• Shantipriya Parida

    ଶାନ୍ତିପ୍ରିୟ ପରିଡା

  • About Me

     

    I am working as a post-doctoral researcher with Prof. Petr Motlicek at Idiap Research Institute since Feb 2019. My current research includes Text Summarization, Topic Detection, Fake News Detection, Dialect Detection, and Deep Learning. Before this, I was doing my research on Neural Machine Translation, NLP, Deep Learning under the supervision of Prof. Ondřej Bojar at the Institute of Formal and Applied Linguistics, Charles University in Prague. I have expertise in machine learning, AI, computational neuroscience, product development, system/solution architect.

     

    Co-organizer for Workshop on Asian Translation WAT2019 and WAT2020. Along with Prof. Ondřej Bojar organized the WAT2019 Multimodal-Translation Task. Program committee member for the LREC 2020 Workshop on Indian Language Data: Resources and Evaluation (WILDRE).

     

    Feel free to contact me for any possible research collaboration in the research areas of mutual interest.

     

    Background:

    I am from the beautiful town Umerkote, in the district of Nabarangpur, state Odisha, an eastern Indian state. I spent most of my life in these cities: Bhubaneswar, the capital of state Odisha and Bangalore, the IT capital of India.

     

    Family:

    My family includes my father Mr. Bijay Kumar Parida (retired central govt service, spent most of the time in social service for the disabled persons), my mother late Mrs. Charulata Parida (was a loving and kind mother and the reason I'm where I am today. recently lost her, worst pain in my life), my dear wife Mrs. Manaswini Mohapatra and my sweet and cute daughter Miss. Aishani Parida (Renee). I have two brothers Mr. Satyabrata Parida, Mr. Dharmaraj Parida, and sister Mrs. Reena Parida. Also, I have many lovely and sweet cousin brothers/sisters, uncles, and aunties. Although we are based far from each other and placed in different countries, still in touch (thanks to technology, FB, WhatsApp :-)

     

    Interest:

    I like to travel, explore new places (historical places fascinates me.), enjoy listening to music, watching movies, try cooking, writing. I always wanted to do something for preserving nature and volunteer for animal welfare.

  • “May all beings everywhere be happy and free, and may the thoughts, words, and actions of my own life contribute in some way to that happiness and to that freedom for all.”

  • CURRENT POSITION

    Postdoctoral Researcher 

    Idiap Research Institute, Martigny, Switzerland

    Feb 2019 – ...

    NLP, Deep Learning, Text Summarization

  • Education 

    Charles University

    Faculty of Mathematics & Physics

    Institute of Formal and Applied Linguistics

    https://ufal.mff.cuni.cz/

    Postdoc (01.2018-01.2019)

    Neural Machine Translation, Natural Language Processing, Deep Learning.

     

    Supervisor : Dr. Ondřej Bojar

    Utkal University

    https://www.utkaluniversity.nic.in/

    Ph.D. Computer Science

    2016

    THESIS TITLE: “CLASSIFYING INSTANTANEOUS COGNITIVE STATES BASED ON MACHINE LEARNING APPROACH”,

     

    under the guidance of Dr. Satchidananda Dehuri, Reader F. M. University, Balasore, Odisha, INDIA.

    Utkal University

     

    Master of Technology (First Class with Honors) in Computer Science

    2004

    DISSERTATION TITLE : “COMBINATION OF CLASSIFIERS”,

     

    completed from Machine Intelligence Unit, Indian Statistical Institute (ISI, Kolkata) under the guidance of Prof. Ashish Ghosh.

    Utkal University

     

    Master of Computer Application (First Class)

    2001.

    PROJECT TITLE : “Developing a Software for Estimating Cumulative Fatigue Damage Using Rainflow Cycle Count ”

     

    completed from National Aerospace Lab, Bangalore, India under the guidance of Prof. Basant Kumar Parida.

    Utkal University

    Bachelor of Science (BSc)

    1998

    Physics, Chemistry and Mathematics

  • Experiences

    Professional Experience

    Huawei Technologies India Pvt. Ltd.

    June 2007-Jan 2017

    System Architect

    • Understanding customer requirements, designing IPTV/Mobile broadband solution.
    • Participating in Bidding/PostBid phase, conducting customer workshop, CTO level presentation.
    • Industry trend analysis, competitor analysis, white paper preparation and publication.

