Patents by Inventor Ayan Mukherjee
Ayan Mukherjee has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20230404461Abstract: State of art techniques hardly provide data balancing for multi-label multi-class data. Embodiments of the present disclosure provide a method and system for identifying cardiac abnormality in multi-lead ECGs using a Hybrid Neural Network (HNN) with fulcrum based data re-balancing for data comprising multiclass-multilabel cardiac abnormalities. The fulcrum based dataset re-balancing disclosed enables maintaining natural balance of the data, control the re-sample volume, and still support the lowly represented classes there by aiding proper training of the DL architecture. The HNN disclosed by the method utilizes a hybrid approach of pure CNN, a tuned-down version of ResNet, and a set of handcrafted features from a raw ECG signal that are concatenated prior to predicting the multiclass output for the ECG signal. The number of features is flexible and enables adding additional domain-specific features as needed.Type: ApplicationFiled: June 6, 2023Publication date: December 21, 2023Applicant: Tata Consultancy Services LimitedInventors: VARSHA SHARMA, AYAN MUKHERJEE, MURALI PODUVAL, SUNDEEP KHANDELWAL, ANIRBAN DUTTA CHOUDHURY, CHIRAYATA BHATTACHARYYA
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Patent number: 11494415Abstract: A method and system for a feature subset-classifier pair for a classification task. The classification task corresponds to automatically classifying data associated with a subject(s) or object(s) of interest into an appropriate class based on a feature subset selected among a plurality of features extracted from the data and a classifier selected from a set of classifier types. The method proposed includes simultaneously determining the feature subset-classifier pair based on a relax-greedy {feature subset, classifier} approach utilizing sub-greedy search process based on a patience function, wherein the feature subset-classifier pair provides an optimal combination for more accurate classification. The automatic joint selection is time efficient solution, effectively speeding up the classification task.Type: GrantFiled: May 23, 2019Date of Patent: November 8, 2022Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Ishan Sahu, Ayan Mukherjee, Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal, Rohan Banerjee
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Patent number: 11168084Abstract: The present invention provides novel purine based compounds of formula 1, method of preparation of purine based compounds and its composition useful for inhibiting signalling through Toll-like receptors. These compounds are useful in inhibiting immune stimulation involving toll-like receptor 9 (TLR9). These can be used in treatment of autoimmune disease and inflammation where aberrant activation of TLR9 plays role.Type: GrantFiled: November 5, 2018Date of Patent: November 9, 2021Assignee: Council of Scientific & Industrial ResearchInventors: Arindam Talukdar, Dipyaman Ganguly, Ayan Mukherjee, Barnali Paul, Oindrila Rahaman, Biswajit Kundu, Swarnali Roy, Raychaudhuri Deblina
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Publication number: 20210246128Abstract: The invention described herein relates to the compounds of Formula I for treating diseases and disorders for which inhibition or modulation of the topoisomerase I enzyme produces a physiologically beneficial response, in particular for the treatment of breast cancer. Also provided is the process of preparing compounds of Formula I.Type: ApplicationFiled: May 24, 2019Publication date: August 12, 2021Inventors: Arindam TALUKDAR, Benu Brata DAS, Biswajit KUNDU, Subhendu K. DAS, Chowdhuri Srijita PAUL, Dipayan SARKAR, Sourav PAL, Debomita BHATTACHARYA, Ayan MUKHERJEE, Subhajit ROY
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Publication number: 20200347062Abstract: The present invention provides novel purine based compounds of formula 1, method of preparation of purine based compounds and its composition useful for inhibiting signalling through Toll-like receptors. These compounds are useful in inhibiting immune stimulation involving toll-like receptor 9 (TLR9).Type: ApplicationFiled: November 5, 2018Publication date: November 5, 2020Inventors: Arindam TALUKDAR, Dipyaman GANGULY, Ayan MUKHERJEE, Barnali PAUL, Oindrila RAHAMAN, Biswajit KUNDU, Swarnali ROY, Raychaudhuri DEBLINA
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Patent number: 10750968Abstract: Current technologies analyze electrocardiogram (ECG) signals for a long duration, which is not always a practical scenario. Moreover the current scenarios perform a binary classification between normal and Atrial Fibrillation (AF) only, whereas there are many abnormal rhythms apart from AF. Conventional systems/methods have their own limitations and may tend to misclassify ECG signals, thereby resulting in an unbalanced multi-label classification problem.Type: GrantFiled: January 30, 2018Date of Patent: August 25, 2020Assignee: Tata Consultancy Services LimitedInventors: Shreyasi Datta, Chetanya Puri, Ayan Mukherjee, Rohan Banerjee, Anirban Dutta Choudhury, Arijit Ukil, Soma Bandyopadhyay, Arpan Pal, Sundeep Khandelwal, Rituraj Singh
