Data-Driven Approaches for Diagnosis of Incipient Faults in DC Motors. - Sai Munikoti; Laya Das; Balasubramaniam Natarajan; Babji Srinivasan (IEEE Trans. Ind. Informatics, 2019)

Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks. - Mohammad Abujubbeh; Sai Munikoti; Balasubramaniam Natarajan (CoRR, 2020)

Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System. - Sai Munikoti; Kumarsinh Jhala; Kexing Lai; Balasubramaniam Natarajan (CoRR, 2020)

Probabilistic Voltage Sensitivity Analysis (PVSA) to Quantify Impact of High PV Penetration on Unbalanced Distribution System. - Sai Munikoti; Balasubramaniam Natarajan; Kumarsinh Jhala; Kexing Lai (CoRR, 2020)

Spatio-Temporal Probabilistic Voltage Sensitivity Analysis (ST-PVSA)-A Novel Framework for Hosting Capacity Analysis. - Sai Munikoti; Mohammad Abujubbeh; Kumarsinh Jhala; Balasubramaniam Natarajan (CoRR, 2020)

Graph neural network based approximation of Node Resiliency in complex networks. - Sai Munikoti; Laya Das; Balasubramaniam Natarajan (CoRR, 2020)

Bayesian Inductive Learner for Graph Resiliency under uncertainty. - Sai Munikoti; Balasubramaniam Natarajan (CoRR, 2020)

Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks. - Sai Munikoti; Laya Das; Balasubramaniam Natarajan (SMC, 2021)

An Information Theoretic approach to identify Dominant Voltage Influencers for Unbalanced Distribution Systems. - Sai Munikoti; Mohammad Abujubbeh; Kumarsinh Jhala; Balasubramaniam Natarajan (CoRR, 2021)

Robustness assessment of Hetero-functional graph theory based model of interdependent urban utility networks. - Sai Munikoti; Kexing Lai; Balasubramaniam Natarajan (Reliab. Eng. Syst. Saf., 2021)

Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics. - Sai Munikoti; Mohammad Abujubbeh; Balasubramaniam Natarajan (IEEE Access, 2022)

Scalable graph neural network-based framework for identifying critical nodes and links in complex networks. - Sai Munikoti; Laya Das; Balasubramaniam Natarajan (Neurocomputing, 2022)

Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids. - Shweta Dahale; Sai Munikoti; Balasubramaniam Natarajan; Rui Yang (ISGT, 2023)

There is more to graphs than meets the eye: Learning universal features with self-supervision. - Laya Das; Sai Munikoti; Mahantesh Halappanavar (CoRR, 2023)

A General Framework for Uncertainty Quantification via Neural SDE-RNN. - Shweta Dahale; Sai Munikoti; Balasubramaniam Natarajan (CoRR, 2023)

SCITUNE: Aligning Large Language Models with Scientific Multimodal Instructions. - Sameera Horawalavithana; Sai Munikoti; Ian Stewart; Henry Kvinge (CoRR, 2023)

NuclearQA: A Human-Made Benchmark for Language Models for the Nuclear Domain. - Anurag Acharya 002; Sai Munikoti; Aaron Hellinger; Sara Smith; Sridevi Wagle; Sameera Horawalavithana (CoRR, 2023)

Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning. - Sai Munikoti; Anurag Acharya 002; Sridevi Wagle; Sameera Horawalavithana (CoRR, 2023)

Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science. - Sridevi Wagle; Sai Munikoti; Anurag Acharya 002; Sara Smith; Sameera Horawalavithana (CoRR, 2023)

ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science. - Sai Munikoti; Anurag Acharya 002; Sridevi Wagle; Sameera Horawalavithana (CoRR, 2023)

A general framework for quantifying aleatoric and epistemic uncertainty in graph neural networks. - Sai Munikoti; Deepesh Agarwal; Laya Das; Balasubramaniam Natarajan (Neurocomputing, 2023)

Generalist Multimodal AI: A Review of Architectures, Challenges and Opportunities. - Sai Munikoti; Ian Stewart; Sameera Horawalavithana; Henry Kvinge; Tegan Emerson; Sandra E. Thompson; Karl Pazdernik (CoRR, 2024)

RAG vs. Long Context: Examining Frontier Large Language Models for Environmental Review Document Comprehension. - Hung Phan; Anurag Acharya 002; Sarthak Chaturvedi; Shivam Sharma; Mike Parker; Dan Nally; Ali Jannesari; Karl Pazdernik; Mahantesh Halappanavar; Sai Munikoti; Sameera Horawalavithana (CoRR, 2024)

PermitQA: A Benchmark for Retrieval Augmented Generation in Wind Siting and Permitting domain. - Rounak Meyur; Hung Phan; Sridevi Wagle; Jan Strube 001; Mahantesh Halappanavar; Sameera Horawalavithana; Anurag Acharya 002; Sai Munikoti (CoRR, 2024)

Surprisingly Fragile: Assessing and Addressing Prompt Instability in Multimodal Foundation Models. - Ian Stewart; Sameera Horawalavithana; Brendan Kennedy 001; Sai Munikoti; Karl Pazdernik (CoRR, 2024)

GraMeR: Graph Meta Reinforcement learning for multi-objective influence maximization. - Sai Munikoti; Balasubramaniam Natarajan; Mahantesh Halappanavar (J. Parallel Distributed Comput., 2024)

Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications. - Sai Munikoti; Deepesh Agarwal; Laya Das; Mahantesh Halappanavar; Balasubramaniam Natarajan (IEEE Trans. Neural Networks Learn. Syst., 2024)

GNN-Based Candidate Node Predictor for Influence Maximization in Temporal Graphs. - Priyanka Gautam; Balasubramaniam Natarajan; Sai Munikoti; S. M. Ferdous; Mahantesh Halappanavar (CoRR, 2025)

Evaluating the Robustness of Dense Retrievers in Interdisciplinary Domains. - Sarthak Chaturvedi; Anurag Acharya 002; Rounak Meyur; Koby Hayashi; Sai Munikoti; Sameera Horawalavithana (CoRR, 2025)

Audit, Alignment, and Optimization of LM-Powered Subroutines with Application to Public Comment Processing. - Reilly Raab; Mike Parker; Dan Nally; Sadie Montgomery; Anastasia Bernat; Sai Munikoti; Sameera Horawalavithana (CoRR, 2025)