AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2025
Banafa, A.
Artificial intelligence in action: Real-world applications and innovations Book
River Publishers, 2025, ISBN: 978-877004619-0 (ISBN); 978-877004620-6 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model
@book{banafa_artificial_2025,
title = {Artificial intelligence in action: Real-world applications and innovations},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000403587&partnerID=40&md5=4b0d94be48194a942b22bef63f36d3bf},
isbn = {978-877004619-0 (ISBN); 978-877004620-6 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {River Publishers},
series = {Artificial Intelligence in Action: Real-World Applications and Innovations},
abstract = {This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning. The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change. The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force. As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks. This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution. © 2025 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model},
pubstate = {published},
tppubtype = {book}
}
2024
Villalobos, W.; Kumar, Y.; Li, J. J.
The Multilingual Eyes Multimodal Traveler’s App Proceedings Article
In: X.-S., Yang; S., Sherratt; N., Dey; A., Joshi (Ed.): Lect. Notes Networks Syst., pp. 565–575, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 23673370 (ISSN); 978-981973304-0 (ISBN).
Abstract | Links | BibTeX | Tags: AI in travel, Artificial intelligence in travel, Assistive navigation technologies, Assistive navigation technology, Assistive navigations, Human-AI interaction in tourism, Human-artificial intelligence interaction in tourism, Language Model, Military applications, Military operations, Multi-modal, Multilingual translations, Multimodal large language model, Multimodal LLMs, Navigation technology, Real- time, Real-time multilingual translation, Robots, Virtual Reality
@inproceedings{villalobos_multilingual_2024,
title = {The Multilingual Eyes Multimodal Traveler’s App},
author = {W. Villalobos and Y. Kumar and J. J. Li},
editor = {Yang X.-S. and Sherratt S. and Dey N. and Joshi A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201104509&doi=10.1007%2f978-981-97-3305-7_45&partnerID=40&md5=91f94aa091c97ec3ad251e07b47fa06e},
doi = {10.1007/978-981-97-3305-7_45},
isbn = {23673370 (ISSN); 978-981973304-0 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Lect. Notes Networks Syst.},
volume = {1004 LNNS},
pages = {565–575},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This paper presents an in-depth analysis of “The Multilingual Eyes Multimodal Traveler’s App” (MEMTA), a novel application in the realm of travel technology, leveraging advanced Artificial Intelligence (AI) capabilities. The core of MEMTA’s innovation lies in its integration of multimodal Large Language Models (LLMs), notably ChatGPT-4-Vision, to enhance navigational assistance and situational awareness for tourists and visually impaired individuals in diverse environments. The study rigorously evaluates how the incorporation of OpenAI’s Whisper and DALL-E 3 technologies augments the app’s proficiency in real-time, multilingual translation, pronunciation, and visual content generation, thereby significantly improving the user experience in various geographical settings. A key focus is placed on the development and impact of a custom GPT model, Susanin, designed specifically for the app, highlighting its advancements in Human-AI interaction and accessibility over standard LLMs. The paper thoroughly explores the practical applications of MEMTA, extending its utility beyond mere travel assistance to sectors such as robotics, virtual reality, and military operations, thus underscoring its multifaceted significance. Through this exploration, the study contributes novel insights into the fields of AI-enhanced travel, assistive technologies, and the broader scope of human-AI interaction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.},
keywords = {AI in travel, Artificial intelligence in travel, Assistive navigation technologies, Assistive navigation technology, Assistive navigations, Human-AI interaction in tourism, Human-artificial intelligence interaction in tourism, Language Model, Military applications, Military operations, Multi-modal, Multilingual translations, Multimodal large language model, Multimodal LLMs, Navigation technology, Real- time, Real-time multilingual translation, Robots, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
2023
Banafa, A.
