IITKGP Signal Processing and Machine Learning Group Homepage
Mission of Signal Processing and Machine Learning Research Group

The focus of our research 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 biomedical signals to improve monitoring and diagnosis. We explore new methodologies for multimodal, multi-scale and multi-channel acquisition, processing and interpretation of clinically relevant information from biomedical signals and images. The principal objective is to improve the non-invasive diagnosis capability through the characterization of physiological phenomena, and to enhance early detection of diseases like cardiac, respiratory and sleep disorders. The Signal Processing and Machine Learning research group encourages the development of theoretical and practical methods of information processing with special emphasis on healthcare.

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Photo Gallery


News and Announcement

Application is invited from the prospective students for the position of Junior Research Fellow/Junior Project Officer in the area of Development of ECG Signal Processing Algorithm and Platform with extended recording and episode detection. Having a good GATE score in EC/EE/IN is mandatory. The candiadate may register to MS programme in ECE or EE department of IIT Kharagpur subject to the fulfilment of admission norms.


Message to Prospective Group Members

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 email for appointment prior to your visit.

Wishing you all the best.

Anirban


Contact us

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] ernet [DOT] in
Telephone: +913222283050
Facebook Page:https://www.facebook.com/SPML.IITKGP/

Dr. Anirban Mukherjee is exploring the development of machine learning algorithms for high throughput -omics data. He is interested in developing signal/image processing algorithms, portable to platforms of Analog Devices for the "e-Health" applications.

The group has collaboration with Analog Devices in terms of exchange of human resource and software/hardware support.
He is a regular member and the co-ordinator of SPML group.

E-mail: anirban [AT] ee [DOT] iitkgp [DOT] ernet [DOT] in


Present Members
Arpan Guha Mazumder

Arpan Guha Mazumder is a doctoral student. He completed his post-graduate studies from the University of Madras. He is working on analysis of proteomic signal for diagnosis and prognosis of Diabetic Retinopathy.

E-mail: arpan007atgc [AT] gmail [DOT] com


Fellowship

Arpan has received the prestigious Fulbright-Nehru Doctoral Research Fellowship 2014-15.

Publications

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.

Jessy Rimaya Khonglah

Jessy Rimaya Khonglah is a Ph.D. student. She completed her post-graduate studies from NIT Jalandhar. She is currently working on speech signal processing application in the healthcare domain.

E-mail: jessy [DOT] khonglah [AT] gmail [DOT] com

Madhusudhan Mishra

Madhusudhan Mishra is a doctoral student. He completed his post-graduate studies from IIT Guwahati. He is currently working on heart-lung sound signal-based diagnostics.

E-mail: ecmadhusudhan [AT] gmail [DOT] com

Google Scholar Profile: citation


Publications

Sanmitra Banerjee, Madhusudhan Mishra and Anirban Mukherjee; Segmentation and Detection of First and Second Heart Sounds (S1 and S2) using Variational Mode Decomposition, IEEE-EMBS Conference on Biomedical Engineering and Sciences, 03-08 Dec. 2016, Kuala Lumpur, Malaysia.

Maitreya Maity

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

MD. Afaque Azam

MD. Afaque Azam is a doctoral student. He completed his post-graduate studies from IIT Kanpur. He is currently working on parametric spatial sound processing.

E-mail: afaqueazam [AT] gmail [DOT] com

Priya Ranjan Muduli

Priya Ranjan Muduli is a doctoral student. He completed his post-graduate studies from NIT Rourkela. He is working on Sensor Fusion in Wireless Body Area Networks.

E-mail: priyaranjanmuduli [AT] gmail [DOT] com

Google Scholar Profile: citation


Publications

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.

Priya Ranjan Muduli and Anirban Mukherjee; Noise-assisted Trend-filtering of Fetal-Electrocardiogram Signals, IEEE-EMBS Conference on Biomedical Engineering and Sciences, 03-08 Dec. 2016, Kuala Lumpur, Malaysia.

Sachin Tom John, Priya Ranjan Muduli, Anirban Mukherjee; An Analog-Front-End for Non-Invasive Fetal Electrocardiography Monitoring, 2016 IEEE Techsym, Sep. 30 - Oct. 02, 2016, IIT Kharagpur, India.

Priya Ranjan Muduli and Anirban Mukherjee; A Subspace Projection-based Joint Sparse Recovery Method for Structured Biomedical Signals, accepted in IEEE Transactions on Instrumentation and Measurement, 2016.

