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Open source chip design using Efabless [Beyond the Degree]

October 12, 2026 by Ihfaz Islam, Harpreet Singh, Lubna Alazzawi, Mohammad Asfar Khan, Kunal Ghosh

It is anticipated that the private sector in the United States will invest US$400 billion to US$500 billion in design over the next 10 years for electronic chip development. The anticipation in the global world market is similar. Because of this, there is an increasing interest in the design and development of chips among graduate students all over the world. For the last 50 … [Read more...] about Open source chip design using Efabless [Beyond the Degree]

Assessment of musical representations using a music information retrieval technique

November 1, 2021 by Valentina Hernández-López, Néstor Darío Duque-Méndez, and Mauricio Orozco-Alzate

While learning to play a musical instrument, a student does not always have the support of a specialized teacher to guide and assess his or her daily practice. The lack of guidance and untimely feedback can be demotivating for successful study. Lerch et al. (2019), in a recent study, suggest that performance assessment is an important aspect in music pedagogy: “Students rely on … [Read more...] about Assessment of musical representations using a music information retrieval technique

Agriculture as a service

November 1, 2021 by Shitala Prasad, Sateesh K. Peddoju, and Debashis Ghosh

In this emerging digital world, mobile devices are the leading technologies available and used by almost everyone everywhere in every field. These ubiquitous devices have become part of our modern lifestyle and have proven to be affordable tools for farmers. If these devices could assist in farming, it would contribute a great deal toward developing the socioeconomy of any … [Read more...] about Agriculture as a service

Alexa-based voice assistant for smart home applications

July 1, 2021 by Clara Jiménez, Edgar Saavedra, Guillermo del Campo, and Asunción Santamaría

Today, the Internet of Things (IoT) is becoming an essential player in creating a new smart era. The communication through the Internet to IoT devices enables new applications in multiple environments, including smart buildings and cities. The IoT market is projected to grow to 75.4 billion connected devices by 2020. Within the IoT ecosystem, smart home technology is also … [Read more...] about Alexa-based voice assistant for smart home applications

Would you be interested in a corporate start-up?

May 1, 2021 by Mike Tinskey

A street sign that says "Start Up."

Entrepreneurship. Innovation. Creativity. While these words may spark some sort of inspiration within you, most people would associate these ingenuity concepts with start-ups. But it is not only startups that need entrepreneurs. In today's world, high-performing companies need to constantly reinvent themselves. They must consistently find new products and services to stay … [Read more...] about Would you be interested in a corporate start-up?

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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.

POPULAR ARTICLE

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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