Machine learning, Artificial Intelligence, Algorithms, Data analytics, Computations, and their applications to sustainability. Intelligent Computations. Soft Computing and AI-driven Process Automation. Genetic Algorithms and Programming

Evolutionary Multi-Objective Optimization, Evolution Strategies, Evolutionary Robotics and Intelligent Agents

Hybrid Systems, evolutionary Rule-based systems, Memetic Algorithms, Hyperheuristics, Biocomputing and Complex Adaptive Systems, Swarm/Collective Intelligence, Bioinformatics and life sciences, Computer vision, image processing and pattern recognition, Dynamic environments, time series and sequence learning, Visualizing and improving the interpretability of machine learning models, Generalization and overfitting, Policy search and reinforcement learning, Fuzzy Logic, Rough Sets and Bayesian Methods, Cognitive Learning, Learning Paradigms, Memory Paradigms and Reasoning Models, Explainable AI, and adversarial Machine Learning, Extreme Learning Machines, Quantum Computing, Generative Adversarial Models, Natural Language Processing, Computational Genomics, Recommendation Systems, Smart Cities and Systems,, Music Information Retrieval

Big Data Analytics, Deep Learning Concepts Modelling, Soft Computing and Nature inspired computing, Human Machine Interaction, Web Intelligence and Social Networking, Cognitive systems and cognitive modelling, Biocomputing and Complex Adaptive Systems, Bio-Inspired Hardware and Networks, Swarm/Collective Intelligence, Cloud, Fog and Cluster computing, Ubiquitous Intelligence and Mobile computing, Emerging tools, technologies and Security, Data mining, Bioinformatics and life sciences; Computer vision, image processing and pattern recognition; Dynamic environments, time series and sequence learning;

Cognitive systems and cognitive modelling; Game Theory and Applications; Augmented & Virtual Reality; Industry 4.0; Social and Crowd Computing; Robotic Process Automation; Cybersecurity and cybernetics; Intelligent E-learning systems; Neural Networks and Pattern Recognition; Security, Authentication and Privacy; Block Chain and Cryptocurrency; Sentiment Analysis.

Industry 4.0; Hardware; Internet of Things; 5G/6G Communications; Robotics; Internet of Medical Things (IoMT) and Smart Healthcare; wireless power transfer; wireless technologies, systems science and automation; power station; substations; high voltage engineering; power electronics; electrical machines and drives; Embedded system design; FPGA; Microelectronics, Radio Frequency; Microwave, Signal Processing, Nano-electronic Devices, Digital Signal Processing.

Deep Learning (DL) and Machine Learning (ML) is now one of the fastest growing fields of research both in academia and Industry. However, the underlying principles of mathematics, statistics and computer sciences is still being understood by the researcher community and the industry across the globe. We, therefore, encourage submissions from researchers from diverse disciplines.

Broad Areas Topics may address any area of deep learning research such as:

• Expressivity

• Generalization

• Optimization

• Representations

• Computation

• Network architectures​

• Recurrent networks

Chemistry, Physics, Materials Sciences, Geology, Geography, Medical and Life Sciences. Oceanography, Rock Mechanics, Engineering Geology, Water Resources, pollution studies, toxicology, pharmacy, Nano-Sciences Nano-Engineering and Nanotechnology. Sensors and Systems.

Other branches of Engineering- Mechanical, Civil, Structural, Thermal. This track focuses on various branches of Engineering and technology that are classified as the aspects of 4th Industrial revolution.