IEEE PUNECON 2026
This conference aims to provide a technical platform for researchers across the globe to present their innovative ideas and share technical knowledge. The theme of the conference is Generative Futuristics System. This conference encourages original papers in the diversified domains pertaining to the field of technological advancements. The participants will be benefited by experiencing recent accomplishments and innovations.
Paper Submission
All accepted, registered and presented papers will be submitted to IEEE for possible inclusion in IEEE Xplore® digital library.
The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.
CALL FOR PAPER
IMPORTANT DATES
Earlier IEEE PuneCon Publications Proceedings and also Scopus Indexed
IEEE PUNECON
https://ieeexplore.ieee.org/xpl/conhome/1829344/all-proceedings
The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.
Conference Tracks
IEEE Punecon 2026 Tracks
Track 1: Intelligent Systems
Track 2: Secure Systems
Track 3: Human-Centric Systems
Track 4: Distributed, Edge & Cloud Computing
Track 5: Cyber-Physical Systems
Track 6: Life Sciences
Track 7: Indian Knowledge System & Technology Integration
Track 8: Computer Vision & Machine Learning
Track 9: Electric Vehicles
Track 10: Medical Signal Processing
Track Details
Track 1: Intelligent Systems
Focuses on the design and development of intelligent algorithms and systems capable of learning, reasoning, and decision-making across diverse applications. Exploring the core intelligence behind modern AI systems. Advancing adaptive, autonomous, and data-driven technologies.
- Artificial Intelligence and Machine Learning
- Deep Learning Architectures and Optimization
- Knowledge Representation and Reasoning
- Reinforcement Learning and Decision Systems
- Natural Language Processing and Conversational AI
- Explainable AI and Trustworthy Intelligence
- Autonomous Agents and Multi-Agent Systems
- Cognitive Computing and Adaptive Systems
Track 2: Secure Systems
Addresses the growing need for robust, secure, and privacy-preserving computing systems in an increasingly connected world. Ensuring trust, resilience, and protection in digital infrastructures.
- Cybersecurity and Threat Intelligence
- Cryptography and Secure Communication
- Network and Cloud Security
- Privacy-Preserving Computing
- Blockchain and Distributed Security
- Secure Software Engineering
- Identity and Access Management
- AI for Cybersecurity and Threat Detection
Track 3: Human-Centric Systems
Explores technologies designed with a focus on human interaction, usability, accessibility, and societal impact. Bridging the gap between humans and intelligent systems.
- Human-Computer Interaction (HCI)
- User Experience (UX) Design and Evaluation
- Assistive Technologies and Accessibility
- Affective Computing and Emotion AI
- Social Computing and Digital Behavior Analysis
- Human-AI Collaboration
- Ethical and Inclusive System Design
- Augmented Intelligence and Human Enhancement
Track 4: Distributed, Edge & Cloud Computing
Focuses on scalable and efficient computing paradigms spanning cloud, edge, and distributed environments. Enabling real-time, resilient, and high-performance systems.
- Cloud Computing and Cloud-Native Architectures
- Edge and Fog Computing
- Distributed Systems and Parallel Computing
- Serverless and Microservices Architectures
- Data Storage, Management, and Big Data Systems
- Resource Optimization and Scheduling
- High-Performance Computing (HPC)
- AI/ML in Distributed Environments
Track 5: Cyber-Physical Systems
Covers the integration of computation, networking, and physical processes in real-world systems. Engineering intelligent systems that interact with the physical world.
- Internet of Things (IoT) and Smart Devices
- Embedded Systems and Real-Time Computing
- Robotics and Autonomous Systems
- Smart Cities and Infrastructure
- Industrial Automation and Industry 4.0
- Sensor Networks and Actuation Systems
- Digital Twins and Simulation Systems
- Human-Machine Interaction in CPS
Track 6: Life Sciences
Highlights the intersection of computing and biological sciences, driving innovation in healthcare, biotechnology, and medicine. Advancing data-driven life science research.
- Bioinformatics and Computational Biology
- Genomics, Proteomics, and Multi-omics
- Medical Image and Signal Analysis
- Precision Medicine and Healthcare Informatics
- Drug Discovery and Computational Pharmacology
- Biomedical Data Analytics
- Systems Biology and Network Analysis
- AI in Healthcare and Diagnostics
Track 7: Indian Knowledge System & Technology Integration
Explores the integration of traditional Indian knowledge systems with modern technology to create sustainable and innovative solutions. Bridging heritage and advanced computing.
- Indian Knowledge Systems and Digital Preservation
- AI for Sanskrit and Classical Languages
- Traditional Medicine Systems (e.g., Ayurveda) and AI
- Cultural Heritage Informatics
- Indigenous Technologies and Sustainability
- Ethical and Philosophical Foundations in Technology
- Smart Agriculture with Traditional Practices
- Knowledge Representation of Ancient Texts
Track 8: Computer Vision & Machine Learning
Focuses on algorithms and systems that enable machines to interpret and learn from visual and structured data. Powering perception-driven intelligent applications.
