About Me

Dr. Satya Ranjan Dash is the Dean of the School of Computer Applications at KIIT-DU. He is a prominent researcher specializing in Natural Language Processing (NLP), with a particular focus on low-resource languages of India and abroad. He is also actively involved in Odia Generative AI, an initiative dedicated to developing Large Language Models (LLMs) for the Odia language. His work emphasizes open research, making models, code, and datasets freely available for non-commercial and research purposes. Dr. Dash plays a key role in advancing AI-driven linguistic innovations and promoting inclusive AI technologies for underrepresented languages.

As the Dean at KIIT-DU, he plays a crucial role in shaping the academic curriculum, fostering research collaborations, and mentoring students in cutting-edge AI and NLP technologies. Under his leadership, the School of Computer Applications has strengthened its focus on AI-driven research, interdisciplinary studies, and global academic partnerships.

Beyond NLP, his research spans across deep learning, speech processing, and AI applications in various domains. He has been instrumental in building AI models tailored for linguistic diversity, enabling automated translations, speech synthesis, and conversational AI for low-resource languages. Dr. Dash is a strong advocate for open research and responsible AI. His work in Generative AI, speech processing, and computational linguistics aims to make AI technology more inclusive, ethical, and impactful. Through his research and leadership, he continues to inspire young researchers, educators, and technologists to contribute towards the advancement of AI for social good.

About

Supervision & Mentorship

  • Dr. Dula Bankira

    Computational Linguistics for Ho Language (2023).

  • Dr. Pranab Kumar Bharimalla

    A Secured Block chain based Electronic Health Record System for the Indian subcontinent (2022)

  • Dr. Rekha Sahu

    Detection of Brain Abnormalities from Spontaneous Electroencephalography using Spiking Neural Network (2022).

  • Dr. Debjani Panda

    Predictive Analytics for Cardio Health Systems (2021).

Research Projects

Development of Electronic Medical Record (EMR) registry and machine learning model for prediction of diabetic nephropathy using renal biomarkers and clinical data.

Indian Council of Medical Research(ICMR), Govt. of India,

Duration :3 yrs.

Development of Electronic Medical Record (EMR) registry and AI Model for prediction of mortality in liver cirrhosis using hepatic biomarkers and clinical data.

Science and Engineering Research Board(SERB), Govt. of India

Duration :3 yrs.

A deep learning-based genome mining strategy for identification of biosynthetic/chemotherapeutic gene clusters in the marine actionobacteria Salinispora and its validation study through data analytic approach.

Ministry of Earth Sciences(MoES), Govt. of India

Duration :2 yrs.

Publication Details

Google Scholar profile of Dr. Satya Ranjan Dash

20 Oct, 2024

Read More

ResearchGate profile of Dr. Satya Ranjan Dash

20 Oct, 2024

Read More

Workshops and Summer School

ATAL FDP on “Artificial Intelligence in Natural Language Processing” (15th to 19th October, 2020)

3-day online workshop on Applied Python-I (27th to 29th October, 2022)

4-day online workshop on Applied Python-II(26th to 29th December, 2023)

2 weeks Summer School on “Recent Trends in Speech Processing and its Application” (7th June -21st June, 2024)

Conferences, Talks and Workshop

Research Group

Dr. Satya Ranjan Dash’s research group is dedicated to advancing Natural Language Processing (NLP), with a special focus on low-resource languages of India and beyond. The group's key objectives are:

Generative AI (Gen AI)

Developing large-scale language models, text generation systems, and AI-driven applications for low-resource languages, ensuring inclusivity in AI advancements.

Medical Image Processing

Leveraging deep learning and computer vision for medical diagnostics, disease detection, and AI-assisted healthcare solutions.

Speech Processing

Enhancing automatic speech recognition (ASR), text-to-speech (TTS), and spoken dialogue systems, particularly for underrepresented languages.