The focus of the research of Signal Processing and Machine Learning Group is on the integration of data, knowledge, and tools necessary for efficient knowledge discovery in the decision-making process associated with information extraction and computational intelligence. The group's research addresses the design and development of signal processing and machine learning techniques and the interpretation of signals and systems to improve monitoring, diagnosis and prognosis. The group explores new methodologies for multimodal, multi-scale and multi-channel acquisition, processingand interpretation of information.
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Application is invited from the prospective students for the position of Junior Project Assistant. The candidate may register to MS programme in EE department of IIT Kharagpur subject to the fulfillment of admission norms. Position: Junior Project Assistant Title of Project: Personalized Lung Function Test through Smartphone-based Spirometer Domain Area : Medical Signal Processing and Machine Learning Manadatory Qualification: B.E/B. Tech in Electrical or Electronics & Communication Engineering (from reputed NITs and universities) with GATE score in EE/EC paper. Desirable Qualification: Knowledge of Python and/or Java
Hi!
If you are interested in working with me for one year or more, in the field of Signal Processing and/or Machine Learning, please do send me an email listing your interests and the research degree you intend to pursue at IIT Kharagpur.
Have a look at our Software Download Centre. These packages are developed by SPML members. If you are appearing for the research interview at the Department of Electrical Engineering, please do visit the Department of Electrical Engineering to know about the interview procedure. If you like to meet me in my office at N-243 in Electrical Engineering Department, please drop an e-mail for appointment prior to your visit. Wishing you all the best. Anirban Send e-mail
Dr. Anirban Mukherjee Coordinator, SPML Department of Electrical Engineering, Indian Institute of Technology Kharagpur, Kharagpur - 721 302, West Bengal, India. Email: anirban [AT] ee [DOT] iitkgp [DOT] ac [DOT] in Telephone: +91-3222-283050
Dr. Anirban Mukherjee
Dr. Anirban Mukherjee is exploring the development of signal processing algorithms for healthcare applications. He is the co-ordinator of SPML group.
E-mail: anirban [AT] ee [DOT] iitkgp [DOT] ac [DOT] in
G. Satya Prasad is a Ph.D. student. His broad area of research is Signal Processing for 6G.
E-mail: gsat1992 [AT] gmail [DOT] com
Deepak Sahu is a Ph.D. student. he completed her post-graduate studies from NIT Rourkela. His broad area of research is Machine Learning.
E-mail: deepakkusahu13 [AT] gmail [DOT] com
Jessy Rimaya Khonglah is a Ph.D. student. She completed her post-graduate studies from NIT Jalandhar. She is currently working on Graph Signal Processing.
E-mail: jessy [DOT] khonglah [AT] gmail [DOT] com
Publications
Supratim Manna, Jessy Rimaya Khonglah, Anirban Mukherjee, and Goutam Saha; Robust Kernelized Graph-based Learning, accepted in Pattern Recognition, Elsevier, 2021.
MD. Afaque Azam is a doctoral student. He completed his post-graduate studies from IIT Kanpur. He is currently working on Signal Processing for Massive MIMO.
E-mail: afaqueazam [AT] gmail [DOT] com
Google Scholar Profile: citation
Fellowship
MD. A. Azam has received the fellowship from the Tata Consultancy Services (TCS) Research Scholar Program 2018-22.
MD Afaque Azam, Amit Kumar Dutta and Anirban Mukherjee; Uplink Channel Estimation with Hardware Imperfections, Antenna Position Error and Channel Correlation for Nested and Linear Array Antennas, IEEE Trans. Vehicular Technology, vol. 69, no. 12, pp. 15412-15426, 2020.
Maitreya Maity is a doctoral student. He completed his post-graduate studies from IIT Kharagpur. He is currently working on healthcare informatics.
E-mail: maitreya [DOT] maity [AT] gmail [DOT] com
Maitreya Maity, Ayush Jaiswal, Kripasindhu Gantait, Jyotirmoy Chatterjee and Anirban Mukherjee; Quantification of Malaria Parasitaemia using Trainable Semantic Segmentation and Capsnet, Pattern Recognition Letters, Elsevier, vol. 138, pp. 88-94, 2020.
Venkatesh Vakamullu is a doctoral student. He completed his post-graduate studies from Tejpur University, Assam. He is working on Phonocardiogram Signal Processing.
E-mail: venkatesh [DOT] vakamullu [AT] gmail [DOT] com
Supratim Manna is an MS student in the Department of Electrical Engineering. He completed his undergraduate study in Electrical Engineering from IIEST Shibpur. He worked on Graph-based Learning.