- Image and Video Processing
- Object Detection and Recognition
- Pattern Recognition and Classification
- Deep Learning for Vision Applications
- 3D Vision and Scene Understanding
- Medical Image Analysis
- Vision for Autonomous Systems
- Multimodal Learning and Fusion
Track 9: Electric Vehicles
Addresses advancements in electric mobility, sustainable transportation, and intelligent vehicle systems. Driving the future of clean and efficient mobility.
- Electric Vehicle Design and Architecture
- Battery Technology and Energy Storage Systems
- Charging Infrastructure and Smart Grids
- Power Electronics and Drive Systems
- Vehicle-to-Grid (V2G) Integration
- Autonomous and Connected Vehicles
- Energy Management and Optimization
- Sustainable Transportation Systems
Track 10: Medical Signal Processing
Focuses on the analysis and interpretation of biomedical signals for improved diagnosis, monitoring, and healthcare delivery. Enabling intelligent healthcare systems.
- Biomedical Signal Acquisition and Processing
- ECG, EEG, EMG Signal Analysis
- Wearable Health Monitoring Systems
- Signal-Based Disease Detection and Diagnosis
- AI in Medical Signal Processing
- Time-Frequency and Spectral Analysis
- Real-Time Health Monitoring Systems
- Healthcare IoT and Remote Diagnostics
IEEE Punecon-2026 Tracks:
- Track 1: Emerging Computing Paradigm
- Track 2: Systems Engineering for AI-Driven Applications
- Track 3: Security, Ethics & Governance
- Track 4: Disruptive Technologies & Future Directions
- Track 5: Generative Social Engineering
- Track 6: Platforms, Frameworks, and Developer Ecosystems
- Track 7: Bioinformatics and Computational Biology
- Track 8: Toolkits, Frameworks, and Platforms for Generative Engineering
- Track 9: Foundations of Intelligent Systems
Track Details:
Track 1: Emerging Computing Paradigm
Explores cutting-edge computational models driving the future—from quantum and neuromorphic computing to edge intelligence—enabling scalable and energy-efficient generative technologies. Exploring the next frontier in computation. Pioneering the computational backbone of generative intelligence.
- Quantum and Neuromorphic Computing
- Edge, Fog, and Swarm Intelligence
- Distributed Computing and Collaborative Platforms
- AI for High-Performance and Cloud-Native Systems
- Quantum Computing and Quantum AI
- Neuromorphic and Brain-Inspired Computing
- Edge AI and Energy-Efficient Architectures
- Hyperdimensional & Holographic Computing
- Synthetic Neural Systems
Track 2: Systems Engineering for AI-Driven Applications
Focuses on integrating generative AI into cyber-physical systems, digital twins, smart factories, and autonomous infrastructures across sectors like manufacturing, healthcare, and transportation. Real-world systems that integrate AI at the edge, cloud, and device layers. Engineering the infrastructure and intelligence behind smart systems.
- Computer Vision and Sensor Fusion
- AI in Industrial, Automotive, and Embedded Systems
- Smart Cities, IoT, and Adaptive Environments
- Robotics, Actuation, and Real-Time Decisioning
- Digital Twins and Simulation-Driven AI
- Smart Factories and Industrial IoT
- Autonomous Systems: Robotics, Drones, Vehicles
- Cyber-Physical Systems and Human-Machine Interaction
- Generative AI for Healthcare, Manufacturing, and Logistics
Track 3: Security, Ethics & Governance
Addresses the ethical, legal, and social challenges of generative AI—including misinformation, privacy, bias, and responsible innovation—while exploring frameworks for global governance and regulation. Policy, security, and human alignment in an AI-driven world. Ensuring trustworthy, transparent, and secure generative technologies.
- Ethics in Generative AI
- Trust, Bias, and Accountability
- Cybersecurity in Intelligent Systems
- Governance, Regulation, and Public Policy
- Deepfake Detection and Synthetic Media Validation
- AI Policy, Regulation, and Global Governance
- Privacy-Preserving Generative AI
- Fairness, Bias Mitigation, and Ethical Frameworks
- Responsible Deployment and Compliance Models
Track 4: Disruptive Technologies & Future Directions
Highlights interdisciplinary breakthroughs shaping the next decade, such as metaverse ecosystems, holographic interfaces, and AI-augmented reality for education, defense, and space. The convergence of tech frontiers that will define the next decade. Exploring revolutionary ideas and cross-disciplinary breakthroughs.