     

    Torry Harris Business Solution

    May 2005 to July 2007

    • Team leader for development and L3 support team for a Telecom Fraud Management Product owned by a UK based Telecom Operator.
    • Development using UNIX, C++, Shell Scripting, AWK/SED.

    ANZ Information Technology

    Oct 2004 to Apr 2005

    Developing banking solution using UNIX, C++.

  • Skills

    Skill Set

    Research Interest

    • Neural Machine Translation
    • Deep Learning
    • Computational Neuroscience
    • Artificial Intelligence
    • Machine Learning

    Reviewer

    • Journal of Integrative Neuroscience
    • Journal of Central South University,
    • Artificial Intelligence in Medicine
    • The world journal of Biological Psychiatry
    • IEEE Access
    • MAKE
    • IEEE TVLSI
    • Sadhana

    System/Solution Architect

    • Designing IPTV/OTT/MBB solution
    • Participating in Bidding/PostBid phase, conducting customer workshop, CTO level presentation.
    • Industry trend analysis, competitor analysis, white paper preparation, publishing in journal.  

    Software Design/Development

    • Unix, C, C++, OOAD, UML (Unified Modeling Language), Shell script, AWK, SED,Python, Oracle,Big Data, Deep Learning, Tensorflow, NLP, Neural Machine Translation
    • Team Lead, Support Lead, low level design (telecom fraud management solution, NMS)

     

    Certification

    TM Forum Certified

     

    Membership

    • IEEE
    • EAMT
    • IACSIT
    • OITS

    Courses

    • “Intelligent System Programming” from Proficience, Indian Institute of Science (IISc, Bangalore)
    • “Project Management and Communication” from Proficience, Indian Institute of Science (IISc, Bangalore) 

    Honors & Award

    • Best SA Support Award
    • Best Bid Support Award
    • PDU Gold Medal Award for Best Design Specification
    • Spot Award

    Program Committee

    • ICON 2020
    • LowResMT2020
    • EMNP2021
    • WILDRE (LREC Workshop)
  • Publication

    Research Paper Publication List (Conference and Journal)