E-mail: supratimmanna121 [AT] gmail [DOT] com
Supratim Manna, Jessy Rimaya Khonglah, Anirban Mukherjee, and Goutam Saha; Robust Kernelized Graph-based Learning, accepted in Pattern Recognition, Elsevier, 2020.
Dr. Madhusudhan Mishra worked on heart-lung sound signal-based diagnostics. Dr. Madhusudhan Mishra is in the faculty of the Department of Electronics and Communication Engineering in the North Eastern Regional Institute of Science and Technology (NERIST), India.
E-mail: ecmadhusudhan [AT] gmail [DOT] com
Madhusudhan Mishra, Sawon Pratiher, Hrishikesh Menon and Anirban Mukherjee; Identification of S1 and S2 Heart Sounds using Spectral and Convex Hull Features, IEEE Sensors Journal, vol. 20, no. 8, pp. 4311-4320, 2020.
Madhusudhan Mishra, Hrishikesh Menon, and Anirban Mukherjee; Characterization of S1 and S2 Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network, IEEE Trans. Instrumentation and Measurement, vol. 68, no. 9, pp. 3211-3220, 2019.
Madhusudhan Mishra, Sanmitra Banerjee, Dennis Thomas, Sagnik Dutta, and Anirban Mukherjee; Detection of Third Heart Sound using Variational Mode Decomposition, IEEE Trans. Instrumentation and Measurement, vol. 67, no. 7, pp. 1713-1721, 2018.
Dr. Priya Ranjan Muduli worked on Sparse Signal Processing. Dr. Priya Ranjan Muduli is in the faculty of the Department of Electronics Engineering in the Indian Institute of Technology BHU, India.
E-mail: priyaranjanmuduli [AT] gmail [DOT] com
Priya Ranjan Muduli and Anirban Mukherjee; A Moreau Envelope-based Nonlinear Filtering Approach to Denoising Physiological Signals, IEEE Trans. Instrumentation and Measurement, vol. 69, no. 4, pp. 1041-1050, 2020.
Priya Ranjan Muduli and Anirban Mukherjee; A Robust Estimator-Based Nonlinear Filtering Approach to Piecewise Biosignal Reconstruction, IEEE Trans. Instrumentation and Measurement, vol. 69, no. 2, pp. 362-370, 2020.
Priya Ranjan Muduli, Atindra Kanti Mandal, and Anirban Mukherjee; An Anti-Noise-Folding Algorithm for the Recovery of Biomedical Signals from Noisy Measurements, IEEE Trans. Instrumentation and Measurement, vol. 66, no. 11, pp. 2909-2916, 2017.
Priya Ranjan Muduli and Anirban Mukherjee; A Subspace Projection-based Joint Sparse Recovery Method for Structured Biomedical Signals, IEEE Trans. Instrumentation and Measurement, vol. 66, no. 2, pp. 234-242, 2017.
Arpan Guha Mazumder worked on analysis of proteomic signal for diagnosis and prognosis of Diabetic Retinopathy.
E-mail: arpan007atgc [AT] gmail [DOT] com
Arpan received the prestigious Fulbright-Nehru Doctoral Research Fellowship 2014-15.
A. Guha Mazumder, S. Banerjee, F. Zevictovich, S. Ghosh, Anirban Mukherjee, and J. Chatterjee; Fourier-transform-infrared-spectroscopy based metabolomic spectral biomarker selection towards optimal diagnostic differentiation of diabetes with and without retinopathy, Spectroscopy Letters, DOI: 10.1080/00387010.2018.1471510, 2018.
A. Guha Mazumder, S. Chatterjee, S. Chatterjee S, J. J. Gonzalez, S. Bag, S. Ghosh, Anirban Mukherjee, and J. Chatterjee; Spectropathology-corroborated multimodal quantitative imaging biomarkers for neuroretinal degeneration in diabetic retinopathy, Clinical Ophthalmology, vol. 11, pp. 2073-2089, 2017.
Arpan Guha Mazumder, Sambuddha Ghosh, Swarnendu Bag, Sumanta Bera, Srutarshi Ghosh, Anirban Mukherjee and Jyotirmoy Chatterjee; 1H-NMR based Serum Metabolomic Signatures Imperative in Retinalneurodegeneration and Development of Diabetic Retinopathy, International Journal of Medical Research and Review, vol. 4, no. 6, pp. 976-981, 2016.