- Distributed Ledger Technologies
- Human-AI Augmentation
- Cross-domain Intelligence Systems
- Convergence of AI, AR/VR, and Metaverse
- Tech Foresight and Futures Thinking
- AI in Metaverse and Virtual/Augmented Reality
- Holography, Mixed Reality, and Immersive Interfaces
- AI for Space, Defense, and Climate Engineering
- Cross-Domain Intelligence and Autonomous Discovery
Track 5: Generative Social Engineering
Investigates the impact of generative AI on human interaction, behaviour manipulation, and communication—covering deepfakes, persuasion algorithms, synthetic media, and digital influence strategies. Understanding the societal dynamics influenced by generative content.
- Generative AI: Models and Techniques
- Generative Social Engineering and Behavioral AI
- Generative Sustainable Systems
- Large Language Models & Diffusion Systems
- Prompt Engineering and Human-AI Collaboration
- Behavioral Influence and Digital Persuasion
- NLP for Narrative Shaping and Sentiment Control
- Social Media Bots and Propaganda Detection
- Generative Memes, Avatars, and Virtual Personas
- Synthetic Journalism and AI-Driven Storytelling
Track 6: Platforms Frameworks & Developer Ecosystems
Covers tools, SDKs, APIs, and cloud-native platforms for building, training, and deploying generative systems—including AutoML, open-source stacks, scalable MLOps, and ethical prompt engineering. Engineering, building, and scaling with the right tools and platforms.
Tools and systems empowering the creators of generative intelligence.
- Toolkits and Frameworks for Generative AI
- Scalable AI/ML Pipelines
- Open Source and Low-Code Platforms
- Deployment, Monitoring, and MLOps
- LLM Toolkits and Prompt Engineering Pipelines
- AutoML and No-Code/Low-Code GenAI Platforms
- Open Source Libraries and API Frameworks
- Scalable MLOps and Cloud-Native Architectures
- GPU/TPU Optimization and Model Compression
Track 7: Bioinformatics and Computational Biology
With the exponential growth of biological data and the increasing convergence of computer science and life sciences, there is a critical need for platforms that bring together researchers, practitioners, and academicians working in Bioinformatics and Computational Biology. This track will focus on the latest advancements in computational methods, data-driven insights, and modelling techniques that are transforming the life sciences, biotechnology, and healthcare sectors. The track will invite high-quality research papers in, but not limited to, the following areas:
- AI/ML/Deep Learning applications in Bioinformatics data
- Genomics, Proteomics, and Multi-omics data integration
- Next-Generation Sequencing (NGS) data analytics
- Biomedical Informatics and Precision Medicine
- Computational Drug Discovery and Repurposing
- Medical Image Analysis
- Network Pharmacology
- Biodiversity and Conservation Informatics
- Bio-Computing, Bio-AI Integration and Genetic Algorithm Applications
- General Computational Biology
Track 8: Toolkits, Frameworks, and Platforms for Generative Engineering:
- Ethics in Generative AI
- Trust, Bias, and Accountability
- Cybersecurity in Intelligent Systems
- Governance, Regulation, and Public Policy
- Deepfake Detection and Synthetic Media Validation
- AI Policy, Regulation, and Global Governance
- Privacy-Preserving Generative AI
- Fairness, Bias Mitigation, and Ethical Frameworks
- Responsible Deployment and Compliance Models
Track 9: Foundations of Intelligent Systems
Delves into the core models powering generative AI—foundation models, LLMs, GANs, diffusion models, and multimodal learning—with a focus on theory, architecture, and optimization. Exploring the theoretical and architectural bedrock of generative AI.
- Deep Learning: Architectures and Advances
- Foundations of Generative AI
- Data, Models, and Optimization
- Computational Neuroscience and Cognitive Models
- Large Language Models and Foundation Models
- GANs, Diffusion Models, and Variants
- Multimodal AI and Cross-Modal Learning
- Continual, Few-Shot, and Zero-Shot Learning
- Knowledge Graphs and Neuro-symbolic Reasoning
Author Instructions:
Please comply with the following guidelines:
- All papers must be in English.
- The paper must discuss only new and previously unpublished results.
- The paper must be formatted according to the IEEE Manuscript Templates for Conference Proceedings, have a minimum of four pages, and must not exceed 6 pages, including figures and references.
- The paper must address at least one category specified in the Call for Papers.
Additional guidelines:
- The plagiarism check will be done on all submitted papers. Plagiarism and self-plagiarism applies to all previously published work, irrespective of whether the other publication is inside or outside of IEEE. We are very serious about Plagiarism Content; we accept only original articles. The article may be rejected at any time if found plagiarized. For more information refer IEEE page – Plagiarism FAQs.
- All papers that are accepted must be presented at the conference. In case a paper is not presented at the conference, it shall be deemed a “no-show.” No-shows will be removed from post-conference distribution.
- All accepted, registered, and presented papers will be submitted to IEEE for possible inclusion in IEEE Xplore® digital library.
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