Greetings from my corner of the WEB! 😊
I am currently a Postdoctoral Researcher at University of Galway, Ireland, working at the intersection of Artificial Intelligence (AI), Natural Language Processing (NLP), Data Science, and Digital Humanities.
My current research focuses on developing AI-driven computational methods for understanding multilingual and historical textual data. I work on Natural Language Processing, Knowledge Graphs, Network Analysis, Machine Translation, and Large Language Models (LLMs) to make complex textual resources more accessible and meaningful.
Before joining the University of Galway, I worked as an Assistant Professor (Grade I) at XIM University, Bhubaneswar, India, where I was involved in teaching Computer Science courses, mentoring students, and guiding research projects in Artificial Intelligence and Machine Learning.
Prior to my academic journey, I worked with the Defence Research and Development Organisation (DRDO), India, as a Junior and Senior Research Fellow. During my time at DRDO, I developed AI-based intelligent systems, speech recognition applications, human-machine interaction tools, and multimodal computational solutions for real-world applications.
I earned my Ph.D. in Computer Science and Engineering from the National Institute of Technology (NIT) Rourkela, India, under the supervision of Dr. Tapas Kumar Mishra (NIT Rourkela, India) and co-supervision of Dr. Bidyut Kumar Patra ( Indian Institute of Technology (BHU) Varanasi, India). My doctoral dissertation, titled "Exploring Efficacy of Machine Translation System for Indian Languages," focused on developing multilingual machine translation approaches for low-resource Indian languages, with the broader goal of reducing language barriers through Artificial Intelligence.
Prior to my Ph.D., I completed my M.Tech in Computer Science and Engineering from Veer Surendra Sai University of Technology (VSSUT), India, where I received the University Gold Medal for academic excellence.
My research interests broadly include:
- 🔹 Natural Language Processing (NLP)
- 🔹 Machine Translation and Multilingual AI
- 🔹 Large Language Models (LLMs)
- 🔹 Low-Resource Language Technologies
- 🔹 Digital Humanities and Computational Manuscript Analysis
- 🔹 Knowledge Graphs and Network Science
- 🔹 Explainable and Human-Centred AI
- 🔹 Speech Processing and Multimodal AI Systems
💡 Great ideas often begin with a simple conversation. If you are interested in exploring new ideas, collaborating on research, or building impactful applications using Large Language Models (LLMs), Natural Language Processing, and AI-driven technologies, feel free to reach out: baladas.sudhansu[at]gmail[dot]com.
I am always happy to connect with researchers, students, developers, and curious minds who believe in using technology to solve real-world problems and create a positive impact. 😊
“कर्मण्येवाधिकारस्ते मा फलेषु कदाचन।”
You have the right to perform your actions, but never be attached to the results.
— श्रीमद् भगवद् गीता (Bhagavad Gita)
Research
My research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Translation, Data Science, and Digital Humanities. I am interested in developing AI-based technologies for multilingual and low-resource languages, historical text analysis, and real-world intelligent systems.
Research Interests
- 🔹 Natural Language Processing (NLP)
- 🔹 Machine Translation and Multilingual AI
- 🔹 Large Language Models (LLMs)
- 🔹 Low-Resource Language Technologies
- 🔹 Digital Humanities and Computational Manuscript Analysis
- 🔹 Knowledge Graphs and Network Science
- 🔹 Speech Processing and Multimodal AI
Publications
-
Statistical Machine Translation for Indic Languages.
Sudhansu Bala Das, Divyajyoti Panda, Tapas Kumar Mishra, and Bidyut Kr. Patra.
Natural Language Processing, Cambridge University Press, Vol. 31, No. 2, pp. 328–345, 2025. (SCI) -
Proceedings of the Workshop on Beyond English: Natural Language Processing for All Languages in an Era of Large Language Models.
Sudhansu Bala Das, Pruthwik Mishra, Alok Singh, Shamsuddeen Hassan Muhammad, Asif Ekbal, and Uday Kumar Das.
Proceedings of GlobalNLP 2025 Workshop, RANLP 2025, Varna, Bulgaria, 2025. -
A Thresholding Method for Improving Translation Quality for Indic MT Task.
Sudhansu Bala Das, Leo Raphael Rodrigues, Tapas Kumar Mishra, and Bidyut Kr. Patra.
Proceedings of the First Workshop on Advancing NLP for Low-Resource Languages, RANLP 2025, pp. 12–20, Varna, Bulgaria, 2025. -
Investigating the Effect of Backtranslation for Indic Languages.
Sudhansu Bala Das, Samujjal Choudhury, Tapas Kumar Mishra, and Bidyut Kr. Patra.
Proceedings of the First Workshop on Natural Language Processing for Indo-Aryan and Dravidian Languages, pp. 152–165, Abu Dhabi, UAE, 2025. -
Multilingual Neural Machine Translation for Indic to Indic Languages.
Sudhansu Bala Das, Divyajyoti Panda, Tapas Kumar Mishra, Bidyut Kr. Patra, and Asif Ekbal.
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 23, No. 5, Article 65, pp. 1–32, 2024. (SCI) -
Improving Multilingual Neural Machine Translation System for Indic Languages.
Sudhansu Bala Das, Atharv Biradar, Tapas Kumar Mishra, and Bidyut Kr. Patra.
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 22, No. 6, Article 169, pp. 1–24, 2023. (SCI) -
NIT Rourkela Machine Translation (MT) System Submission to WAT 2022 for MultiIndicMT.
Sudhansu Bala Das, Atharv Biradar, Tapas Kumar Mishra, and Bidyut Kr. Patra.
Proceedings of the 9th Workshop on Asian Translation, International Conference on Computational Linguistics (COLING), pp. 73–77, Gyeongju, Republic of Korea, 2022. (CORE A*) -
An Efficient Average Execution Time–Round-Robin (AET-RR) Scheduling Algorithm.
Sudhansu Bala Das, S.K. Mishra, and A.K. Sahu.
International Journal of Information Technology, Vol.14, pp.863–876, Springer, 2022. (Scopus) -
Alarm Coloring and Grouping Algorithm for Root Cause Analysis.
Sudhansu Bala Das, Sugyan Kumar Mishra, and Anup Kumar Sahu.
Journal of King Saud University - Computer and Information Sciences, Vol.33, Issue 5, pp.572–579, Elsevier, 2021. (SCI) -
Proof-of-Driving Incentive Mechanism for VANET to Enhance Traffic Safety and Efficiency.
Surjya Kanta Daimary, Sekh Main Hasan, Hemanta Kumar Kalita, and Sudhansu Bala Das.
Data-Driven AI: A Multidisciplinary Approach, CRC Press, 2026. (Book Chapter)