Nikhil Muralidhar

50 papers A* 6A 1B 4C 1Journal 28Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DenoMAE2.0: Improving Denoising Masked Autoencoders by Classifying Local Patches for Automatic Modulation Classification. IEEE Trans. Commun. Atik Faysal, Mohammad Rostami, Taha Boushine, Reihaneh Gh. Roshan, Nikhil Muralidhar, Yu-Dong Yao, Huaxia Wang
2026	J	`jnl`	Finetune-Informed Pretraining Boosts Downstream Performance. CoRR Atik Faysal, Mohammad Rostami, Reihaneh Gh. Roshan, Nikhil Muralidhar, Huaxia Wang
2026	J	`jnl`	Semi-Supervised Masked Autoencoders: Unlocking Vision Transformer Potential with Limited Data. CoRR Atik Faysal, Mohammad Rostami, Reihaneh Gh. Roshan, Nikhil Muralidhar, Huaxia Wang
2025	J	`jnl`	Can AI Validate Science? Benchmarking LLMs for Accurate Scientific Claim → Evidence Reasoning. CoRR Shashidhar Reddy Javaji, Yupeng Cao, Haohang Li, Yangyang Yu, Nikhil Muralidhar, Zining Zhu
2025	—	`conf`	Can AI Validate Science? Benchmarking LLMs on Claim →Evidence Reasoning in AI Papers. IJCNLP-AACL (long papers) Shashidhar Reddy Javaji, Yupeng Cao, Haohang Li, Yangyang Yu, Nikhil Muralidhar, Zining Zhu
2025	J	`jnl`	DenoMAE2.0: Improving Denoising Masked Autoencoders by Classifying Local Patches. CoRR Atik Faysal, Mohammad Rostami, Taha Boushine, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar
2025	J	`jnl`	DenoMAE: A Multimodal Autoencoder for Denoising Modulation Signals. CoRR Atik Faysal, Taha Boushine, Mohammad Rostami, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar, Avimanyu Sahoo, Yu-Dong Yao
2025	J	`jnl`	DenoMAE: A Multimodal Autoencoder for Denoising Modulation Signals. IEEE Commun. Lett. Atik Faysal, Taha Boushine, Mohammad Rostami, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar, Avimanyu Sahoo, Yu-Dong Yao
2025	J	`jnl`	DiSC-AMC: Token- and Parameter-Efficient Discretized Statistics In-Context Automatic Modulation Classification. CoRR Mohammad Rostami, Atik Faysal, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar, Yu-Dong Yao
2025	B	`conf`	LLM-Modulo-Rec: Leveraging Approximate World Knowledge of LLMs to Improve eCommerce Search Ranking Under Data Paucity. IEEE Big Data Ali El Sayed, Reihaneh Gh. Roshan, Sathappan Muthiah, Nikhil Muralidhar
2025	A*	`conf`	Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout. ICLR Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar
2025	J	`jnl`	Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout. CoRR Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar
2025	J	`jnl`	Plug-and-Play AMC: Context Is King in Training-Free, Open-Set Modulation with LLMs. CoRR Mohammad Rostami, Atik Faysal, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar, Yu-Dong Yao
2025	J	`jnl`	The Prompt is Mightier than the Example. CoRR Shengzhe Xu, Nikhil Muralidhar, Naren Ramakrishnan
2024	J	`jnl`	Are LLMs Naturally Good at Synthetic Tabular Data Generation? CoRR Shengzhe Xu, Cho-Ting Lee, Mandar Sharma, Raquib Bin Yousuf, Nikhil Muralidhar, Naren Ramakrishnan
2024	B	`conf`	Counter Data Paucity through Adversarial Invariance Encoding: A Case Study on Modeling Battery Thermal Runaway. IEEE Big Data Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar
2024	J	`jnl`	Information Guided Regularization for Fine-tuning Language Models. CoRR Mandar Sharma, Nikhil Muralidhar, Shengzhe Xu, Raquib Bin Yousuf, Naren Ramakrishnan
2024	J	`jnl`	Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems. CoRR Shengzhe Xu, Christo Kurisummoottil Thomas, Omar Hashash, Nikhil Muralidhar, Walid Saad, Naren Ramakrishnan
2024	J	`jnl`	Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems. IEEE Netw. Shengzhe Xu, Christo Kurisummoottil Thomas, Omar Hashash, Nikhil Muralidhar, Walid Saad, Naren Ramakrishnan
2024	—	`conf`	Laying Anchors: Semantically Priming Numerals in Language Modeling. NAACL-HLT (Findings) Mandar Sharma, Rutuja Murlidhar Taware, Pravesh Koirala, Nikhil Muralidhar, Naren Ramakrishnan
2024	J	`jnl`	Laying Anchors: Semantically Priming Numerals in Language Modeling. CoRR Mandar Sharma, Rutuja Murlidhar Taware, Pravesh Koirala, Nikhil Muralidhar, Naren Ramakrishnan
2024	—	`conf`	NMformer: A Transformer for Noisy Modulation Classification in Wireless Communication. WOCC Atik Faysal, Mohammad Rostami, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar
2024	J	`jnl`	NMformer: A Transformer for Noisy Modulation Classification in Wireless Communication. CoRR Atik Faysal, Mohammad Rostami, Reihaneh Gh. Roshan, Huaxia Wang, Nikhil Muralidhar
