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Learning 101 reloaded: Revisiting the basics for the GenAI era

December 27, 2024 by Junaid Qadir

In this paper, we delve into the transformative landscape of education amidst the disruptive advances of generative AI (GenAI), characterized by an unprecedented capacity to generate new information with tools such as ChatGPT. Building upon my previous publication, “Learning 101: the Untaught Basics,” in this magazine, I interrogate what has changed since then and how learners … [Read more...] about Learning 101 reloaded: Revisiting the basics for the GenAI era

Computational approaches in mental health

May 24, 2024 by Shamal Lalvani, Leandros Stefanopoulos, Nicos Maglaveras, Aggelos K. Katsaggelos

< In the past few decades, technology has played a considerable role in medical research. For example, advances in machine learning algorithms have allowed for automatic diagnosis of medical conditions, through techniques involving neuroimaging data, electronic health records and physiological biomarkers. Research in the past few decades has also resulted in a … [Read more...] about Computational approaches in mental health

Meal delivery services: Current practices, challenges, and future directions

February 6, 2024 by Maria Michalopoulou

Meal delivery services have undergone a tremendous evolution during the last decade and, according to market predictions, this trend will continue to grow in the following years. The service growth forecast in combination with the high complexity of the problem indicate the importance of achieving efficient solutions. This article presents a detailed description of the meal … [Read more...] about Meal delivery services: Current practices, challenges, and future directions

Understanding social conventions for socially aware robot navigation

June 13, 2023 by Kiran Jot Singh

Navigation is an essential skill for autonomous robots, and it becomes a cumbersome task in human-populated environments. Robots need to perform their tasks without disturbing the people around them. Robots navigating in a human-populated environment need to ensure people’s comfort and safety. For more about this article see link … [Read more...] about Understanding social conventions for socially aware robot navigation

An underwater explorer remotely operated vehicle: Unraveling the secrets of the ocean

June 9, 2023 by Xiang-Rui Huang

In recent years, underwater robots have been an essential focus of marine science and technology applications. Whether it is the application of military tasks or general civil affairs, underwater robots have played a significant role. For example, unmanned underwater vehicles (UUVs) can work in the sea for a long time, have high maneuverability, and perform various underwater … [Read more...] about An underwater explorer remotely operated vehicle: Unraveling the secrets of the ocean

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About the Magazine

IEEE Potentials Magazine is the publication dedicated to undergraduate and graduate students and young professionals. IEEE Potentials explores career strategies, the latest in research, and important technical developments. Through its articles, it also relates theories to practical applications, highlights technology’s global impact, and generates international forums that foster the sharing of diverse ideas about the profession.

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Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

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