Awards and Honours

UWinnipeg Robin H. Farquhar Award for Excellence for Contributing to Self-Governance, 2026

2025-2026 UWinnipeg Outstanding Graduate Mentor, 2025

Member of NSERC Discovery Grants Committee EG (1507) 2023-2026

UW Merit Award for Exceptional Performance: 2022,2021,2018, 2017, 2010, 2009, 2008, 2003 and 1999

  • Keynote Talk IJCRS 2023 Int. Joint Conference on Rough Sets 2021
  • Keynote Talk KES, Intelligent Decision Technologies 2021
  • Plenary Talk 12th Int.Conf. on Soft Computing and Pattern Recognition, SoCPaR 2020
  • Elected Senior Member IRSS: 2016
  • Featured on NSERC media release, May 24 2003 for my research on Software Quality
  • Best paper Award at the AIRTC’98 Conference in Arizona, October 1998
  • Researcher of the Year, College Award, Idaho State University, 1994

    • Journals

  • Editor, EAAI Journal, Elsevier (term ended June, 2022)
  • Managing Editor, Transactions on Rough Sets, Springer (2004-2025)

    • Conferences

    Progran Co-Chair MIWAI 2026
    Halifax, Canada

    Organizing Co-Chair ISCMI 2025
    Brazil.

    Organizing Co-Chair ISCMI 2022
    Toronto, Canada

    Program Co-Chair IJCRS 2021
    IFSA-EUSFLAT2021, Bratislava, Slovakia

    Conference Co-Chair MIWAI 2013
    MIWAI 2013, Krabi Thailand

    Program Co-Chair RSKT2011
    The Fifth International Conference on Rough Sets and Knowledge Technology Banff, October 9-12, 2011

    Program Co-Chair RSCTC2010
    Seventh International Conference on Rough Sets and Current Trends in Computing Warsaw, June 28-30, 2010

    Workshop Chair A12011
    Canadian Conference of Artificial Intelligence Saint John's NewFoundland and Labrador, May 27-29, 2011

    My research spans a broad range of topics within Artificial Intelligence with a particular emphasis on Multimodality, Natural Langauage Processing and Soft Computing. My research has been funded by NSERC Discovery Grant, NSERC Alliance Society and Alliance Grants as well as MITACS Accelerate grants. I am currently accepting students whose interests align with my research. Please note that I am currently not supervising projects in the health domain.

    Multimodal AI

    We are pursuing challenging problems as to how to effectively learn from multimodal data (text, audio, visual, genomic), and to build AI systems that are explainable in complex domains such as Numerical Weather Prediction, Affective Computing, Visual Question Answering and Taxonomic Classification. Sample publications include:

  • Manjot Singh Sran and Sheela Ramanna, SPriG: Shared-only fusion with improvement-guided private gating for multimodal affective computing, Information Fusion Journal, 137, 2027

  • Manjot Singh Sran and Sheela Ramanna, Ketan Kotecha , DiMoE: Disentangled Representation Learning with Mixture-of-Experts Fusion for Sentiment Intensity Prediction and Emotion Classification, Algorithms Journal, 137, 2027

  • Ishadie Namir, Md. Akif Hussain, Sheela Ramanna, Qian Liu, Pradeeban Kathiravelu, Satellite image processing in the circumpolar north: Understanding climate crisis by predicting sea ice extent in the arctic, Remote Sensing Applications: Society and Environment Journal, 2025, vol. 40, 10197

  • P. Singhal , R. Walambe, S. Ramanna and K. Kotecha, Domain Adaptation: Challenges, Methods, Datasets, and Applications, IEEE Access, vol. 11, pp. 6973-7020, 2023, doi: 10.1109/ACCESS.2023.3237025.

  • Anil Rahate , Rahee Walambe, Sheela Ramanna, Ketan Kotecha, Employing multimodal co-learning to evaluate the robustness of sensor fusion for industry 5.0 tasks, Soft Computing, Springer, 2022.

  • Anil Rahate, Shruti Mandaokar, Pulkit Chandel , Rahee Walambe, Sheela Ramanna, Ketan Kotecha, Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions, Information Fusion, Elsevier, 2021 . ArXiv Preprint.

    • Tolerance-based Soft Computing in Multimodal AI and Natural Language Processing

    My particular interest is in exploring representational learning from various forms of deep neural architectures to be used in downsteam tolerance-based soft computing predictors. Our group have been been developing new learning algorithms in this domain. I am also interested in mathematical theories in this domain which are useful in the design of ambuigity aware intelligent systems. Sample publications in this area include:

  • Jaher Hassan Chowdhury and Sheela Ramanna MMLTC: A novel Tolerance-Based Clustering Framework for Multimodal Sentiment and Harmful Meme Classification in Multilingual Settings, Computational Intelligence, 42, no. 2, (2026): e70219

  • Arjun T D, Anand Kumar Madasamy, Sheela Ramanna, SeqTNS: Sequential Tolerance-based Classifier for Identification of Rhetorical Roles in Indian Legal Documents, Findings, Proc. of the 14th Intl. Joint Conf. on NLP and the 4th Conf. of the Asia-Pacific Chapter of ACL, 2025, pages 837-847

  • Siddharth Kelkar, Srinivasa Ravi, Anand Kumar M, Sheela Ramanna, Multimodal Propaganda Detection in Memes with Tolerance-Based Soft Computing Method, IJCRS Proceedings, LNAI, 14839, 2024, pp. 343-351

  • Sheela Ramanna, Tolerance-based granular methods: Foundations and applications in natural language processing, Intelligent Decision Technologies Journal, 17, 1 pp. 139-158, 2023

    • Natural Language Processing

    Our group is also focusing on exploring diverse paradigms such as reinforcement learning, neural cellular automata in text classification, multilingual text summarization, machine translation and Legal AI. Sample publications in this area include:

  • Asma Ben Ali, Sujay Rittikar, Sheela Ramanna When Representation Drift Does Not Reflect Functional Contribution: A Regime Analysis of Prompt Tuning, Proc. of the 35th ACM International Conference on Information and Knowledge Management, CIKM '26.

  • Ishadie Namir and Sheela Ramanna, Comparative Analysis of Native and Translation-Based Multimodal VQA Systems for the Bangla Language, Proc. of The 19th International Conference on Multi-disciplinary Trends in Artificial Intelligence (MIWAI), October 2026, Halifax, Nova Scotia, Canada.

  • Sujay Rittikar, Sheela Ramanna, Winterpeg: Do Neural Cellular Automata Help Where Pretraining Ends? Findings of WMT 2026, Shared Task on Low-Resource Indic Languages Translation, EMNLP, Hungary 2026.

  • Sujay Rittikar, Sheela Ramanna, STRIDE Moves Market Sentiment , Proc. of the The 39th Canadian Conference on Artificial Intelligence, PMLR 318:1151-1156