Ramakanth Reddy, Priya Ranjan Muduli and Anirban Mukherjee; Compressed Sensing of Respiratory Signals Promoting Joint-Sparsity, 22nd National Conference on Communications, 4-6 March, 2016, IIT Guwahati, India.

Priya Ranjan 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.

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Sanmitra Banerjee

Sanmitra Banerjee is an undergraduate student. He is currently working in the area of signal processing for cardio-pulmonary sound.

E-mail: sanmitra [DOT] roni [AT] gmail [DOT] com


Publications

Sanmitra Banerjee, Madhusudhan Mishra and Anirban Mukherjee; Segmentation and Detection of First and Second Heart Sounds (S1 and S2) using Variational Mode Decomposition, IEEE-EMBS Conference on Biomedical Engineering and Sciences, 03-08 Dec. 2016, Kuala Lumpur, Malaysia.

Subhadip Dey

Subhadip Dey is an M. Tech student. He is currently working on Gaussian Process-based Regression in Machine Learning.

E-mail: subhadipdey23071994 [AT] gmail [DOT] com

Google Scholar Profile: citation

Yash Murat

Yash Murat is an M. Tech student. He is currently working on Acoustic Array Signal Processing.

E-mail: ymurat2010 [AT] gmail [DOT] com


Visitors
Mr. Sagnik Dutta IIEST, Shibpur 16 May, 2014 - 30 Jun, 2014
Prof. Lalan Kumar IIT Delhi, India 09 Sep, 2016 - 09 Sep, 2016
Mr. Rahul Chakraborty Jadavpur University, India 20 May, 2014 - 11 Jul, 2014
Mr. Muzaffer Ahmed All India Institute of Medical Sciences, New Delhi, India 30 Apr, 2014 - 06 May, 2014

Previous Members
Previous Research Students

Santanu Ghorai

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 Applied Electronics & Instrumentation Engineering in Heritage Institute of Technology, Kolkata.

E-mail: santanughorai74 [AT] gmail [DOT] com

Google Scholar Profile: citation


Publications

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.

Surajit Panja

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 ECE in Indian Institute of Information Technology (IIIT) Guwahati.

E-mail: surajit[DOT]panja [AT] gmail [DOT] com

Google Scholar Profile: citation


Publications

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.

Surajit Panja, Sourav Patra, Anirban Mukherjee, Madhumita Basu, Sanghamitra Sengupta and Pranab K. Dutta; Feedback Linearization and Optimal Control-based Approach for Steering Steady-States of Nonlinear Biochemical Networks, IEEE INDICON, Kochi, India, Dec. 7-9, 2012.

Previous Graduate Students

Aniruddha Maiti

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.
Mr. Aniruddha Maiti is now a research assistant at Temple University, Philadelphia, USA and pursuing his doctoral research in Machine Learning.

E-mail: aniruddha.maiti87 [AT] gmail [DOT] com


Publications

Aniruddha Maiti, S. Ghorai and Anirban Mukherjee; A Multi-Fold String Kernel for Sequence Classification, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Jul. 22-29, 2015, Milano, Italy.

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 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.)

Aniruddha Maiti and Anirban Mukherjee; Expectation Maximization in Random Projected Spaces to Find Motifs in Genome Sequences, IEEE International Conference on Electronics, Communication, and Instrumentation, Jan. 16-17, 2014, Kolkata.

Atindra Kanti Mandal

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

Ramakanth Reddy

Ramakanth Reddy was a Dual-degree M. Tech student in 2015. He worked on prediction of Bayesian Network.

E-mail: ramakanth.1729 [AT] gmail [DOT] com


Publications

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.

Ramakanth Reddy, P. R. Muduli and Anirban Mukherjee; Compressed Sensing of Respiratory Signals Promoting Joint-Sparsity, 22nd National Conference on Communications, 4-6 March, 2016, IIT Guwahati, India.

Sachin Tom John

Sachin Tom John was an M. Tech student in 2016. He worked on fetal ECG acquisition and its applicability in the Point-Of-Care (POC) settings.

E-mail: sachintomjohn [AT] rediffmail [DOT] com


Publications

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.
More Information.

Previous Under-Graduate Students

Rakesh Reddy Gunukula

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


Publications

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.