Publications


2021

  1. TLDKS
    Reducing the cost of aggregation in crowdsourcing.
    Rituraj Singh, Loı̈c Hélouët, and Zoltan Miklos

    In Transactions on Large-Scale Data and Knowledge-Centered Systems 2021.

    Crowdsourcing is a way to solve problems that need human contribution. Crowdsourcing platforms distribute replicated tasks to workers, pay them for their contribution, and aggregate answers to produce a reliable conclusion. A fundamental problem is to infer a correct answer from the set of returned results. Another challenge is to obtain a reliable answer at a reasonable cost: unlimited budget allows hiring experts or large pools of workers for each task but a limited budget forces to use resources at best. Last, crowdsourcing platforms have to detect and ban malevolent users (a.k.a. spammers) to achieve good accuracy of their answers. This paper considers crowdsourcing of simple boolean tasks. We first define a probabilistic inference technique, that considers difficulty of tasks and expertise of workers when aggregating answers. We then propose CrowdInc, a greedy algorithm that reduces the cost needed to reach a consensual answer. CrowdInc distributes resources dynamically to tasks according to their difficulty. The algorithms solves batches of simple tasks in rounds that estimate workers expertize, tasks dificulty, and synthesize a plausible aggregated conclusion and a confidence score using Expectation Maximization. The synthesized values are used to decide whether more workers should be hired to increase confidence in synthesized answers. We show on several benchmarks that CrowdInc achieves good accuracy, reduces costs, and we compare its performance to existing solutions. We then use the estimation of CrowdInc to detect spammers, and study the impact of spammers on costs and accuracy.
  2. PhD Thesis
    Data Centric Workflows for Crowdsourcing Application.
    Rituraj Singh,

    2021.

    PDF Video
    Crowdsourcing uses human intelligence to solve tasks which are still difficult for machines. Tasks at existing crowdsourcing platform are batches of relatively simple microtasks. However, real-world problems are often more difficult than micro-tasks. They require data collection, organization, pre-processing, analysis, and synthesis of results. In this thesis, we study how to specify complex crowdsourcing tasks and realize them with the helpof existing crowdsourcing platforms. The first contribution of this thesis is a complex workflows model that provides high-level constructs to describe a complex task through orchestration of simpler tasks. We provide algorithms to check termination and correctness of a complex workflow for a subset of the language (these questions are undecidable in the general case). A well-known drawback of crowdsourcing is that human answers might be wrong. To leverage this problem, crowdsourcing platforms replicate tasks, and forge a final trusted answer out of the produced results. Replication increases quality of data, but it is costly. The second contribution of this thesis is a set of aggregation techniques where merging of answers is realized using Expectation Maximization, and replication of tasks is performed online after considering the confidence estimated for aggregated data. Experimental results show that these techniques allow to aggregate the returned answers while achieving a good trade-off between cost and data quality, both for the realization of a batches of microtasks, and of complex workflow.
  3. PetriNets
    Cost and Quality in Crowdsourcing Workflows.
    Loı̈c Hélouët, Zoltan Miklos, and Rituraj Singh

    In International Conference on Applications and Theory of Petri Nets and Concurrency 2021.

2020

  1. Patent
    Cascaded binary classifier for identifying rhythms in a single-lead electrocardiogram (ECG) signal.
    Shreyasi Datta, PURI Chetanya, Ayan Mukherjee, Rohan Banerjee, Anirban Dutta Choudhury, Arijit Ukil, Soma Bandyopadhyay, Arpan Pal, Sundeep Khandelwal, Rituraj Singh, and others

    2020.

  2. PetriNets
    Data centric workflows for crowdsourcing.
    Pierre Bourhis, Loı̈c Hélouët, Zoltan Miklos, and Rituraj Singh

    In International Conference on Applications and Theory of Petri Nets and Concurrency 2020.

  3. Patent
    Anomaly detection by self-learning of sensor signals.
    Soma Bandyopadhyay, Arijit Ukil, Rituraj Singh, PURI Chetanya, Arpan Pal, and CA Murthy

    2020.

