## Professional Experience

## Academic Qualifications

## Awards

## Research Interests

## Professional Association

## Courses Taught

## Publications

2020 |
K. Gupta, B. Bhowmick and A. Majumdar, Systems and Methods for Coupled Representation using Transform Learning for Solving Inverse Problems, US Patent App. 16/502,760, 2020 |

J. Gubbi, K. Seemakurthy, N. K. Sandeep, A. Varghese, S. S. Deshpande, M. G. Chandra, P. Balamuralidhar and A. Majumdar, Method and System for solving Inverse Problems using Deep Dictionary Learning, US Patent App. 16/504,196, 2020 | |

2019 |
K. Gupta, B. Bhowmick and A. Majumdar, Systems and Methods for Solving Inverse Problems Using a Coupled Autoencoder, US Patent 10,360,665, 2019 |

T. Bose, A. Majumdar and T. Chattopadhyay, Method and System for Incorporating Regression into Stacked Auto Encoder (SAE), US Patent App. 16/265,906, 2019 | |

2018 |
K. Kumar, M. G. Chandra, A. A. Kumar and A. Majumdar, Anomaly Detection in Industrial Internet-of-Things, (India) filed. |

2017 |
M. Jain, S. Deb and A. Majumdar, Smartphone Based Health Monitoring Using the Inbuilt Camera, (India) filed. Application No. – 201711028803 |

M. Jain, A. V. Subramanyam, S. Deb and A. Majumdar, Cuff-less Blood Pressure Estimation Solution Using Electrocardiogram and Photoplethysmogram, (India) filed. Application No. – 201711028803 |

2018 |
A. Majumdar, Compressed Sensing for Engineers, CRC Press, 2018. |

M. Vatsa, R. Singh and A. Majumdar, Deep Learning in Biometrics CRC Press, 2018. | |

2015 |
A. Majumdar, Compressed Sensing for Magnetic Resonance Image Reconstruction Cambridge University Press, 2015. |

A. Majumdar and R. K. Ward Ed, MRI: Physics, Reconstruction and Analysis CRC Press, 2015. | |

R. Singh, M. Vatsa, A. Majumdar and A. Kumar Ed, Machine Intelligence and Signal Processing Springer, 2015. | |

2014 |
A. Majumdar, Advances in online dynamic MRI reconstruction Frontiers of Medical Imaging, C.H. Chen, World Scientific Publishing, 2014. |

2013 |
A. Majumdar and R. K. Ward, Sparsity Based Reconstruction Techniques in Single Channel and Multi-channel MRI Recent Advances in Medical Imaging Technologies, Troy Farncombe and Kris Iniewski, CRC Press, 2013. |

2011 |
A. Majumdar, R. K. Ward and P. Nasiopoulos, Distributed Face Recognition Face Recognition: Methods, Applications and Technology, Adamo Quaglia and Calogera M. Epifano Ed., Nova Publishers, NY, 2011. |

2011 |
A. Majumdar, R. K. Ward and P. Nasiopoulos, Distributed Face Recognition Face Recognition: Methods, Applications and Technology, Adamo Quaglia and Calogera M. Epifano Ed., Nova Publishers, NY, 2011. |

2010 |
A. Majumdar and R. K. Ward, DCompressive Classification for Face Recognition Face Recognition, Ed. Milos Oravec. Intech Publishers, pp. 47-64, 2010. |

A. Majumdar, Multi Font Bangla Basic Character Recognition via Multiresolution Transforms Digitizing the legacy of Indian Languages, Ed. Salonee Priya, ICFAI University Press, pp. 158-174, 2010. | |

2009 |
A. Majumdar and R. K. Ward, Multiresolution Methods in Face Recognition/a> Recent Advances in Face Recognition, Eds. M. S. Bartlett, K. Delac and M. Grgic, I-Tech Education and Publishing, Vienna, Austria, pp. 79-96, 2009. |

2021 |
Aanchal Mongia and Angshul Majumdar, Matrix Completion on Learnt Graphs: Application to Collaborative Filtering , Expert Systems with Applications (Accepted). |

