Scope & IEEE Guidelines

The theme chosen by ICDSE 2027 for this year’s conference is “Agentic AI for Public Health and Wellness”. Authors are invited to submit original, high-quality, and unpublished research contributions exploring data engineering, advanced computation, and medical systems.

All selected and presented papers will be submitted to IEEE xplore for possible inclusion as proceedings of ICDSE 2027 ( Approval pending).

Page length crossing 6 will have extra page charges

Formatting templates (Docx / Latex) can be downloaded from:
ICDSE Template

Submission Deadline

September 30, 2026.

Submission Instructions

Technical Tracks & Topics

Select a track to review topics and respective Track Chairs

Track 1: Core AI & Machine Learning Methodologies

Focuses on core algorithmic improvements, novel network architectures, training optimizations, and theoretical foundations of AI/ML.

Track Chair: Shailesh Sivan, Cochin University, India

  • Supervised, Unsupervised, and Reinforcement Learning
  • Deep Learning & Neural Network Architectures
  • Optimization Algorithms and Theoretical Machine Learning
  • Generative AI & Large Language Models (LLMs)
  • Statistical and Evolutionary Computing

Track 2: AI & ML tools for health and wellness

Focuses on clinical diagnostic support systems, personal vital tracking, automated wellness modeling, and assistive technologies.

Track Chair: Jeena K, Cochin University, India

  • Smart Health Monitoring & Predictive Vital Diagnostics
  • Wearable Sensors and IoT for Personal Wellness
  • Assistive Technologies & Rehabilitation Engineering
  • Behavioral Analytics and Mental Health Computing
  • Wellness Tracking Mobile Apps and Platforms

Track 3: BioAI & Computational Genomics

Deals with pattern recognition in genomics, sequence alignment, protein folding prediction, and pathway analytics using AI.

Track Chair: Jereesh A S, Cochin University, India

  • Deep Learning for Gene Sequencing and Genomics
  • Computational Proteomics and Structural Bioinformatics
  • Biological Network Modeling & Pathway Analysis
  • Drug Discovery & Molecular Property Prediction
  • AI in Disease Pathology & Clinical Decision Support

Track 4: Data Infrastructure for Biological Data

Focuses on high-throughput database systems, distributed pipelines, and cloud computing for biology databases.

Track Chair: Bijoy A Jose, Cochin University of Science and Technology, Kerala

  • Distributed Storage & Database Systems for Genomics
  • High-Performance Computing for Biological Simulation
  • Data Integration, Interoperability & Open Standards in Bioinformatics
  • Privacy-Preserving Biological Data Sharing
  • Cloud and Edge Infrastructures for Smart Healthcare

Track 5: AI & Ethics, Policies in Health care

Covers explainable AI in medicine, patient data privacy, policy frameworks, and socio-technical safety regulations.

Track Chair: Deepak Padmanabhan, Queen's University Belfast, UK

  • Fairness, Bias, and Explainability (XAI) in Medical AI
  • Patient Privacy, Consent, and Data Ownership Policies
  • Regulatory Frameworks and Standards for Clinical AI
  • Socio-Technical Implications of Healthcare Automation
  • Ethical Frameworks for Autonomous Health Systems

Doctoral Symposium

PhD students in data science, advanced computing, computational biology, and related fields are invited to present their ongoing research. This symposium provides a unique venue to receive feedback from senior academic panels, industry experts, and peer research groups.

Submissions to the Doctoral Symposium should describe the research problem, methodology, and current progress. Selected PhD delegates will present their work in interactive poster and slide sessions.

Inquire About Symposium