    Conference

    • S. Parida, S. Panda, A. R. Dash, E. Villatoro-Tello,  A. S. Doğruöz, R. M. Ortega-Mendoza, A. Hernández, Y. Sharma, P. Motlicek (2021). "Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution)". In Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericaSNLP), ACL Anthology, 2021. [paper]
    • S. Parida, P. Motlicek, A. R. Dash, S.R. Dash, S. P. Biswal, P. Pattnaik, & D. K. Mallick (2020). "ODIANLP's Participation in WAT2020 ". In Proceedings of the 7th Workshop on Asian Translation (WAT2020), ACL Anthology, 2020 . [paper]
    • M. Fabien, E. Villatoro-Tello, P. Motlicek, & S. Parida (2020). "BertAA: BERT fine-tuning for Authorship Attribution". In Proceedings of the 17th International Conference on Natural Language Processing, ICON2020. [paper]
    • S. Parida, E. Villatoro-Tello, S. Kumar, M. Fabien, & P. Motlicek (2020). "Detection of Similar Languages and Dialects Using Deep Supervised Autoencoders". In Proceedings of the 17th International Conference on Natural Language Processing, ICON2020. [paper]
    • S. Parida, E. Villatoro-Tello, S. Kumar, P. Motlicek, & Q. Zhan, (2020). "Idiap Submission to Swiss-German Language Detection Shared Task". In Proceedings of the 5th Swiss Text Analytics Conference (SwissText) & 16th Conference on Natural Language Processing (KONVENS). [paper]
    • E. Villatoro-Tello, S. Parida, S. Kumar, P. Motlicek, & Q. Zhan, (2020). "Idiap & UAM participation at GermEval 2020: Classification and Regression of Cognitive and Motivational Style from Text". In Proceedings of the GermEval 2020 Shared Task on the Classification and Regression of Cognitive and Motivational style from Text, 2020. [paper]
    • S. Parida, P. Motlicek. "Abstract Text Summarization: A Low Resource Challenge".  In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 5996-6000. 2019.
    • S. Parida, P. Motlicek. "Idiap Abstract Text Summarization System for German Text Summarization Task". Proceedings of the 4th edition of the Swiss Text Analytics Conference.
    • S. Parida, O. Bojar, S. Dash. "Hindi Visual Genome: A Dataset for English-to-Hindi Machine Translation". Computación y Sistemas, 23(4), 1499-1505.
    • S. Parida, O. Bojar, S. Dash. "OdiEnCorp: Odia-English and Odia-Only Corpus for Machine Translation".  In Smart Intelligent Computing and Applications, pp. 495-504. Springer, Singapore, 2020.
    • T. Kocmi, S. Parida,  O.Bojar. "CUNI NMT System for WAT 2018 Translation Tasks". In Proceedings of the 5th Workshop on Asian Translation (WAT2018), Hong Kong, China, December. Demo English-to-Hindi Translation URL Based on WAT 2018 Model: https://lindat.mff.cuni.cz/services/transformer/
    • S. Parida, O. Bojar. “Translating Short Segments with NMT: A Case Study in English-to-Hindi”. In Proceedings of the 21st Annual Conference of the European Association for Machine Translation, p. 229–238 Alacant, Spain, May 2018.
    • S. Parida, S. Dehuri & S.-B. Cho. “Neuro-Fuzzy Ensembler for Cognitive States Classification”, Advance Computing Conference (IACC 2014), pp. 1243-1247, IEEE, 2014.
    • S. Parida, S. Dehuri & S.-B. Cho.” Application of Genetic Algorithms and Gaussian Bayesian Approach in Pipeline for Cognitive State Classification”, Advance Computing Conference (IACC 2014), pp. 1237-1242, IEEE, 2014.
    • S.Parida & S. Dehuri. “A Review of Hybrid Techniques based on Machine Learning Approach in Cognitive Classification”, Soft Computing for Problem Solving (SocPros 2012), Springer AISC, vol. 236, pp. 659-666, 2014.
    • S. Parida, S. Dehuri & G.-N. Wang. “Genetic Algorithms Based Feature Selection for Cognitive State Classification Using Ensemble of Decision Trees”, In Proceedings of the International Conference on Vibration Problems (ICOVP 2013), pp. 1-10, 2013.
    • S. Parida & S. Dehuri. “A Study of Feature Selection Techniques for fMRI based  State Classification”, Advancements in the Era of Multi-Disciplinary Systems(AEMDS 2013), pp. 500-507, Elsevier, 2013.

    Journal

    • D. Panda, D. Panda, S. R. Dash, & S. Parida (2021). "Extreme Learning Machines with feature selection using GA for effective prediction of fetal heart disease: A Novel Approach". Informatica, 2021. [paper]
    • R. Sahu, S. R. Dash, L. A. Cacha, R. R. Poznanski, and S. Parida (2021). "Classifier Implementation for Spontaneous EEG Activity during Schizophrenic Psychosis". Computación y Sistemas, 2021. [paper]
    • R. Sahu, S.R. Dash, L. A. Cacha, R.R. Poznanski, & S. Parida (2020). "Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques". Journal of Integrative Neuroscience, 2020. [paper]
    • D. Panda, S.R. Dash, R. Ray, & S. Parida (2020). "Predicting the Causal Effect Relationship Between COPD and Cardio Vascular Diseases". Informatica, 2020. [paper]
    • E. Villatoro-Tello, S. Parida, P. Motlicek, & O. Bojar (2020). "Inferring Highly-dense Representations for Clustering Broadcast Media Content". The Prague Bulletin of Mathematical Linguistics (PBML), 2020. [paper]
    • L. A. Cacha, S. Parida, S. Dehuri, S. B. Cho, & R. R. Poznanski, A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjectsJournal of integrative neuroscience15(04), 593-606, 2016.
    • S. Parida, S. Dehuri & S.-B. Cho. “Machine Learning Approaches for Cognitive State Classification and Brain Activity Prediction: A Survey”, Current Bioinformatics, Bentham Science Publishers, vol. 10, pp. 344- 359, 2015.
    • S. Parida, S. Dehuri, S.-B. Cho, L. A. Cacha, & R. R. Poznanski. “A Hybrid Method for Classifying Cognitive States from fMRI data”, Journal of Integrative Neuroscience, World Scientific, vol. 14, pp. 355-368, 2015.
    • S. Parida & S. Dehuri. “Review of fMRI Data Analysis: A Special Focus on Classification”, International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 5, pp. 1-26, 2014.
    • S. Parida & S. Dehuri. “Applying Machine Learning Techniques for Cognitive State Classification”, International Journal of Computer Applications (IJCA), pp. 40-45, 2013.
    • Gupta, R, & S. Parida. “Challenges and Opportunities: Mobile Broadband”, International Journal of Future Computer and Communication, vol. 2, no. 6, pp. 660, IACSIT Press, 2013.