Aanchal Mongia, Angshul Majumdar and Emilie Chouzenoux, Computational prediction of Drug-Disease association based on Graph-regularized one bit Matrix completion , IEEE/ACM Transactions on Computational Biology and Bioinformatics (Accepted). | |

A. Mongia, S. K. Saha, E. Chouzenoux and A. Majumdar, A computational approach to aid clinicians in selecting anti-viral drugs for COVID-19 trials , Nature Scientific Reports (Accepted). | |

S. Sharma, V. Elvira, E. Chouzenoux and A. Majumdar, Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting , Neurocomputing (Accepted). | |

Angshul Majumdar, Kernelized Linear Autoencoder , Neural Processing Letters. | |

Shalini Sharma and Angshul Majumdar, Sequential Transform Learning , Transactions on Knowledge Discovery from Data (accepted). | |

2020 |
Pooja Gupta, Angshul Majumdar, E. Chouzenoux and G. Chierchia, SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems , Expert Systems With Applications (accepted). |

Rachesh Sharma, Neetesh Pandey, Aanchal Mongia, Shreya Mishra, Angshul Majumdar, Vibhor Kumar, FITs: Forest of imputation trees for recovering true signals in single-cell open chromatin profiles , NAR Genomcs and Bioinformatics (accepted). | |

S. Sharma, A. Majumdar, Unsupervised Detection of Non-Technical Losses via Recursive Transform Learning , IEEE Transactions on Power Delivery (accepted). | |

S. Singh, A. Majumdar and S. Makonin, Compressive Non-Intrusive Load Monitoring , BuildSys'20, short paper (accepted). | |

S. Sharma, A. Majumdar, V. Elvira and E. Chouzenoux, Blind Kalman Filtering for Short-term Load Forecasting , IEEE Transactions on Power Systems (accepted). | |

P. Rai, D. Sengupta and A. Majumdar, SelfE: Gene Selection via Self Expression for Single-Cell Tata , IEEE Transactions on Computational Biology and Bioinformatics (accepted) (I.F. 2.8). | |

A. Majumdar, Graph Transform Learning , Neural Networks, Vol. 128, pp. 248-253, 2020. (I.F. 5.7) | |

P. Gupta, J. Maggu, A. Majumdar, E. Chouzenoux and G. Chierchia, DeConFuse: A Deep Convolutional Transform based Unsupervised Fusion Framework , EURASIP Journal on Advances in Signal Processing (accepted) (1.7) | |

J. Maggu, A. Majumdar, E. Chouzenoux and G. Chierchia, Deeply Transformed Subspace Clustering , Signal Processing, Vol. 174, 107628, 2020. (I.F. 4.0) | |

V. Singhal and A. Majumdar, A domain adaptation approach to solve inverse problems in imaging via coupled deep dictionary learning , Pattern Recognition (accepted), (I.F. 5.9) | |

A. Mongia and A. Majumdar, Drug-Target Interaction prediction using Multi Graph Regularized Nuclear Norm Minimization , PLOS ONE, vol. 15, no. 1, p.e0226484, 2020. (I.F. 2.7) | |

V. Singhal and A. Majumdar, Reconstructing Multi-echo Magnetic Resonance Images via Structured Deep Dictionary Learning , Neurocomputing (accepted), (I.F. 4.0) | |

J. Maggu, A. Majumdar and E. Chouzenoux, Transformed Subspace Clustering , IEEE Transactions on Knowledge and Data Engineering (accepted), (I.F. 4.0) | |

A. Mongia, N. Jhamb, E. Chouzenoux and A. Majumdar, Deep Latent Factor Model for Collaborative Filtering , Signal Processing, Vol. 169, 107366, 2020 (I.F. 4.0) | |

A. Mongia, D. Sengupta and A. Majumdar, deepMC: deep Matrix Completion for imputation of single cell RNA-seq data , Journal of Computational Biology (accepted) (I.F. 1.2) | |

