Recommending Temporally Relevant News Content from Implicit Feedback Data. - Nikhil Muralidhar; Huzefa Rangwala; Eui-Hong Sam Han (ICTAI, 2015)

Incorporating Prior Domain Knowledge into Deep Neural Networks. - Nikhil Muralidhar; Mohammad Raihanul Islam; Manish Marwah; Anuj Karpatne; Naren Ramakrishnan (IEEE BigData, 2018)

illiad: InteLLigent Invariant and Anomaly Detection in Cyber-Physical Systems. - Nikhil Muralidhar; Chen Wang 044; Nathan Self; Marjan Momtazpour; Kiyoshi Nakayama; Ratnesh Sharma; Naren Ramakrishnan (ACM Trans. Intell. Syst. Technol., 2018)

Multivariate Long-Term State Forecasting in Cyber-Physical Systems: A Sequence to Sequence Approach. - Nikhil Muralidhar; Sathappan Muthiah; Kiyoshi Nakayama; Ratnesh Sharma; Naren Ramakrishnan (IEEE BigData, 2019)

Detection of False Data Injection Attacks in Cyber-Physical Systems using Dynamic Invariants. - Kiyoshi Nakayama; Nikhil Muralidhar; Chenrui Jin; Ratnesh Sharma (ICMLA, 2019)

DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems. - Nikhil Muralidhar; Sathappan Muthiah; Naren Ramakrishnan (IJCAI, 2019)

Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids. - Nikhil Muralidhar; Jie Bu; Ze Cao; Long He; Naren Ramakrishnan; Danesh K. Tafti; Anuj Karpatne (CoRR, 2019)

PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly. - Nikhil Muralidhar; Jie Bu; Ze Cao; Long He; Naren Ramakrishnan; Danesh K. Tafti; Anuj Karpatne (SDM, 2020)

Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems. - Nikhil Muralidhar; Jie Bu; Ze Cao; Long He; Naren Ramakrishnan; Danesh K. Tafti; Anuj Karpatne (Big Data, 2020)

Cut-n-Reveal: Time Series Segmentations with Explanations. - Nikhil Muralidhar; Anika Tabassum; Liangzhe Chen; Supriya Chinthavali; Naren Ramakrishnan; B. Aditya Prakash (ACM Trans. Intell. Syst. Technol., 2020)

Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. - Alexander Rodríguez; Nikhil Muralidhar; Bijaya Adhikari; Anika Tabassum; Naren Ramakrishnan; B. Aditya Prakash (AAAI, 2021)

Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. - Nikhil Muralidhar; Abdullah Zubair; Nathanael R. Weidler; Ryan M. Gerdes; Naren Ramakrishnan (HOST, 2021)

PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. - Nikhil Muralidhar; Jie Bu; Ze Cao; Neil Raj; Naren Ramakrishnan; Danesh K. Tafti; Anuj Karpatne (ICDM, 2021)

Using AntiPatterns to avoid MLOps Mistakes. - Nikhil Muralidhar; Sathappan Muthiah; Patrick Butler; Manish Jain; Yu Yu; Katy Burne; Weipeng Li; David Jones; Prakash Arunachalam; Hays 'Skip' McCormick; Naren Ramakrishnan (CoRR, 2021)

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning. - Anika Tabassum; Nikhil Muralidhar; Ramakrishnan Kannan; Srikanth Allu (IEEE Big Data, 2022)

Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. - Gopikrishna Rathinavel; Nikhil Muralidhar; Timothy J. O'Shea; Naren Ramakrishnan (ICDM, 2022)

Efficient Generative Wireless Anomaly Detection for Next Generation Networks. - Gopikrishna Rathinavel; Nikhil Muralidhar; Naren Ramakrishnan; Timothy J. O'Shea (MILCOM, 2022)

Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic. - Mandar Sharma; Nikhil Muralidhar; Naren Ramakrishnan (CoRR, 2022)

Science Guided Machine Learning: Incorporating Scientific Domain Knowledge for Learning Under Data Paucity and Noisy Contexts. - Nikhil Muralidhar (2022)

Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency. - Mandar Sharma; Nikhil Muralidhar; Naren Ramakrishnan (ACL (1), 2023)

ML-Assisted Optimization of Securities Lending. - Abhinav Prasad; Prakash Arunachalam; Ali Motamedi; Ranjeeta Bhattacharya; Beibei Liu; Hays McCormick; Shengzhe Xu; Nikhil Muralidhar; Naren Ramakrishnan (ICAIF, 2023)

Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. - Bharat Srikishan; Anika Tabassum; Srikanth Allu; Ramakrishnan Kannan; Nikhil Muralidhar (AAAI, 2024)

Counter Data Paucity through Adversarial Invariance Encoding: A Case Study on Modeling Battery Thermal Runaway. - Anika Tabassum; Srikanth Allu; Ramakrishnan Kannan; Nikhil Muralidhar (IEEE Big Data, 2024)

Laying Anchors: Semantically Priming Numerals in Language Modeling. - Mandar Sharma; Rutuja Murlidhar Taware; Pravesh Koirala; Nikhil Muralidhar; Naren Ramakrishnan (NAACL-HLT (Findings), 2024)

NMformer: A Transformer for Noisy Modulation Classification in Wireless Communication. - Atik Faysal; Mohammad Rostami; Reihaneh Gh. Roshan; Huaxia Wang; Nikhil Muralidhar (WOCC, 2024)

Information Guided Regularization for Fine-tuning Language Models. - Mandar Sharma; Nikhil Muralidhar; Shengzhe Xu; Raquib Bin Yousuf; Naren Ramakrishnan (CoRR, 2024)

Are LLMs Naturally Good at Synthetic Tabular Data Generation? - Shengzhe Xu; Cho-Ting Lee; Mandar Sharma; Raquib Bin Yousuf; Nikhil Muralidhar; Naren Ramakrishnan (CoRR, 2024)

Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems. - Shengzhe Xu; Christo Kurisummoottil Thomas; Omar Hashash; Nikhil Muralidhar; Walid Saad; Naren Ramakrishnan (IEEE Netw., 2024)

Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout. - Bharat Srikishan; Daniel O'Malley; Mohamed Mehana; Nicholas Lubbers; Nikhil Muralidhar (ICLR, 2025)

DenoMAE2.0: Improving Denoising Masked Autoencoders by Classifying Local Patches. - Atik Faysal; Mohammad Rostami; Taha Boushine; Reihaneh Gh. Roshan; Huaxia Wang; Nikhil Muralidhar (CoRR, 2025)

Plug-and-Play AMC: Context Is King in Training-Free, Open-Set Modulation with LLMs. - Mohammad Rostami; Atik Faysal; Reihaneh Gh. Roshan; Huaxia Wang; Nikhil Muralidhar; Yu-Dong Yao (CoRR, 2025)

The Prompt is Mightier than the Example. - Shengzhe Xu; Nikhil Muralidhar; Naren Ramakrishnan (CoRR, 2025)

Can AI Validate Science? Benchmarking LLMs for Accurate Scientific Claim → Evidence Reasoning. - Shashidhar Reddy Javaji; Yupeng Cao; Haohang Li; Yangyang Yu; Nikhil Muralidhar; Zining Zhu 005 (CoRR, 2025)

DenoMAE: A Multimodal Autoencoder for Denoising Modulation Signals. - Atik Faysal; Taha Boushine; Mohammad Rostami; Reihaneh Gh. Roshan; Huaxia Wang; Nikhil Muralidhar; Avimanyu Sahoo; Yu-Dong Yao (IEEE Commun. Lett., 2025)