    Resource

    1. OdiEnCorp 2.0 (Odia-English parallel corpus)

     

    The released corpus is available freely for non-commercial research purpose at below link:

     

    http://hdl.handle.net/11234/1-3211

     

    2. OdiEnCorp 1.0 (Odia-English parallel and Odia monolingual corpus)

     

    The released corpus is available freely for non-commercial research purpose at below link:

     

    http://hdl.handle.net/11234/1-2879

     

    3. Hindi Visual Genome 1.0 (English to Hindi Multimodal dataset)

     

    The released corpus is available freely for non-commercial research purpose at below link:

     

    https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-2997

     

    4. Hindi Visual Genome 1.1 (English to Hindi Multimodal dataset)

     

    The released corpus is available freely for non-commercial research purpose at below link:

     

    https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-3267

     

    5. Malayalam Visual Genome 1.1 (English to Malayalam Multimodal dataset)

     

    The released corpus is available freely for non-commercial research purpose at below link:

     

    https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-3533

     

    6. English->Hindi Machine Translation System

     

    https://lindat.mff.cuni.cz/services/transformer/

     

    7. Odia-NLP-Resource-Catalog

     

    A catalog for Odia language NLP resources. Share among NLP researchers interested in Odia language NLP research. Welcome for any resource contribution for Odia language NLP research.

     

    https://github.com/shantipriyap/Odia-NLP-Resource-Catalog

     

     

    Invited Talk/Presentation

    • Presented at Institute of Mathematics and Application, Bhubaneswar, India Natural Language Processing Webinar on "Deep Learning Approaches for Natural Language Processing" on 1st May 2021. [ppt]
    • Presented at One Week Indo-German SPARC Symposium cum Workshop on “Recent Advances in Machine Translation”, (RAMT-2021) on "Multimodal Multilingual Corpus Development for Machine Translation" on 17th March 2021. [ppt] 
    • Presented at Odia Machine Learning Conference on "Odia Natural Language Processing Resource Development" on 4th October 2020. [ppt] [ppt1]
    • Presented at KIIT University Natural Language Processing Webinar on "Deep Learning Approaches for Natural Language Processing" on 25th July 2020. [ppt]
    • Presentation of our shared task paper "Idiap & UAM participation at GermEval 2020: Classification and Regression of Cognitive and Motivational Style from Text" at SwissText 2020 conference. Our team obtains the second position for the subtask2 Operant Motive Classification. [ppt
    • Presented our shared task paper "Idiap Submission to Swiss German Language Detection Shared Taskat SwissText 2020 conference. [ppt]
    • Presented our work with Prof. Petr Motlicek "Building a Text Summarization System in Multilingual Low Resource Settings" in European Commission (EC) and Crosslang organized workshop "Summarization – Key to Information Overload" on 28th May 2020. [ppt]
    • Presented our paper "OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation" at LREC 2020 Workshop (WILDRE5 - Workshop on Indian Language Data: Resources and Evaluation) on 24th May 2020 Online Presentation. [ppt]
    • Presented our Multimodal shared task overview at EMNLP 2019 Hongkong (WAT Workshop) on 4th Nov 2019. [ppt]
    • Delivered a knowledge-sharing presentation on "Machine Translation using Deep Learning and Python: A Case Study for Indian languages Hindi and Odia" during the two-day workshop on Python Programming and Internet of Things(WPPIoT) at KIIT University, Bhubaneswar, India. [ppt]

     

     

     

     

  • Blog/Travelogue

    Odia (also spelled Oriya) is an Indo-Aryan language spoken in the Indian state Odisha. Apart from Odisha, Odia has significant speaking populations in five neighboring states (Andhra Pradesh, Madhya Pradesh, West Bengal, Jharkhand, and Chhattisgarh) and one neighboring country (Bangladesh). Odia...
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