S. Singh and A. Majumdar, Non-intrusive load Monitoring via Multi-label Sparse Representation based Classification , IEEE Transactions on Smart Grids, vol. 11, no. 2, pp. 1799-1801, 2020 (I.F. 10.5) | |

2019 |
A. Majumdar and M. Gupta, Recurrent Transform Learning , Neural Networks, vol. 118, pp.271-279, 2019 (I.F. 5.7). |

A. Mongia and A. Majumdar, Matrix Completion on Multiple Graphs: Application in Collaborative Filtering , Signal Processing, Vol. 165, pp. 144-148, 2019. (I.F. 4.0). | |

M. Gaur, S. Makonin, I. V. Bajić and A. Majumdar, Performance Evaluation of Techniques for Identifying Abnormal Energy Consumption in Buildings , IEEE Access, vol. 7, pp. 62721-62733, 2019 (I.F. 3.5). | |

J. Maggu, H. Agarwal and A. Majumdar, Label Consistent Transform Learning for Hyperspectral Image Classification , IEEE Geosciences and Remote Sensing Letters, Vol. 16 (9), pp. 1502-1506, 2019 (I.F. 2.9). | |

A. Mongia, D. Sengupta and A. Majumdar, McImpute: Matrix completion based imputation for single cell RNA-seq , Frontiers in Genetics, Vol. 10, 2019. (I.F. 4.1). | |

V. Singhal and A. Majumdar, Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 11 (12), 5019 – 5028, 2019 (I.F. 2.7). | |

A. Gogna and A. Majumdar, Discriminative Autoencoder for Feature Extraction: Application to Character Recognition, Neural Processing Letters, Vol. 49 (3), pp 1723–1735, 2019 (I.F. 1.7). | |

A. Majumdar, Blind Denoising Autoencoder, IEEE Transactions on Neural Networks and Learning Systems, Vol. 30 (1), pp. 312-317, 2019 (I.F. 7.9). | |

V. Singhal, J. Maggu and A. Majumdar, Simultaneous Detection of Multiple Appliances from Smart-meter Measurements via Multi-Label Consistent Deep Dictionary Learning and Deep Transform Learning, IEEE Transactions on Smart Grid, Vol. 10 (3), pp. 2969-2978, 2019 (I.F. 6.6). | |

S. Singh and A. Majumdar, Analysis Co-Sparse Coding for Energy Disaggregation, IEEE Transactions on Smart Grid, Vol. 10 (1), pp. 462-470, 2019. (I.F. 6.6). | |

2018 |
A. Majumdar, Compressed Sensing for Engineers, CRC Press, 2018. |

M. Vatsa, R. Singh and A. Majumdar, Deep Learning in Biometrics CRC Press, 2018. | |

D. Talwar, A. Mongia, D. Sengupta and A. Majumdar, AutoImpute: Autoencoder based imputation of single-cell RNA-seq data Nature Scientific Reports, vol. 8, no. 1, pp. 1-11, 2018 (I.F. 4.1). | |

A. Majumdar, Graph Structured Autoencoder Neural Networks, Vol. 106, pp. 271-280, 2018 (I.F. 7.1). | |

M. Gupta and A. Majumdar, Disaggregating Transform Learning for Non-Intrusive Load Monitoring IEEE ACCESS, vol. 6, pp. 46256 – 46265, 2018 (I.F. 3.2). | |

D. J. Lewis, V. Singhal and A. Majumdar, Solving Inverse Problems in Imaging via Deep Dictionary Learning, IEEE Access, Vol. 7, 37039 - 37049 (I.F. 3.2). | |

A. Majumdar, An Autoencoder Based Formulation for Compressed Sensing Reconstruction, Magnetic Resonance Imaging, Vol. 52, pp. 62-68, 2018 (I.F. 2.5). | |

J. Maggu, P. Singh and A. Majumdar, Multi-echo Reconstruction from Partial K-space Scans via Adaptively Learnt Basis, Magnetic Resonance Imaging, Vol. 52, pp. 62-68, 2018 (I.F. 2.5). | |