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Patent number: 10664698Abstract: Development of sensor data based descriptive and prescriptive system involves machine learning tasks like classification and regression. Any such system development requires the involvement of different stake-holders for obtaining features. Such features typically obtained are not interpretable for 1-D sensor signals. Embodiments of the present disclosure provide systems and methods that perform signal analysis for features extraction and interpretation thereof wherein input is raw signal data where origin of a feature is traced to signal data, and mapped to domain/application knowledge. Feature(s) are extracted using deep learning network(s) and machine learning (ML) model(s) are implemented for sensor data analysis to perform causality analysis for prognostics. Layer(s) (say last layer) of Deep Network(s) contains the automatically derived features that can be used for ML tasks.Type: GrantFiled: February 21, 2018Date of Patent: May 26, 2020Assignee: Tata Consultancy Services LimitedInventors: Snehasis Banerjee, Tanushyam Chattopadhyay, Ayan Mukherjee
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Patent number: 10662177Abstract: The present invention relates to small molecule 4-(piperazin-1-yl)quinazolin-2-amino compounds with formula (I) useful for inhibiting signalling by certain toll-like receptors (TLRs), especially TLR9. Toll-like receptors (TLRs) are members of the larger family of evolutionarily conserved pattern recognition receptors which are critical first line of defense for self-nonself discrimination by the host immune response. Aberrant TLR9 activation is implicated in autoreactive inflammation in different autoimmune diseases. The invention depicts compounds with formula (I), composition and methods can be used in a number of clinical applications, including as pharmaceutical agents and methods for treating conditions involving unwanted immune activity due to TLR9 activation.Type: GrantFiled: March 21, 2017Date of Patent: May 26, 2020Assignee: Council of Scientific & Industrial ResearchInventors: Arindam Talukdar, Dipyaman Ganguly, Barnali Paul, Ayan Mukherjee, Shounak Roy, Swarnali Roy, Amrit Raj Ghosh, Roopkatha Bhattacharya, Oindrila Rahaman, Biswajit Kundu
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Publication number: 20200012941Abstract: The disclosure herein describes a method and a system for generating hybrid learning techniques. The hybrid learning technique refers to learning techniques that are a combination a plurality of techniques that include of deep learning, machine learning and signal processing to enable a rich feature space representation and classifier construction. The generation of the hybrid learning techniques also considers influence/impact of domain constraints that include business requirements and computational constraints, while generating hybrid learning techniques. Further from the plurality hybrid learning techniques a single hybrid learning technique is chosen based on performance matrix based on optimization techniques.Type: ApplicationFiled: July 9, 2019Publication date: January 9, 2020Applicant: Tata Consultancy Services LimitedInventors: Arijit UKIL, Soma BANDYOPADHYAY, Pankaj MALHOTRA, Arpan PAL, Lovekesh VIG, Gautam SHROFF, Tulika BOSE, Ishan SAHU, Ayan MUKHERJEE
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Publication number: 20190361919Abstract: A method and system for a feature subset-classifier pair for a classification task. The classification task corresponds to automatically classifying data associated with a subject(s) or object(s) of interest into an appropriate class based on a feature subset selected among a plurality of features extracted from the data and a classifier selected from a set of classifier types. The method proposed includes simultaneously determining the feature subset-classifier pair based on a relax-greedy {feature subset, classifier} approach utilizing sub-greedy search process based on a patience function, wherein the feature subset-classifier pair provides an optimal combination for more accurate classification. The automatic joint selection is time efficient solution, effectively speeding up the classification task.Type: ApplicationFiled: May 23, 2019Publication date: November 28, 2019Applicant: Tata Consultancy Services LimitedInventors: Ishan SAHU, Ayan MUKHERJEE, Arijit UKIL, Soma BANDYOPADHYAY, Chetanya PURI, Rituraj SINGH, Arpan PAL, Rohan BANERJEE
