Sunil Kumar Sahu

Principal Applied Scientist · Inception42

Abu Dhabi, UAE

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About

I am a Principal Applied Scientist at Inception42 in Abu Dhabi, UAE. My work centers on agentic AI — building autonomous, tool-using systems on top of large language and multimodal models that can plan, reason, and act to solve real-world tasks.

Previously, I was a Postdoctoral Researcher at the National Centre of Text Mining (NaCTeM), University of Manchester, UK, working with Prof. Sophia Ananiadou. I completed my Ph.D. in Computer Science and Engineering at IIT Guwahati, India, under the supervision of Dr. Ashish Anand.

Research Interests

Agentic AI Large Language Models Large Multimodal Models Autonomous Agents Tool Use & Reasoning Deep Learning

Career

  1. 2025 — Present

    Principal Applied Scientist

    Inception42 — Abu Dhabi, UAE

    Research on large language models, multimodal models, and agentic AI.

  2. 2021 — 2025

    Senior Applied Scientist

    Inception42 — Abu Dhabi, UAE

    Large language and multimodal model research and development.

  3. 2019 — 2021

    Applied Scientist

    Inception42 — Abu Dhabi, UAE

    Applied NLP and deep learning research.

  4. 2017 — 2019

    Postdoctoral Researcher

    National Centre of Text Mining (NaCTeM), University of Manchester, UK

    Research with Prof. Sophia Ananiadou on text mining and information extraction.

  5. 2013 — 2017

    Ph.D., Computer Science & Engineering

    Dept. of Computer Science & Engineering, IIT Guwahati, India

    Advisor: Dr. Ashish Anand. Deep learning for biomedical information extraction.

Publications

Full list on Google Scholar.

2026

  • A. Singh, D. Banerjee, D. Sahnan, M. Choudhury, S. Chauhan, R. J. Das, S. K. Sahu, et al. Nanda Family: Open-Weights Generative Large Language Models for Hindi. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2026.

2025

  • M. Choudhury, S. Chauhan, R. J. Das, D. Sahnan, X. Han, H. Li, A. Singh, S. K. Sahu, et al. Llama-3-Nanda-10B-Chat: An Open Generative Large Language Model for Hindi. arXiv:2504.06011, 2025.

2024

  • C. Gautam, S. Parameswaran, A. Kane, Y. Fang, S. Ramasamy, S. Sundaram, S. K. Sahu, et al. Class Name Guided Out-of-Scope Intent Classification. Findings of ACL: EMNLP 2024.
  • G. Gosal, Y. Xu, G. Ramakrishnan, R. Joshi, A. Sheinin, B. Mishra, S. K. Sahu, et al. Bilingual Adaptation of Monolingual Foundation Models. arXiv:2407.12869, 2024.

2023

  • N. Sengupta, S. K. Sahu, B. Jia, S. Katipomu, H. Li, F. Koto, W. Marshall, et al. Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models. arXiv:2308.16149, 2023.

2022

  • S. Kamboj, S. K. Sahu, N. Sengupta. DENTRA: Denoising and Translation Pre-training for Multilingual Machine Translation. Proceedings of the Seventh Conference on Machine Translation (WMT), 2022.

2020

  • S. K. Sahu, D. Thomas, B. Chiu, N. Sengupta, M. Mahdy. Relation Extraction with Self-determined Graph Convolutional Network. CIKM 2020.
  • B. Chiu, S. K. Sahu, N. Sengupta, D. Thomas, M. Mahdy. Attending to Inter-sentential Features in Neural Text Classification. SIGIR 2020.
  • B. Chiu, S. K. Sahu, D. Thomas, N. Sengupta, M. Mahdy. Autoencoding Keyword Correlation Graph for Document Clustering. ACL 2020.
  • F. Christopoulou, T. T. Tran, S. K. Sahu, M. Miwa, S. Ananiadou. Adverse Drug Events and Medication Relation Extraction in Electronic Health Records with Ensemble Deep Learning Methods. Journal of the American Medical Informatics Association (JAMIA), 2020.
  • S. K. Sahu, A. Anand. Unified Neural Architecture for Drug, Disease and Clinical Entity Recognition. Deep Learning Techniques for Biomedical and Health Informatics, 2020.

2019

  • S. K. Sahu, F. Christopoulou, M. Miwa, S. Ananiadou. Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network. ACL 2019.

2018

  • S. K. Sahu, A. Anand. Drug-Drug Interaction Extraction from Biomedical Text Using Long Short Term Memory Network. Journal of Biomedical Informatics, 2018.
  • S. K. Sahu, A. Anand. What Matters in a Transferable Neural Network Model for Relation Classification in the Biomedical Domain? Artificial Intelligence in Medicine, 2018.
  • A. Godbole, A. Dalmia, S. K. Sahu. Siamese Neural Networks with Random Forest for Detecting Duplicate Question Pairs. arXiv:1801.07288, 2018.

2017

  • D. Raj, S. Sahu, A. Anand. Learning Local and Global Contexts Using a Convolutional Recurrent Network Model for Relation Classification in Biomedical Text. CoNLL 2017.
  • P. V. S. S. Rahul, S. K. Sahu, A. Anand. Biomedical Event Trigger Identification Using Bidirectional Recurrent Neural Network Based Models. BioNLP 2017.

2016

  • S. K. Sahu, A. Anand, K. Oruganty, M. Gattu. Relation Extraction from Clinical Texts Using Domain Invariant Convolutional Neural Network. BioNLP 2016.
  • S. K. Sahu, A. Anand. Recurrent Neural Network Models for Disease Name Recognition Using Domain Invariant Features. ACL 2016.
  • R. D. Sharma, S. Tripathi, S. K. Sahu, S. Mittal, A. Anand. Predicting Online Doctor Ratings from User Reviews Using Convolutional Neural Networks. International Journal of Machine Learning and Computing, 2016.

2015

  • T. H. Muneeb, S. Sahu, A. Anand. Evaluating Distributed Word Representations for Capturing Semantics of Biomedical Concepts. BioNLP 2015.

Awards & Honors

  • WMT 2020 Shared Task (Similar Language Translation): Our team achieved 5th rank.
  • n2c2 Shared Task 2018 (Track 2): Our team achieved 6th rank in concept extraction and 3rd rank in both relation extraction and the end-to-end system.
  • Travel Grants: Awarded travel grants to attend ACL 2015 and ACL 2016 from Google, Microsoft, and IIT Guwahati.
  • Publications at premier venues including ACL, SIGIR, CIKM, CoNLL, and BioNLP.

Contact

I'm always happy to connect about research and collaboration.