Call for Papers

OAIC 2026 invites original, unpublished research contributions across all areas of artificial intelligence.

Invitation to Authors

The Organizing Committee of the 2026 1st IEEE Odisha AI Conference (OAIC) invites researchers, academicians, industry professionals, and practitioners worldwide to submit original, unpublished contributions on Artificial Intelligence and applications (see tracks and focus below). OAIC 2026 is the inaugural edition of a regional conference dedicated to fostering excellence in AI research and its transformative applications across industry, governance, healthcare, energy, and society. The conference will serve as a premier forum for exchanging ideas, presenting research findings, and building interdisciplinary collaborations that address real-world challenges through AI-driven solutions — with a special emphasis on the development priorities of the state of Odisha and the broader Indian subcontinent.

The conference will feature keynote addresses by leading researchers and practitioners, technical paper presentations, tutorials and workshops, and dedicated industry sessions — creating a vibrant ecosystem for knowledge exchange between academia and industry.

PublicationAll accepted and presented papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE quality requirements.

e gradient (23.4 x 33.1 in) by Bharat Jyoti Ranjan Sahu . Embed link

Conference Tracks

Explore our conference tracks and submit your contributions to the appropriate areas of interest:

Track 1 Focus

AI Foundations

Sub-Track 1A

Machine Learning, Deep Learning, and Causal AI

Supervised, unsupervised, semi-supervised, and self-supervised learning

Neural network architectures and deep generative models

Transfer learning and meta-learning

Federated learning

Foundation models and large-scale pretraining

Explainable and interpretable AI (XAI)

Uncertainty quantification

Causal inference and causal discovery

Counterfactual reasoning

Bayesian learning methods

Statistical learning theory

Model-free and model-based reinforcement learning

Multi-agent RL

Safe and constrained RL

RL for robotics and control

Human-in-the-loop RL

Reinforcement learning from human feedback (RLHF)

Planning and sequential decision making under uncertainty

Game-theoretic AI

Sub-Track 1B

Data Science, Big Data, and Predictive Analytics

Data mining and knowledge discovery

Big data processing, integration, and visualization

AI for data-driven decision making

Predictive and prescriptive analytics

Knowledge graphs and semantic web

Time series analysis

Anomaly detection

AI for business intelligence

Sub-Track 1C

Computer Vision, Remote Sensing, and Imaging

Image and video analysis

Object detection, recognition, and segmentation

Medical image processing

Remote sensing and satellite image analysis

Drone and aerial imaging

Hyperspectral and multispectral imaging

Integrated sensing and communication (ISAC)

3D vision and scene understanding

Generative models for vision

Sub-Track 1D

Natural Language Processing and Speech Technologies

Large language models and generative AI

Text analytics and information extraction

Speech recognition and synthesis

Conversational AI and dialogue systems

Multilingual and low-resource NLP

Question answering and retrieval-augmented generation

Sentiment analysis

AI for regional and indigenous languages

Submission Types

Choose the format that best fits your contribution.

Full Paper

6 pages

Original, unpublished research contributions.

Demo / Poster

2–4 pages

Live demonstrations and poster presentations.

Submit Your Paper