Method-Level Test Generation Framework for Debugging Big Data Applications.
IEEE BigData
Huadong Feng, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn
2017 — conf
Applying Combinatorial Testing to Data Mining Algorithms.
ICST Workshops
Jaganmohan Chandrasekaran, Huadong Feng, Yu Lei, D. Richard Kuhn, Raghu Kacker
2016 — conf
Evaluating the Effectiveness of BEN in Localizing Different Types of Software Fault.
ICST Workshops
Jaganmohan Chandrasekaran, Laleh S. Ghandehari, Yu Lei, Raghu Kacker, D. Richard Kuhn
2015 — conf
BEN: A combinatorial testing-based fault localization tool.
ICST Workshops
Laleh Shikh Gholamhossein Ghandehari, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn