Machine Learning and Human Computer Interaction MLHCI

Dear Colleagues,

This Special Issue aims to bring together researchers and practitioners to present their latest achievements and innovations in the areas of machine learning and human–computer interaction.

Machine learning is a subfield of artificial intelligence (AI). The main objective of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Machine learning is a continuously developing field. Because of this, there are some considerations to keep in mind as you work with machine learning methodologies or analyze the impact of machine learning processes. The objective of this conference is to analyze the implications and challenges faced during the implementation of machine learning in different domains.

HCI is a field in need of significant innovation and breakthroughs toward radically new future forms of interaction. Moreover, the conference will also emphasize the challenges and innovative topics in human–computer interaction theory, methodology, and practice, including, for example, novel theoretical approaches to interaction, novel user interface concepts and technologies, novel interaction devices, UI development methods, environments and tools, multimodal user interfaces, emotions in HCI, aesthetic issues, HCI and children, evaluation methods and tools, and many others.

Prospective authors are invited to contribute to and help shape the conference through submissions of their research papers. High-quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, qualitative, or theoretical work in all areas of machine learning and computer science are cordially invited for presentation at the conference. The conference solicits contributions of extended abstracts and papers that address the themes of the conference, related to one or more of the following tracks:

Track - 1 Machine Learning Algorithms

• Machine Learning System Design
• Machine Learning Optimization
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Statistical Learning
• Transfer learning
• Extreme Learning Machines
• Kernel-based Learning
• Bayesian Learning
• Instruction-based Learning
• Adversarial Machine Learning

Track - 2 Deep and Transfer Learning

• Deep Neural Networks Optimization Algorithms
• Deep Feedforward Networks
• Deep Convolutional Neural Networks
• Deep Recurrent Neural Networks
• Sequence Modelling
• Deep Generative Models
• Generative Adversarial Networks
• Inference Dependencies on Multi-Layered Networks
• Tensors for Deep Learning
• Transfer Learning

 Track - 3 Applications of Machine Learning

• Healthcare
• Agriculture
• Biomedical informatics
• Computational Biology
• Transportation
• Malware detection
• Mobile applications
• Disaster Management
• Text Processing

Track – 4 Human–Computer Interaction

• HCI Theories and Methods
• Design Process Management
• UX (User Experience)
• DX and New Business Model
• Design Thinking
• Heuristics and Guidelines for Design
• Agent System and Intelligent Speaker
• Artificial Intelligence and IoT
• Robots, Avatars, and Virtual Humans
• Computer Vision
• Natural Language Processing
• Climate Science

Track - 5 Human–Environment Interactions

• VR, AR, MR, XR and Metaverse
• Gesture and Eye-gaze-based Interaction
• Audio–Visual Artificial Environment
• Computer Graphics and Virtual Trip
• Large System User Interface
• Mobile HCI and Automobiles
• Natural User Interface
• Brain Machine Interface

Track - 6 Learning and Creativity

• Creativity and Imagination
• e-Learning and Distant Learning
• Game Design and Game Mapping
• Game and Communication
• Gamification and Media Design

Prof. Dr. Kumar Manoj
Prof. Dr. Sharma Ajay
Dr. Singh Pardeep
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• machine learning
• human–computer interaction
• healthcare
• smart agriculture
• disaster management
• mobile applications
• artificial intelligence
• IoT