Dr. Surajit Panja worked on modeling of the dynamics Metabolic Networks (MN). He used S-system model to study the performance and robustness of these networks. Dr. Surajit Panja is in the faculty of the Department of Electronics and Communication Engineering in the Indian Institute of Information Technology Guwahati, India.
E-mail: surajit[DOT]panja [AT] gmail [DOT] com
Surajit Panja, Sourav Patra and Anirban Mukherjee; Tweaking Metabolic Networks: A Design Method, INAE Letters, Springer, pp. 1-6, DOI 10.1007/s41403-016-0005-5, 2016. (MATLAB toolbox available in SDC.)
Surajit Panja, Sourav Patra, Anirban Mukherjee, Madhumita Basu, Sanghamitra Sengupta and Pranab K. Dutta; A Closed-loop Control Scheme for Steering Steady States of Glycolysis and Glycogenolysis Pathway, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 4, pp. 858-868, 2013.
Surajit Panja, Sourav Patra, Anirban Mukherjee, Madhumita Basu, Sanghamitra Sengupta and Pranab K. Dutta; Robustness of TCA Cycle at Steady-State: An LMI-based Analysis and Synthesis Framework, IEEE Trans. on Nanobioscience, vol. 12, no. 2, pp. 128-134, 2013.
Surajit Panja, Sourav Patra, Anirban Mukherjee, Madhumita Basu, Sanghamitra Sengupta and Pranab K. Dutta; An Optimization-based Design Framework for Steering Steady-States and Improving Robustness of Glycolysis-Glycogenolysis Pathway, IEEE Trans. Biomedical Engineering, vol. 60, no. 2, pp. 554-561, 2013.
Dr. Supratim Gupta developed Image-based Driver Alertness System. Dr. Supratim Gupta is in the faculty of Electrical Engineering in National Institute of Technology, Rourkela.
E-mail: guptasu[AT] nitrkl [DOT] ac [DOT] in
Supratim Gupta, Aurobinda Routray and Anirban Mukherjee; A New Method for Edge Extraction in Images using Local Form Factors, Intl. Journal of Computer Applications, vol. 21, no. 2, pp. 15-22, 2011.
Dr. Santanu Ghorai developed a Non-parallel Plane Proximal (Kernel) Classifier (NPPC). He also developed a regression methodology, Vector-Valued Regularized Kernel Function Approximation (VVRKFA). The NPPC and VVRKFA Toolbox (MATLAB) are available in the Software Download Centre. He has an expertise in handling high-throughput -omics data in the Machine Learning framework. Dr. Santanu Ghorai is in the faculty of the Department of Applied Electronics & Instrumentation Engineering in Heritage Institute of Technology, Kolkata.
E-mail: santanughorai74 [AT] gmail [DOT] com
Santanu Ghorai, Anirban Mukherjee and Pranab K Dutta; Advances in Proximal Kernel Classifiers, Lambert Academic Publishing, Germany, 2012, ISBN 978-3-659-27836-5.
Santanu Ghorai, Anirban Mukherjee, M. Gangadharan and Pranab K. Dutta; Automatic Defect Detection on Hot Rolled Flat Steel Products, IEEE Trans. Instrumentation and Measurement, vol. 62, no. 3, pp. 612-621, 2013.
Santanu Ghorai, Anirban Mukherjee, Sanghamitra Sengupta and Pranab K. Dutta; Cancer Classification from Gene Expression Data by NPPC Ensemble, IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 8, no. 3, pp. 659-671, 2011.
Santanu Ghorai, Anirban Mukherjee and Pranab K. Dutta; Discriminant Analysis for Fast Multiclass Data Classification through Regularized Kernel Function Approximation, IEEE Trans. Neural Networks, vol. 21, no. 6, pp. 1020-1029, 2010. (MATLAB toolbox available in SDC).
Santanu Ghorai, Shaikh Jahangir Hossain, Anirban Mukherjee, and Pranab K. Dutta; Newton's Method for Nonparallel Plane Proximal Classifier with Unity Norm Hyperplanes, Signal Processing, vol. 90, no. 1, pp. 93-104, 2010. (MATLAB toolbox available in SDC).
Santanu Ghorai, Anirban Mukherjee and Pranab K. Dutta; Nonparallel Plane Proximal Classifier, Signal Processing, vol. 89, no. 4, pp. 510-522, 2009.
Sudipto Trivedy was an MS student in the Department of Electrical Engineering. He completed his undergraduate study in Electrical Engineering from IIEST Shibpur. He worked on Respiratory signal processing in a point-of-care applications. He has joined the AI division of the Tata Steel.
