Arijit Ukil
Joao Gama
ABSTRACT
The management of knowledge-driven artificial intelligence technologies is essential in order to evaluate their impact on human life and society. Social networks and tech use can have a negative impact on us physically, emotionally, socially and mentally. On the other hand, intelligent systems can have a positive effect on people's lives. Currently, we are witnessing the power of large language models (LLMs) like chatGPT and its influence towards the society. The objective of the workshop is to contribute to the advancement of intelligent technologies designed to address the human condition. This could include precise and personalized medicine, better care for elderly people, reducing private data leaks, using AI to manage resources better, using AI to predict risks, augmenting human capabilities, and more. The workshop's objective is to present research findings and perspectives that demonstrate how knowledge-enabled technologies and applications improve human well-being. This workshop indeed focuses on the impacts at different granularity levels made by Artificial Intelligence (AI) research on the micro granular level, where the daily or regular functioning of human life is affected, and also the macro granulate level, where the long-term or far-future effects of artificial intelligence on people's lives and the human society could be pretty high. In conclusion, this workshop explores how AI research can potentially address the most pressing challenges facing modern societies, and how knowledge management can potentially contribute to these solutions.
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- Arijit Ukil, Soma Bandyoapdhyay, Chetanya Puri, Arpan Pal, and Kayapanda Mandana. 2016. Cardiac condition monitoring through photoplethysmogram signal denoising using wearables: can we detect coronary artery disease with higher performance efficacy?. In 2016 Computing in Cardiology Conference (CinC). IEEE, 281--284.Google ScholarCross Ref
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- Arijit Ukil, Leandro Marin, and Antonio Jara. 2022. ADV-ResNet: Residual Network with Controlled Adversarial Regularization for Effective Classification of Practical Time Series Under Training Data Scarcity Problem. In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8.Google Scholar
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- Arijit Ukil, Leandro Marin, and Antonio J Jara. 2023. Priv-Aug-Shap-ECGResNet: Privacy Preserving Shapley-Value Attributed Augmented Resnet for Practical Single-Lead Electrocardiogram Classification. In ICASSP 2023--2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 1--5.Google Scholar
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- Arijit Ukil, Leandro Marin, Subhas Chandra Mukhopadhyay, and Antonio J Jara. 2022. AFSense-ECG: Atrial fibrillation condition sensing from single lead electrocardiogram (ECG) signals. IEEE Sensors Journal 22, 12 (2022), 12269--12277.Google ScholarCross Ref
- Arijit Ukil and Uttam Kumar Roy. 2017. Smart cardiac health management in IoT through heart sound signal analytics and robust noise filtering. In 2017 IEEE 28th annual international symposium on personal, indoor, and mobile radio communications (PIMRC). IEEE, 1--5.Google Scholar
- Arijit Ukil, Ishan Sahu, Angshul Majumdar, Sai Chander Racha, Gitesh Kulkarni, Anirban Dutta Choudhury, Sundeep Khandelwal, Avik Ghose, and Arpan Pal. 2021. Resource constrained CVD classification using single lead ECG on wearable and implantable devices. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 886--889.Google ScholarCross Ref
- Arijit Ukil and Jaydip Sen. 2010. Secure multiparty privacy preserving data aggregation by modular arithmetic. In 2010 First International Conference On Parallel, Distributed and Grid Computing (PDGC 2010). IEEE, 344--349.Google ScholarCross Ref
Index Terms
- Knowledge-driven Analytics and Systems Impacting Human Quality of Life- Neurosymbolic AI, Explainable AI and Beyond
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