Transformative AI: Responsible, Transparent, and Trustworthy AI Systems Book
River Publishers, 2023, ISBN: 978-877004018-1 (ISBN); 978-877004019-8 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AI, AI Ethics, Alexa, Augment Reality, Autoencoders, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, ChatGPT, Cloud computing, CNN, Computer vision, Conditional Automation, Convolutional Neural Networks, Cryptocurrency, Cybersecurity, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Entanglement, Ethereum, Explainable AI. Environment and sustainability, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, High Automation, Hybrid Blockchain, IEEE, IIoT, Industrial Internet of Things, Internet of Things, IoT, Jarvis, Long Short-Term Memory Networks, LTE, Machin Learning, Microsoft, Narrow AI, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, NYTimes, Open Source, Partial Automation, PayPal, Private Blockchain, Private Cloud Computing, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum Internet. Wearable Computing Devices (WCD). Autonomic Computing, Quantum Machine Learning (QML), R2D2, Reactive Machines . Limited Memory, Recurrent Neural Networks, Robots, Sci-Fi movies, Self-Aware, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Super AI, Superposition, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice User Interface, VUI, Wearable Technology, Wi-Fi, Zero-Trust Model
@book{banafa_transformative_2023,
title = {Transformative AI: Responsible, Transparent, and Trustworthy AI Systems},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180544759&partnerID=40&md5=c1fcd00f4b40e16156d9877185f66554},
isbn = {978-877004018-1 (ISBN); 978-877004019-8 (ISBN)},
year = {2023},
date = {2023-01-01},
publisher = {River Publishers},
series = {Transformative AI: Responsible, Transparent, and Trustworthy AI Systems},
abstract = {Transformative AI provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment. The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy. The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities. Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years. © 2024 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AI, AI Ethics, Alexa, Augment Reality, Autoencoders, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, ChatGPT, Cloud computing, CNN, Computer vision, Conditional Automation, Convolutional Neural Networks, Cryptocurrency, Cybersecurity, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Entanglement, Ethereum, Explainable AI. Environment and sustainability, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, High Automation, Hybrid Blockchain, IEEE, IIoT, Industrial Internet of Things, Internet of Things, IoT, Jarvis, Long Short-Term Memory Networks, LTE, Machin Learning, Microsoft, Narrow AI, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, NYTimes, Open Source, Partial Automation, PayPal, Private Blockchain, Private Cloud Computing, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum Internet. Wearable Computing Devices (WCD). Autonomic Computing, Quantum Machine Learning (QML), R2D2, Reactive Machines . Limited Memory, Recurrent Neural Networks, Robots, Sci-Fi movies, Self-Aware, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Super AI, Superposition, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice User Interface, VUI, Wearable Technology, Wi-Fi, Zero-Trust Model},
pubstate = {published},
tppubtype = {book}
}
DeChant, C.; Akinola, I.; Bauer, D.
Learning to summarize and answer questions about a virtual robot’s past actions Journal Article
In: Autonomous Robots, vol. 47, no. 8, pp. 1103–1118, 2023, ISSN: 09295593 (ISSN).
Abstract | Links | BibTeX | Tags: Action sequences, E-Learning, Interpretability, Language Model, Long horizon task, Long horizon tasks, Natural language processing systems, Natural languages, Question Answering, Representation learning, Robots, Summarization, Video frame, Virtual Reality, Virtual robots, Zero-shot learning
@article{dechant_learning_2023,
title = {Learning to summarize and answer questions about a virtual robot’s past actions},
author = {C. DeChant and I. Akinola and D. Bauer},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176588341&doi=10.1007%2fs10514-023-10134-4&partnerID=40&md5=162b3343d5f000f2b79f59c339f99022},
doi = {10.1007/s10514-023-10134-4},
issn = {09295593 (ISSN)},
year = {2023},
date = {2023-01-01},
journal = {Autonomous Robots},
volume = {47},
number = {8},
pages = {1103–1118},
abstract = {When robots perform long action sequences, users will want to easily and reliably find out what they have done. We therefore demonstrate the task of learning to summarize and answer questions about a robot agent’s past actions using natural language alone. A single system with a large language model at its core is trained to both summarize and answer questions about action sequences given ego-centric video frames of a virtual robot and a question prompt. To enable training of question answering, we develop a method to automatically generate English-language questions and answers about objects, actions, and the temporal order in which actions occurred during episodes of robot action in the virtual environment. Training one model to both summarize and answer questions enables zero-shot transfer of representations of objects learned through question answering to improved action summarization. © 2023, The Author(s).},
keywords = {Action sequences, E-Learning, Interpretability, Language Model, Long horizon task, Long horizon tasks, Natural language processing systems, Natural languages, Question Answering, Representation learning, Robots, Summarization, Video frame, Virtual Reality, Virtual robots, Zero-shot learning},
pubstate = {published},
tppubtype = {article}
}