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Publication number: 20190138806Abstract: Development of sensor data based descriptive and prescriptive system involves machine learning tasks like classification and regression. Any such system development requires the involvement of different stake-holders for obtaining features. Such features typically obtained are not interpretable for 1-D sensor signals. Embodiments of the present disclosure provide systems and methods that perform signal analysis for features extraction and interpretation thereof wherein input is raw signal data where origin of a feature is traced to signal data, and mapped to domain/application knowledge. Feature(s) are extracted using deep learning network(s) and machine learning (ML) model(s) are implemented for sensor data analysis to perform causality analysis for prognostics. Layer(s) (say last layer) of Deep Network(s) contains the automatically derived features that can be used for ML tasks.Type: ApplicationFiled: February 21, 2018Publication date: May 9, 2019Applicant: Tata Consultancy Services LimitedInventors: Snehasis BANERJEE, Tanushyam CHATTOPADHYAY, Ayan MUKHERJEE
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Publication number: 20190092758Abstract: The present invention relates to small molecule4-(piperazin-1-yl)quinazolin-2-amino compounds with formula (I) useful for inhibiting signalling by certain toll-like receptors (TLRs), especially TLR9. Toll-like receptors (TLRs) are members of the larger family of evolutionarily conserved pattern recognition receptors which are critical first line of defence for self-nonself discrimination by the host immune response. Aberrant TLR9 activation is implicated in autoreactive inflammation in different autoimmune diseases. The invention depicts compounds with formula (I), composition and methods can be used in a number of clinical applications, including as pharmaceutical agents and methods for treating conditions involving unwanted immune activity due to TLR9 activation.Type: ApplicationFiled: March 21, 2017Publication date: March 28, 2019Inventors: Arindam Talukdar, Dipyaman Ganguly, Barnali Paul, Ayan Mukherjee, Shounak Roy, Swarnali Roy, Amrit Raj Ghosh, Roopkatha Bhattacharya, Oindrila Rahaman, Biswajit Kundu
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Publication number: 20190082988Abstract: Current technologies analyze electrocardiogram (ECG) signals for a long duration, which is not always a practical scenario. Moreover the current scenarios perform a binary classification between normal and Atrial Fibrillation (AF) only, whereas there are many abnormal rhythms apart from AF. Conventional systems/methods have their own limitations and may tend to misclassify ECG signals, thereby resulting in an unbalanced multi-label classification problem.Type: ApplicationFiled: January 30, 2018Publication date: March 21, 2019Applicant: Tata Consultancy Services LimitedInventors: Shreyasi DATTA, Chetanya PURI, Ayan MUKHERJEE, Rohan BANERJEE, Anirban Dutta CHOUDHURY, Arijit UKIL, Soma BANDYOPADHYAY, Arpan PAL, Sundeep KHANDELWAL, Rituraj SINGH
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Patent number: 9978392Abstract: Traditionally known classification methods of non-stationary physiological audio signals as noisy and clean involve human intervention, may involve dependency on particular type of classifier and further analyses is carried out on classified clean signals. However, in non-stationary audio signals a major portion may end up being classified as noisy and hence may get rejected which may cause missing of intelligence which could have been derived from lightly noisy audio signals that may be critical. The present disclosure enables automation of classification based on auto-thresholding and statistical isolation wherein noisy signals are further classified as highly noisy and lightly noisy through continuous dynamic learning.Type: GrantFiled: March 10, 2017Date of Patent: May 22, 2018Assignee: Tata Consultancy Services LimitedInventors: Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Arpan Pal, Rituraj Singh, Ayan Mukherjee, Debayan Mukherjee
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Publication number: 20180075861Abstract: Traditionally known classification methods of non-stationary physiological audio signals as noisy and clean involve human intervention, may involve dependency on particular type of classifier and further analyses is carried out on classified clean signals. However, in non-stationary audio signals a major portion may end up being classified as noisy and hence may get rejected which may cause missing of intelligence which could have been derived from lightly noisy audio signals that may be critical. The present disclosure enables automation of classification based on auto-thresholding and statistical isolation wherein noisy signals are further classified as highly noisy and lightly noisy through continuous dynamic learning.Type: ApplicationFiled: March 10, 2017Publication date: March 15, 2018Applicant: Tata Consultancy Services LimitedInventors: Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Arpan Pal, Rituraj Singh, Ayan Mukherjee, Debayan Mukherjee