2017 |
V. Singhal, A. Majumdar and R. K. Ward, Semi-supervised Deep Blind Compressed Sensing for Analysis and Reconstruction of Biomedical Signals from Compressive Measurements, IEEE ACCESS, Vol. 6 (1), pp. 545-553. (I.F. 3.2). |

K. Gupta and A. Majumdar, Imposing Class-wise Feature Similarity in Stacked Autoencoders by Nuclear Norm Regularization Neural Processing Letters, (I.F. 1.7). | |

J. Maggu and A. Majumdar, Kernel Transform Learning, Pattern Recognition Letters, Vol. 117, pp. 117-122, 2017 (I.F. 1.9). | |

V. Singhal, H. Agrawal, S. Tariyal and A. Majumdar, Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification IEEE Transactions on Geosciences and Remote Sensing, Vol. 55 (9), pp. 5274-5283, 2017. (I.F. 4.9). | |

A. Gogna and A. Majumdar, Balancing Accuracy and Diversity in Recommendations using Matrix Completion Framework, Knowledge Based Systems, Vol. 125, pp. 83-95, 2017. (I.F. 4.5). | |

S. Singh and A. Majumdar, Deep Sparse Coding for Non-Intrusive Load Monitoring IEEE Transactions on Smart Grid, Vol. 9 (5), pp. 4669 - 4678 (I.F. 6.6). | |

V. Singal and A. Majumdar, Majorization Minimization Technique for Optimally Solving Deep Dictionary Learning, Neural Processing Letters, pp. 1- 16, 2017, (I.F. 1.7). | |

I. Manjani, S. Tariyal, M. Vatsa, R. Singh, A. Majumdar, Detecting Silicone Mask based Presentation Attack via Deep Dictionary Learning, IEEE Transactions on Information Forensics and Security, Vol. 12 (7), pp. 1713-1723, 2017 (I.F. 4.3). | |

A. Majumdar, Causal MRI Reconstruction via Kalman Prediction and Compressed Sensing Correction Magnetic Resonance Imaging, Vol. 39, pp. 64-70, 2017 (I.F. 2.2). | |

A. Sankaran, M. Vatsa, R. Singh and A. Majumdar, Group Sparse Autoencoder, Image and Vision Computing, Vol. 60, pp. 64-74, 2017 (I.F. 1.7). | |

M. Gulati, S. S. Ram, A. Majumdar and A. Singh, Single Point Conducted EMI Sensor With Intelligent Inference for Detecting IT Appliances, IEEE Transactions on Smart Grid, Vol. 9 (4), pp. 3716-3726, 2018 (I.F. 6.6). | |

A. Gogna and A. Majumdar, DiABlO: Optimization based design for improving diversity in recommender system Information Sciences, Vol. 378, pp. 59-74, 2017 (I.F. 4.8). | |

J. Mehta and A. Majumdar, RODEO: Robust DE-aliasing autoencOder for Real-time Medical Image Reconstruction, Pattern Recognition, Vol. 63, pp. 499-510, 2017 (I.F. 3.3). | |

A. Majumdar, A. Gogna and R. K. Ward, Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals, IEEE Transactions on Biomedical Engineering, Vol. 64 (9), pp. 2196 – 2205, 2017 (I. F. 2.5). | |

W Singh, A Shukla, S Deb, A Majumdar, Energy Efficient EEG Acquisition and Reconstruction for a Wireless Body Area Network, Integration, the VLSI Journal, Vol. 58, pp. 295-302, 2017. | |

A. Majumdar, M. Vatsa and R. Singh, Face Recognition via Class Sparsity based Supervised Encoding IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 39 (6), pp. 1273-1280, 1 2017. (I.F. 8.3). | |

A. Sankaran, G. Goswami, R. Singh, M. Vatsa and A. Majumdar, Class Sparsity Signature based Restricted Boltzmann Machines Pattern Recognition, Vol. 61, pp. 674-685, 2017. (I.F. 3.3). | |

