Shantipriya PARIDA

Short Biography

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, Machine Translation, and NLP resource development for low resource and indigineous languages. Before Idiap, I was working as a Post-doctoral researcher with Prof. Ondřej Bojar at Charles University, Prague working on Machine Translation, and Deep Learning. I have expertise in machine learning, AI, computational neuroscience, product development, system/solution architect. Co-organizer for Workshop on Asian Translation WAT2019, WAT2020, and WAT2021. Along with Prof. Ondřej Bojar organised the WAT2019 Multimodal-Translation Task, WAT2020 Multimodal-Translation Task, and WAT2020 Indic Odia-English Translation Task. Program committee member for the LREC 2020 Workshop on Indian Language Data: Resources and Evaluation (WILDRE), ICON 2020, LowResMT2020, LowResMT2021, MMTLRL-2021, EMNLP2021, and Automin2021 . Now we are working on our edited NLP book titled "Natural Language Processing in Healtchcare: A Special Focus on Low Resource Languages".



Postdoc in Neural Machine Translation under guidance of Prof. Ondřej Bojar at Institute of Formal and Applied Linguistic, Faculty of Physics & Mathematics, Charles University, Prague.

Ph.D. in Computer Science, Utkal University, INDIA, 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.

Master of Technology (First Class with Honors) in Computer Science, School of Mathematics Statistics & Computer Science, Utkal University, INDIA 2004. DISSERTATION TITLE : “COMBINATION OF CLASSIFIERS”, completed from Machine Intelligence Unit, Indian Statistical Institute under the guidance of Prof. Ashish Ghosh.

Master of Computer Application (First Class), Utkal University, 2001.

Bachelor of Science, Utkal University, 1998.

Professional Experience

Worked as System Architect in Huawei Technologies India Pvt. Ltd, Bangalore, INDIA from July 2007 to Jan 2018.

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

Worked as Senior Software Engineer in Torry Harris Business Solutions, Bangalore, INDIA from 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.

Worked as Software Engineer in ANZ Information Technology, Bangalore, INDIA from Oct 2004 to Apr 2005.

  • Developing banking solution using UNIX, C++.


Selected Conference and Jornal Paper

  • E. Villatoro-Tello, S. Parida, S. Kumar, & P. Motlicek (2021). " Applying Attention-Based Models for Detecting Cognitive Processes and Mental Health Conditions ". Cognitive Computation, 2021 [paper]
  • S. Parida, S. Panda, A. R. Dash, E. Villatoro-Tello, A. S. Dogruoz, R. M. Ortega-Mendoza, A. Hernandez, 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, 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]
  • 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]
  • 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, S. R. Dash, O. Bojar, P. Motlicek, P. Pattnaik, & D. K. Mallick, (2020, May). "OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation". In Proceedings of the WILDRE5–5th Workshop on Indian Language Data: Resources and Evaluation (LREC2020) (pp. 14-19). [paper]
  • S. Parida, O. Bojar, P. Motlicek. "Idiap NMT System for WAT 2019 Multimodal Translation Task". In Proceedings of the 6th Workshop on Asian Translation, pp. 175-180, 2019.
  • 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". In Proceedings of the 4th edition of the Swiss Text Analytics Conference (SwissText 2019), 2019.
  • S. Parida, O. Bojar, S. Dash. "Hindi Visual Genome: A Dataset for English-to-Hindi Machine Translation". CICLing 2019. Corpus download link:
  • S. Parida, O. Bojar, S. Dash. "OdiEnCorp: Odia-English and Odia-Only Corpus for Machine Translation". In Proceedings of the Third International Conference on Smart Computing & Informatics (SCI) 2018, pp. 495-504, Springer, 2020. Corpus download link:
  • 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 :
  • 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.
  • 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 subjects". Journal of integrative neuroscience, 15(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.


  • OdiEnCorp2.0 (Odia-English parallel corpus)
  • OdiEnCorp 1.0 (Odia-English parallel and Odia monolingual corpus)
  • Hindi Visual Genome 1.1 (English to Hindi Multimodal dataset)
  • Malayalam Visual Genome 1.1 (English to Malayalam Multimodal dataset)
  • English->Hindi Machine Translation System
  • Odia-NLP-Resource-Catalog
  • Personal home page


    Tel: +41277217449
    Office: 307-1