E-mail: sudipto.trivedy [AT] gmail [DOT] com
Sudipto Trivedy, Manish Goyal, Prasanta R. Mohapatra, and Anirban Mukherjee; Design and Development of Smartphone-enabled Spirometer with a Disease Classification System Using Convolutional Neural Network, IEEE Trans. Instrumentation and Measurement, vol. 69, no. 9, pp. 7125-7135, 2020.
Akhilesh Kumar was an M. Tech student graduated in 2019. He worked on Tracking of Vehicles and Estimation of Speed of Vehicle using Radar Signals. He is working in DRDO Hyderabad, India.
E-mail: akhilesh2k3@gmail.com
Akhilesh Kumar, Anirban Mukherjee and Mahendra Mandava; Estimation of Speed and Tracking of Vehicles using Radar Duet, 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2019), 20 - 23 May, 2019, Auckland, New Zealand.
Atindra Kanti Mandal was an M. Tech student in 2017. He worked on respiratory signal acquisition and processing in the Point of Care settings. He is currently continuing his PhD studies in IIT Bombay.
E-mail: atindra1 [AT] gmail [DOT] com
Sachin Tom John was an M. Tech student graduated in 2016. He worked on fetal ECG acquisition and its applicability in the Point-Of-Care (POC) settings. He is working in the Indian Air Force.
E-mail: sachintomjohn [AT] rediffmail [DOT] com
Sachin Tom John, P. R. Muduli, Anirban Mukherjee; An Analog-Front-End for Non-Invasive Fetal Electrocardiography Monitoring, 2016 IEEE Techsym, Sep. 30 - Oct. 02, 2016, IIT Kharagpur, India.
Accolade The Wearable FECG Monitor, designed by Sachin Tom John, has been judged runners-up in the Internet-of-Things/Wearables devices category in ARM Competition.
In the Embedded World 2016 Conference, ARM conducted a competition of products developed using ARM-based SoCs. Among the winners is the Wearable FECG Monitor designed by Sachin Tom John. It has been judged runners-up in the Internet-of-Things/Wearables devices category.
Ramakanth Reddy was a Dual-degree M. Tech student graduated in 2015. He worked on Respiratory Signal Storage via Compressed Sensing.
E-mail: ramakanth.1729 [AT] gmail [DOT] com
Aniruddha Maiti, Ramakanth Reddy and Anirban Mukherjee; Structural Prediction of Dynamic Bayesian Network with Partial Prior Information, IEEE Trans. on NanoBioscience, vol. 14, no. 1, pp. 95-103, 2015.
Aniruddha Maiti was a CSIR-sponsored MS student in 2014. He worked on mining of motifs in Transcription Interaction Networks (TIN) and Protein-Protein Intercation Networks (PPIN). He developed Model Shift-based Monte Carlo-based Expectation Maximization (MSMCEM) algorithm. This is available in the Software Download Centre.
E-mail: aniruddha.maiti87 [AT] gmail [DOT] com
Aniruddha Maiti and Anirban Mukherjee; On the Monte-Carlo Expectation Maximization for Finding Motifs in DNA Sequences, IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 2, pp. 677-686, 2015. (MATLAB toolbox available in SDC.)
Shivashanker Reddy was an M. Tech student graduated in 2007. He worked on segmentation of microscopic images under varying degree of staining.
E-mail:
Tathagata Ray, D. Shivashanker Reddy, Anirban Mukherjee, Jyotirmoy Chatterjee, Ranjan Rashmi Paul and Pranab K. Dutta; Detection of Constituent Layers of Histological Oral Sub-mucous Fibrosis Images using the Hybrid Segmentation Algorithm, Oral Oncology, 44, no. 12, pp. 1167-1171, 2008. Download.
Hrishikesh Menon was a dual degree M. Tech student. He was working in the area of deep learning applications of Iris biometrics.
E-mail: hrishikeshmenon96 [AT] gmail [DOT] com
Sanmitra Banerjee was an undergraduate student. He worked in the area of signal processing for cardio-pulmonary sound.
E-mail: sanmitra [DOT] roni [AT] gmail [DOT] com
Rakesh Reddy Gunukula was a B. Tech student. He was working on deep learning-based sparse signal recovery for fetal ecg signal in the Point-Of-Care (POC) settings.
E-mail: rakeshreddy [DOT] gunukula [AT] gmail [DOT] com
P. R. Muduli, Rakesh Gunukula Reddy and Anirban Mukherjee; A Deep Learning Approach to Fetal-ECG Signal Reconstruction, 22nd National Conference on Communications, 4-6 March, 2016, IIT Guwahati, India.