2016 |
S. Tariyal, A. Majumdar, R. Singh and M. Vatsa, Deep Dictionary Learning, IEEE ACCESS, Vol. 4, pp. 10096 – 10109, 2016. (I. F. 1.3). |

N. Kohli, M. Vatsa, R. Singh, A. Noore and A. Majumdar, Hierarchical Representation Learning for Kinship Verification, IEEE Transactions on Image Processing, Vol. 26 (1), pp. 289-302, 217. (I.F. 3.7). | |

S. Tariyal, H. Agrawal and A. Majumdar, Removing Sparse Noise from Hyperspectral Images with Sparse and Low-rank Penalties, SPIE Journal of Electronic Imaging (accepted) (I.F. 0.7). | |

H. Agrawal and A. Majumdar, Hyperspectral Unmixing in the Presence of Mixed Noise using Joint-Sparsity and Total-Variation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 9 (9), pp. 4257 – 4266, 2016. (I.F. 3.0). | |

N. Kohli, M. Vatsa, R. Singh, A. Noore and A. Majumdar, Hyperspectral Image Denoising Using Spatio-Spectral Total Variation, IEEE Geosciences and Remote Sensing Letters, Vol. 13 (3), pp. 442-446, 2016. (I.F. 2.2). | |

A. Majumdar, N. Ansari, H. Agarwal and P. Biyani, Impulse Denoising for Hyper-Spectral Images: A Blind Compressed Sensing Approach, Signal Processing, Vol. 119, pp. 136-141, 2016. (I.F. 2.2) | |

G. Goswami, P. Mittal, A. Majumdar, R. Singh and M. Vatsa, Group Sparse Representation based Classification for Multi-feature Multimodal Biometrics, Information Fusion, Vol. 32 (B), pp. 3 - 12. (I.F. 10.7) | |

2015 |
A. Gogna and A. Majumdar, A Comprehensive Recommender System Model: Improving Accuracy for both Warm and Cold Start Users, IEEE ACESS, Vol. 2803 – 2813 (I.F. 1.2). |

A. Gogna and A. Majumdar, Blind Compressive Sensing Formulation Incorporating Metadata for Recommender System Design, APSIPA Transactions on Signal and Information Processing (Cambridge Journal), Vol. 4, 2015. | |

P. Khurana, P. Bhattacharjee and A. Majumdar, Matrix Factorization from Non-linear Projections: Application in Estimating T2 Maps from Few Echoes, Magnetic Resonance Imaging, Vol. 33 (7), pp. 927-931, 2015. (I.F. 2.0). | |

A. Gogna and A. Majumdar, Matrix Completion Incorporating Auxiliary Information for Recommender System Design, Expert Systems with Applications, Vol. 24 (14), pp. 5789-5799, 2015. (I.F. 2.9). | |

A. Majumdar and R. K. Ward, Energy Efficient EEG Sensing and Transmission for Wireless Body Area Networks: A Blind Compressed Sensing Approach, Biomedical Signal Processing and Control, Vol. 20, pp. 1-9, 2015. (I.F. 1.5). | |

H. Aggarwal and A. Majumdar, Exploiting Spatio-Spectral Correlation for Impulse Denoising in Hyperspectral Images, SPIE Journal of Electronic Imaging, Vol. 24(1), 013027, 2015 (I.F. 0.7). | |

A. Shukla and A. Majumdar, Exploiting Inter-channel Correlation in EEG Signal Reconstruction, Biomedical Signal Processing and Control, Vol. 18 (4), pp. 49–55, 2015 (I.F. 1.5). | |

S. S. Ram and A. Majumdar, High-resolution radar imaging of moving humans using doppler processing and compressed sensing, IEEE Transactions on Aerospace and Electronic Systems, Vol. 51, pp. 1279-1287, 2015 (I.F. 1.3). | |