2024	A*	`conf`	Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. AAAI Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar
2024	J	`jnl`	Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. CoRR Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar
2023	—	`conf`	Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency. ACL (1) Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan
2023	J	`jnl`	Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency. CoRR Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan
2023	—	`conf`	ML-Assisted Optimization of Securities Lending. ICAIF Abhinav Prasad, Prakash Arunachalam, Ali Motamedi, Ranjeeta Bhattacharya, Beibei Liu, Hays McCormick, Shengzhe Xu, Nikhil Muralidhar, Naren Ramakrishnan
2022	J	`jnl`	Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. CoRR Nikhil Muralidhar, Abdullah Zubair, Nathanael R. Weidler, Ryan M. Gerdes, Naren Ramakrishnan
2022	A*	`conf`	Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. ICDM Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy J. O'Shea, Naren Ramakrishnan
2022	J	`jnl`	Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. CoRR Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy J. O'Shea, Naren Ramakrishnan
2022	—	`conf`	Efficient Generative Wireless Anomaly Detection for Next Generation Networks. MILCOM Gopikrishna Rathinavel, Nikhil Muralidhar, Naren Ramakrishnan, Timothy J. O'Shea
2022	B	`conf`	MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning. IEEE Big Data Anika Tabassum, Nikhil Muralidhar, Ramakrishnan Kannan, Srikanth Allu
2022	J	`jnl`	Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic. CoRR Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan
2022	—	`—`	Science Guided Machine Learning: Incorporating Scientific Domain Knowledge for Learning Under Data Paucity and Noisy Contexts. Nikhil Muralidhar
2021	—	`conf`	Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. HOST Nikhil Muralidhar, Abdullah Zubair, Nathanael R. Weidler, Ryan M. Gerdes, Naren Ramakrishnan
2021	A*	`conf`	PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. ICDM Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
2021	A*	`conf`	Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. AAAI Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash
2021	J	`jnl`	Using AntiPatterns to avoid MLOps Mistakes. CoRR Nikhil Muralidhar, Sathappan Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays 'Skip' McCormick, Naren Ramakrishnan
2020	J	`jnl`	Cut-n-Reveal: Time Series Segmentations with Explanations. ACM Trans. Intell. Syst. Technol. Nikhil Muralidhar, Anika Tabassum, Liangzhe Chen, Supriya Chinthavali, Naren Ramakrishnan, B. Aditya Prakash
2020	A	`conf`	PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly. SDM Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
2020	J	`jnl`	Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems. Big Data Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
2020	J	`jnl`	Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. CoRR Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash
2019	C	`conf`	Detection of False Data Injection Attacks in Cyber-Physical Systems using Dynamic Invariants. ICMLA Kiyoshi Nakayama, Nikhil Muralidhar, Chenrui Jin, Ratnesh Sharma
2019	A*	`conf`	DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems. IJCAI Nikhil Muralidhar, Sathappan Muthiah, Naren Ramakrishnan
2019	—	`conf`	Multivariate Long-Term State Forecasting in Cyber-Physical Systems: A Sequence to Sequence Approach. IEEE BigData Nikhil Muralidhar, Sathappan Muthiah, Kiyoshi Nakayama, Ratnesh Sharma, Naren Ramakrishnan
2019	J	`jnl`	Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids. CoRR Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
2018	—	`conf`	Incorporating Prior Domain Knowledge into Deep Neural Networks. IEEE BigData Nikhil Muralidhar, Mohammad Raihanul Islam, Manish Marwah, Anuj Karpatne, Naren Ramakrishnan
2018	J	`jnl`	illiad: InteLLigent Invariant and Anomaly Detection in Cyber-Physical Systems. ACM Trans. Intell. Syst. Technol. Nikhil Muralidhar, Chen Wang, Nathan Self, Marjan Momtazpour, Kiyoshi Nakayama, Ratnesh Sharma, Naren Ramakrishnan
2015	B	`conf`	Recommending Temporally Relevant News Content from Implicit Feedback Data. ICTAI Nikhil Muralidhar, Huzefa Rangwala, Eui-Hong Sam Han