  4. Patent
    Cascaded binary classifier for identifying rhythms in a single-lead electrocardiogram (ECG) signal.
    Shreyasi Datta, PURI Chetanya, Ayan Mukherjee, Rohan Banerjee, Anirban Dutta Choudhury, Arijit Ukil, Soma Bandyopadhyay, Arpan Pal, Sundeep Khandelwal, Rituraj Singh, and others

    2020.

  5. ICWS
    Reducing the Cost of Aggregation in Crowdsourcing.
    Rituraj Singh, Loı̈c Hélouët, and Zoltán Miklós

    In International Conference on Web Services 2020.

  6. Patent
    Anomaly detection by self-learning of sensor signals.
    Soma Bandyopadhyay, Arijit Ukil, Rituraj Singh, PURI Chetanya, Arpan Pal, and CA Murthy

    2020.

2019

  1. Patent
    Method and system for physiological parameter derivation from pulsating signals with reduced error.
    Soma Bandyopadhyay, Arijit Ukil, PURI Chetanya, Rituraj Singh, Arpan Pal, CA Murthy, and Kayapanda Mandana

    2019.

  2. Journal
    Detection of atrial fibrillation and other abnormal rhythms from ECG using a multi-layer classifier architecture.
    Ayan Mukherjee, Anirban Dutta Choudhury, Shreyasi Datta, Chetanya Puri, Rohan Banerjee, Rituraj Singh, Arijit Ukil, Soma Bandyopadhyay, Arpan Pal, and Sundeep Khandelwal

    In Physiological measurement 2019.

  3. HAL
    Data Centric Workflows for Crowdsourcing.
    Pierre Bourhis, Loı̈c Hélouët, Rituraj Singh, and Zoltán Miklós

    In 2019.

  4. Patent
    Synthetic rare class generation by preserving morphological identity.
    Arijit Ukil, Soma Bandyopadhyay, PURI Chetanya, Rituraj Singh, and Arpan Pal

    2019.

  5. Patent
    Generalized one-class support vector machines with jointly optimized hyperparameters thereof.
    Arijit Ukil, Soma Bandyopadhyay, PURI Chetanya, Rituraj Singh, and Arpan Pal

    2019.

  6. patent
    Method and system for physiological parameter derivation from pulsating signals with reduced error.
    Soma Bandyopadhyay, Arijit Ukil, PURI Chetanya, Rituraj Singh, Arpan Pal, CA Murthy, and Kayapanda Mandana

    2019.

  7. Patent
    Method and system for physiological parameter derivation from pulsating signals with reduced error.
    Soma Bandyopadhyay, Arijit Ukil, PURI Chetanya, Rituraj Singh, Arpan Pal, CA Murthy, and Kayapanda Mandana

    2019.

  8. patent
    Systems and methods for detecting anomaly in a cardiovascular signal using hierarchical extremas and repetitions.
    Soma Bandyopadhyay, Arijit Ukil, PURI Chetanya, Rituraj Singh, Arpan Pal, and C A Murthy

    2019.

  9. patent
    Method and system for pattern recognition in a signal using morphology aware symbolic representation.
    Soma Bandyopadhyay, Arijit Ukil, PURI Chetanya, Rituraj Singh, Arpan Pal, and C A Murthy

    2019.

  10. Patent
    Method and system for joint selection of a feature subset-classifier pair for a classification task.
    SAHU Ishan, Ayan Mukherjee, Arijit Ukil, Soma Bandyopadhyay, PURI Chetanya, Rituraj Singh, Arpan Pal, and Rohan Banerjee

    2019.

2018

  1. Patent
    Noisy signal identification from non-stationary audio signals.
    Arijit Ukil, Soma Bandyopadhyay, PURI Chetanya, Arpan Pal, Rituraj Singh, Ayan Mukherjee, and Debayan Mukherjee

    2018.

  2. IJCNN
    AutoModeling: Integrated Approach for Automated Model Generation by Ensemble Selection of Feature Subset and Classifier.
    Arijit Ukil, Ishan Sahu, Chetanya Puri, Ayan Mukherjee, Rituraj Singh, Soma Bandyopadhyay, and Arpan Pal

    In 2018 International Joint Conference on Neural Networks (IJCNN) 2018.