A. Shukla and A. Majumdar, Row-sparse Blind Compressed Sensing for Reconstructing Multi-channel EEG signals, Biomedical Signal Processing and Control, Vol. 18 (4), pp. 174–178, 2015 (I.F. 1.5). | |

A. Majumdar, Improving Synthesis and Analysis Prior Blind Compressed Sensing with Low-rank Constraints for Dynamic MRI Reconstruction, Magnetic Resonance Imaging, Vol. 33(1), pp. 174-179, 2015 (I.F. 2.0). | |

2014 |
A. Majumdar and R. Ward, Exploiting Sparsity and Rank Deficiency for MR Image Reconstruction from Multiple Partial K-Space Scans, IEEE Canadian Journal of Electrical and Computer Engineering, Vol. 37 (4), pp. 228, 235, 2014 (invited). |

A. Majumdar, A. Gogna and R. Ward, Low-rank Matrix Recovery Approach For Energy Efficient EEG Acquisition for Wireless Body Area Network, Sensors, Special Issue on State-of-the-art Sensor Technologies in Canada, Vol. 14(9), pp. 15729-15748, 2014 (I.F. 2.0). | |

A. Majumdar and R. K. Ward, Non-Convex Row-sparse MMV Analysis Prior Formulation For EEG Signal Reconstruction, Biomedical Signal Processing and Control, Vol. 13, pp. 142–147, 2014 (I.F. 1.5). | |

2013 |
A. Majumdar, K. Chaudhury and R. Ward, Calibrationless Parallel Magnetic Resonance Imaging: A Joint Sparsity Model, Sensors, Special Issue on Magnetic Resonance Sensors, Vol. 13(12), pp. 16714-16735, 2013. (I.F. 2.0) |

M. Mohsina and A. Majumdar, Gabor Based Analysis Prior Formulation For EEG Signal Reconstruction, Biomedical Signal Processing and Control, Vol. 8 (6), pp. 951–955, 2013 (I.F. 1.5). | |

A. Majumdar, Motion Predicted Online Dynamic MRI Reconstruction from Partially Sampled K-Space Data, Magnetic Resonance Imaging, Vol. 31 (9), pp. 1578–1586, 2013. (I.F. 2.0) | |

H. S. Chen, A. Majumdar and P. Kozlowski, Compressed Sensing CPMG with Group-Sparse Reconstruction for Myelin Water Imaging, Magnetic Resonance in Medicine, Vol. 71 (3), pp. 1166-1171, 2013, (I. F. 3.0). | |

A. Majumdar and R. K. Ward, Rank Awareness in Group-sparse Recovery of Multi-echo MR Images, Sensors, Special Issue on Medical and Biomedical Imaging, Vol. 13 (3), pp. 3902-3921, 2013. (I.F. 2.0) | |

A. Majumdar, Improved Dynamic MRI Reconstruction by Exploiting Sparsity and Rank-Deficiency, Magnetic Resonance Imaging, Vol. 31(5), pp. 789-95, 2013. (I.F. 2.0) | |

A. Majumdar, R. K. Ward and T. Aboulnasr, Non-Convex Algorithm for Sparse and Low-Rank Recovery: Application to Dynamic MRI Reconstruction, Magnetic Resonance Imaging, Vol. 31 (3), pp. 448 – 455, 2013. (I.F. 2.0) | |

A. Majumdar, R. K. Ward and T. Aboulnasr, Algorithms to Approximately Solve NP Hard Row-Sparse MMV Recovery Problem: Application to Compressive Color Imaging, IEEE Journal on Emerging and Selected Topics in Circuits and Systems , Special Issue on Circuits, Systems and Algorithms for Compressive Sensing, Vol. 2 (3), pp. 362-369. 2013 (I.F. 1.5). | |

2012 |
A. Majumdar, R. K. Ward and T. Aboulnasr, Compressed Sensing Based near Real-Time Online Dynamic MRI Reconstruction, IEEE Transactions on Medical Imaging, Vol. 31 (2), pp. 2253 – 2266, 2012. (I.F. 3.7) |

