Distributed Sampling for Dense Sensor Networks: A "Bit-Conservation Principle". - Prakash Ishwar; Animesh Kumar; Kannan Ramchandran (IPSN, 2003)

On distributed sampling of bandlimited and non-bandlimited sensor fields. - Animesh Kumar; Prakash Ishwar; Kannan Ramchandran (ICASSP (3), 2004)

On distributed sampling of smooth non-bandlimited fields. - Animesh Kumar; Prakash Ishwar; Kannan Ramchandran (IPSN, 2004)

Fundamental Redundancy Versus Power Trade-Off in Standby SRAM. - Animesh Kumar; Huifang Qin; Prakash Ishwar; Jan M. Rabaey; Kannan Ramchandran (ICASSP (2), 2007)

Fundamental Bounds on Power Reduction during Data-Retention in Standby SRAM. - Animesh Kumar; Huifang Qin; Prakash Ishwar; Jan M. Rabaey; Kannan Ramchandran (ISCAS, 2007)

Fundamental Data Retention Limits in SRAM Standby Experimental Results. - Animesh Kumar; Huifang Qin; Prakash Ishwar; Jan M. Rabaey; Kannan Ramchandran (ISQED, 2008)

Error-Tolerant SRAM Design for Ultra-Low Power Standby Operation. - Huifang Qin; Animesh Kumar; Kannan Ramchandran; Jan M. Rabaey; Prakash Ishwar (ISQED, 2008)

SRAM supply voltage scaling: A reliability perspective. - Animesh Kumar; Jan M. Rabaey; Kannan Ramchandran (ISQED, 2009)

Dithered A/D conversion of smooth non-bandlimited signals. - Animesh Kumar; Prakash Ishwar; Kannan Ramchandran (IEEE Trans. Signal Process., 2010)

High-Resolution Distributed Sampling of Bandlimited Fields With Low-Precision Sensors. - Animesh Kumar; Prakash Ishwar; Kannan Ramchandran (IEEE Trans. Inf. Theory, 2011)

SRAM in hold-operation: Modeling the interaction of soft-errors and switching power-supply noise. - Amrut Kolhapure; Animesh Kumar (ISCAS, 2012)

On the Separability of Targets Using Binary Proximity Sensors - B. Santhana Krishnan; Animesh Kumar; D. Manjunath; Bikash Kumar Dey (CoRR, 2012)

Estimation of Bandlimited Signals in Additive Gaussian Noise: a "Precision Indifference" Principle - Animesh Kumar; Vinod M. Prabhakaran (CoRR, 2012)

Estimation of bandlimited signals from the signs of noisy samples. - Animesh Kumar; Vinod M. Prabhakaran (ICASSP, 2013)

Channel-code detection by a third-party receiver via the likelihood ratio test. - Arti D. Yardi; Animesh Kumar; Saravanan Vijayakumaran (ISIT, 2014)

Quantitative assessment of TV white space in India. - Gaurang Naik; Sudesh Singhal; Animesh Kumar; Abhay Karandikar (NCC, 2014)

Sampling smooth spatio-temporal physical fields: When will the aliasing error increase with time? - Karthik Sharma; Animesh Kumar (ICASSP, 2015)

OpenPAWS: An open source PAWS and UHF TV White Space database implementation for India. - Soumik Ghosh; Gaurang Naik; Animesh Kumar; Abhay Karandikar (NCC, 2015)

How much TV UHF band spectrum is sufficient for rural broadband coverage? - Animesh Kumar; Rajeev Kumar 003; Punit Rathod; Abhay Karandikar (WiOpt, 2015)

Bandlimited Spatial Field Sampling with Mobile Sensors in the Absence of Location Information. - Animesh Kumar (CoRR, 2015)

On Bandlimited Signal Reconstruction From the Distribution of Unknown Sampling Locations. - Animesh Kumar (IEEE Trans. Signal Process., 2015)

Interference-constrained coverage algorithms in the protocol and SINR models. - Prateek R. Kapadia; Om P. Damani; Animesh Kumar (Wirel. Networks, 2015)

High rate quantization analysis for a class of finite rate of innovation signals. - Ajinkya Jayawant; Animesh Kumar (EUSIPCO, 2016)

Optimal quantization of TV white space regions for a broadcast based geolocation database. - Garima Maheshwari; Animesh Kumar (EUSIPCO, 2016)

Bandlimited field reconstruction from samples obtained on a discrete grid with unknown random locations. - Ankur Mallick; Animesh Kumar (ICASSP, 2016)

Toward enabling broadband for a billion plus population with TV white spaces. - Animesh Kumar; Abhay Karandikar; Gaurang Naik; Meghna Khaturia; Shubham Saha; Mahak Arora; Jaspreet Singh (IEEE Commun. Mag., 2016)

Estimation of Bandlimited Grayscale Images From the Single Bit Observations of Pixels Affected by Additive Gaussian Noise. - Abhinav Kumar 004; Animesh Kumar (CoRR, 2016)

Towards Enabling Broadband for a Billon Plus Population with TV White Spaces. - Animesh Kumar; Abhay Karandikar; Gaurang Naik; Meghna Khaturia; Shubham Saha; Mahak Arora; Jaspreet Singh (CoRR, 2016)