  3. EMBC
    Pattern Analysis in Physiological Pulsatile Signals: An Aid to Personalized Healthcare.
    Soma Bandyopadhyay, Arijit Ukil, Chetanya Puri, Rituraj Singh, Arpan Pal, and CA Murthy

    In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2018.

  4. Patent
    System and method for physiological monitoring.
    Arijit Ukil, Soma Bandyopadhyay, PURI Chetanya, Rituraj Singh, Arpan Pal, and Debayan Mukherjee

    2018.

  5. Arxiv
    Class Augmented Semi-Supervised Learning for Practical Clinical Analytics on Physiological Signals.
    Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, and Arpan Pal

    In arXiv preprint arXiv:1812.07498 2018.

  6. ICASSP
    ICASSP 2018.
    Chetanya Puri, Arijit Ukil, Soma Bandyopadhyay, Rituraj Singh, and Arpan Pal

    In 2018.

  7. ICASSP
    Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection Using Phonocardiogarm Signals.
    Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, and Arpan Pal

    In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2018.

2017

  1. ICASSP
    Heartmate: automated integrated anomaly analysis for effective remote cardiac health management.
    Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal, and Ayan Mukherjee

    In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2017.

  2. EMBC
    Analysis of phonocardiogram signals through proactive denoising using novel self-discriminant learner.
    Chetanya Puri, Rituraj Singh, Soma Bandyopadhyay, Arijit Ukil, and Ayan Mukherjee

    In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2017.

  3. CinC
    Identifying normal, AF and other abnormal ECG rhythms using a cascaded binary classifier.
    Shreyasi Datta, Chetanya Puri, Ayan Mukherjee, Rohan Banerjee, Anirban Dutta Choudhury, Rituraj Singh, Arijit Ukil, Soma Bandyopadhyay, Arpan Pal, and Sundeep Khandelwal

    In 2017 Computing in cardiology (cinc) 2017.

  4. IJCAI
    On Solving the Class Imbalance Problem for Clinical Decision Improvement Using Heart Sound Signals.
    Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, and Arpan Pal

    In Proceedings of the IJCAI 2017 Workshop on Learning in the Presence of Class Imbalance and Concept Drift (LPCICD’17) 2017.

  5. eHealth
    CardioFit: Affordable Cardiac Healthcare Analytics for Clinical Utility Enhancement.
    Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal, and KM Mandana

    2017.

2016

  1. ISCC
    SensIPro: Smart sensor analytics for Internet of things.
    Soma Bandyopadhyay, Arijit Ukil, Chetanya Puri, Rituraj Singh, Tulika Bose, and Arpan Pal

    In 2016 IEEE Symposium on Computers and Communication (ISCC) 2016.

  2. EMBC
    An unsupervised learning for robust cardiac feature derivation from PPG signals.
    Soma Bandyopadhyay, Arijit Ukil, Chetanya Puri, Rituraj Singh, Arpan Pal, KM Mandana, and CA Murthy

    In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2016.

  3. SenSys
    3S: Sensing Sensor Signal: Demo Abstract.
    Soma Bandyopadhyay, Arijit Ukil, Rituraj Singh, Chetanya Puri, Arpan Pal, and CA Murthy

    In Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM 2016.

  4. ICACCI
    Efficient user assignment in crowd sourcing applications.
    Akash Yadav, Ashok Singh Sairam, and Rituraj Singh

    In 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) 2016.

  5. CinC
    Classification of normal and abnormal heart sound recordings through robust feature selection.
    Chetanya Puri, Arijit Ukil, Soma Bandyopadhyay, Rituraj Singh, Arpan Pal, Ayan Mukherjee, and Debayan Mukherjee

    In 2016 Computing in Cardiology Conference (CinC) 2016.

  6. IHWTS
    iCarMa: Inexpensive Cardiac Arrhythmia Management–An IoT Healthcare Analytics Solution.
    Chetanya Puri, Arijit Ukil, Soma Bandyopadhyay, Rituraj Singh, Arpan Pal, and Kayapanda Mandana

    In Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems 2016.

2015

  1. SenSys
    IAS: Information analytics for sensors.
    Soma Bandyopadhyay, Arijit Ukil, Chetanya Puri, Arpan Pal, Rituraj Singh, and Tulika Bose

    In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems 2015.