A. Majumdar and R. K. Ward, Causal dynamic MRI reconstruction via nuclear norm minimization Magnetic Resonance Imaging, Vol. 30(10), 1483-94, pp. 2012. (I.F. 2.0) | |

A. Majumdar and R. K. Ward, Iterative Estimation of MRI Sensitivity Maps and Image based on SENSE Reconstruction (iSENSE) Concepts in Magnetic Resonance: Part A, Vol. 40 (6), pp. 269-280, 2012. (I.F. 1.7) | |

A. Majumdar, FOCUSS Based Schatten-p Norm Minimization for Real-Time Reconstruction of Dynamic Contrast Enhanced MRI IEEE Signal Processing Letters, Vol. 9(5), pp. 315-318, 2012. (I.F. 1.4) | |

A. Majumdar and R. K. Ward, Calibration-less Multi-Coil MR Image Reconstruction Magnetic Resonance Imaging, Vol. 30(7), pp. 1032-45, 2012. (I.F. 2.0) | |

A. Majumdar and R. K. Ward, Nuclear Norm Regularized SENSE Reconstruction Magnetic Resonance Imaging, Vol. 30 (2), pp. 213–221, 2012. (I.F. 2.0) | |

A. Majumdar and R. K. Ward, On the Choice of Compressed Sensing Priors: An Experimental Study Signal Processing: Image Communication, Vol. 27 (9), pp. 1035–1048, 2012. (I.F. 1.4) | |

A. Majumdar and R. K. Ward, Exploiting Rank Deficiency and Transform Domain Sparsity for MR Image Reconstruction Magnetic Resonance Imaging, Vol. 30 (1), pp. 9–18, 2012. (I.F. 2.0) | |

2011 |
A. Majumdar and R. K. Ward, An Algorithm for Sparse MRI Reconstruction by Schatten p-norm Minimization Magnetic Resonance Imaging, Vol. 29(3), pp. 408-17, 2011. (I.F. 2.0) |

A. Majumdar, Accelerating Multi-Echo T2 Weighted MR Imaging: Analysis Prior Group Sparse Optimization Journal of Magnetic Resonance, Vol. 210 (1), pp. 90-97, 2011. (I.F. 2.1) | |

A. Majumdar and R. K. Ward, Joint Reconstruction of Multi-echo MR Images Using Correlated Sparsity Magnetic Resonance Imaging, Vol. 29 (7), pp. 899-906, 2011. (I.F. 2.0) | |

A. Majumdar and R. K. Ward, Some Empirical Advances in Matrix Completion Signal Processing, Vol. 91 (5), pp. 1334-1338, 2011. (I.F. 2.2) | |

A. Majumdar and R. K. Ward, Increasing Energy Efficiency in Sensor Networks: Blue Noise Sampling and Non-Convex Matrix Completion International Journal of Sensor Networks, Vol. 9, (3/4), pp. 158-169, 2011. (I.F. 1.4) | |

2010 |
A. Majumdar and R. K. Ward, Improved Group Sparse Classifier Pattern Recognition Letters, Vol. 31 (13), pp. 1959-1964, 2010. (I.F. 1.5) |

A. Majumdar and R. K. Ward, Compressed Sensing of Color Images Signal Processing, Vol. 90 (12), 3122-3127, 2010. (I.F. 2.2) | |

A. Majumdar and R. K. Ward, Robust Classifiers for Data Reduced via Random Projections IEEE Transactions on Systems, Man, and Cybernetics, Part B, Vol. 40 (5), pp. 1359 - 1371. (I.F. 3.0) | |

2009 |
A. Majumdar and R. K. Ward, Fast Group Sparse Classification IEEE Canadian Journal of Electrical and Computer Engineering, Vol. 34 (4), pp. 136-144, 2009, (Invited). |

A. Majumdar and R. K. Ward, Image Compression by Block PCA Coding in Curvelet Domain Journal of Signal, Image and Video Processing, Vol. 3 (1), pp. 27-34(8), 2009. (I.F. 0.6) |