Bandlimited Field Reconstruction from Samples Obtained at Unknown Random Locations on a Grid. - Ankur Mallick; Animesh Kumar (CoRR, 2016)

Blind Reconstruction of Binary Cyclic Codes From Unsynchronized Bitstream. - Arti D. Yardi; Saravanan Vijayakumaran; Animesh Kumar (IEEE Trans. Commun., 2016)

Optimal Envelope Approximation in Fourier Basis with Applications in TV White Space. - Animesh Kumar (CoRR, 2017)

Spatial Field estimation from Samples taken at Unknown Locations generated by an Unknown Autoregressive Process. - Sudeep Salgia; Animesh Kumar (CoRR, 2017)

Mobile Sensing of Two-Dimensional Bandlimited Fields on Random Paths. - Charvi Rastogi; Animesh Kumar (CoRR, 2017)

On Bandlimited Field Estimation from Samples Recorded by a Location-Unaware Mobile Sensor. - Animesh Kumar (IEEE Trans. Inf. Theory, 2017)

Estimation of Bandlimited Signals on Graphs From Single Bit Recordings of Noisy Samples. - Mohak Goyal; Animesh Kumar (EUSIPCO, 2018)

Bandlimited Spatiotemporal Field Sampling with Location and Time Unaware Mobile Sensors. - Sudeep Salgia; Animesh Kumar (ICASSP, 2018)

On Distributed Nonlinear Signal Analytics : Bandwidth and Approximation Error Tradeoffs. - Vijay Anavangot; Animesh Kumar (CoRR, 2018)

Novel Near-Optimal Scalar Quantizers with Exponential Decay Rate and Global Convergence. - Vijay Anavangot; Animesh Kumar (CoRR, 2018)

A Novel Approximate Lloyd-max Quantizer and Its Analysis. - Vijay Anavangot; Animesh Kumar (ICASSP, 2019)

Feasibility assessment of location-unaware sensing for estimation of non-bandlimited measurements. - Shruti Sawant; Indrani Mukherjee; Siddharth G. Tallur; Animesh Kumar (IEEE SENSORS, 2019)

Distribution Learning of a Random Spatial Field with a Location-Unaware Mobile Sensor. - Meera Pai; Animesh Kumar (NeurIPS, 2019)

A Transfer Learning Approach to Classify the Brain Age from MRI Images. - Animesh Kumar; Pramod Pathak; Paul Stynes (BDA, 2020)

Algorithms for Overpredictive Signal Analytics in Federated Learning. - Vijay Anavangot; Animesh Kumar (EUSIPCO, 2020)

Estimation of Time to Failure Distribution in SRAM Due to Trapped Oxide Charges. - Dimple Kochar; Animesh Kumar (ISCAS, 2021)

Signal Source Distribution Approximation to Speedup Scalar Quantizer Design. - Vijay Anavangot; Animesh Kumar (IEEE Trans. Signal Process., 2021)

Signal Reconstruction From Quantized Noisy Samples of the Discrete Fourier Transform. - Mohak Goyal; Animesh Kumar (IEEE Trans. Signal Process., 2022)

Beyond Scaling: Predicting Patent Approval with Domain-specific Fine-grained Claim Dependency Graph. - Xiaochen Gao; Feng Yao; Kewen Zhao; Beilei He; Animesh Kumar; Vish Krishnan; Jingbo Shang (ACL (1), 2024)

Deep Reinforcement Learning Based Bandwidth Part Assignment in 5G NR-U. - S. Ram Aditya; Shyamal Dhua; Animesh Kumar; Vimal Bastin Edwin Joseph; R. Rajavelsamy (CCNC, 2024)

Data Contamination Can Cross Language Barriers. - Feng Yao; Yufan Zhuang; Zihao Sun; Sunan Xu; Animesh Kumar; Jingbo Shang (EMNLP, 2024)

Unmasking the Phantom: Discovering Exogenous Cues to Detect Political Deepfake Images. - Animesh Kumar; Christoph Burtscher; Andreas Eckhardt (ICIS, 2024)

Cracking Political Deepfakes: An Exploratory Study to Unveil Cues for Detection. - Animesh Kumar; Christoph Burtscher; Andreas Eckhardt (Wirtschaftsinformatik, 2024)

Sentiment-aware Enhancements of PageRank-based Citation Metric, Impact Factor, and H-index for Ranking the Authors of Scholarly Articles. - Shikha Gupta; Animesh Kumar (Comput. Sci., 2024)

Redefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML). - Animesh Kumar (CoRR, 2024)

AI-Driven Innovations in Modern Cloud Computing. - Animesh Kumar (CoRR, 2024)

Analysis of SQL injection attacks in the cloud and in WEB applications. - Animesh Kumar; Sandip Dutta; Prashant Pranav (Secur. Priv., 2024)

Role of Partisanship in Detection of Political Audio-visual Deepfakes: A Study on the 2024 U.S. Presidential Election. - Animesh Kumar; Christoph Burtscher; Andreas Eckhardt (PACIS, 2025)