Features

Edge technologies bring data storage and data processing closer to where data is generated. That simple shift has big benefits. While cloud computing relies on sending data back and forth between a centralized server, edge computing performs computation closer to the source, reducing latency and bandwidth usage. As applications increasingly rely on ultra-fast, near-instantaneous connections, edge technologies are an essential tool for enabling them.

Materials engineers study, design, and manipulate the properties of materials. Their work can enable entirely new products, or help to improve existing ones. This is a deeply multidisciplinary field, bringing together principles of physics, chemistry, and engineering. And several of the research challenges it’s facing are related to the most pressing challenges in the world.

Many companies are turning towards cutting-edge technology known as “carbon capture” or “carbon removal” to tackle this issue. Carbon capture stores or utilizes carbon emissions from industrial processes before entering the atmosphere, whereas carbon removal removes excess carbon from the environment.

Climate change is real. Its effects are drastic, and worsening. Global efforts to cut emissions and reduce fossil fuel consumption have met with mixed results. To mitigate the most catastrophic outcomes of climate change, some engineers are turning to outside-the-box ideas like solar radiation management.

This guide reveals how to ace a candidate interview for engineering school at the undergraduate and graduate levels. It includes a resource guide for preparation and how to draft stellar responses to common questions.

Data science is an interdisciplinary field that leverages scientific methods, processes, algorithms, and systems to extract insights and knowledge from both structured and unstructured forms of data. It’s commonly associated with big data and artificial intelligence, combining statistics, data analysis, machine learning, and related techniques to understand and analyze actual phenomena with data.

AI’s integration into the architectural landscape is a testament to the industry’s readiness for technological evolution, and it continues to shape the future of architectural design. “It goes hand in hand with computer science developments. It’s a long legacy,” says Dr. Daniel Koehler, assistant professor at the University of Texas at Austin School of Architecture.

Mechanical engineering is one of the oldest and broadest engineering disciplines. Its domain stretches across complex mechanical systems’ design, analysis, manufacturing, and maintenance. While mechanical engineering has played (and continues to play) an enormous role in the evolution of the automobile, it represents just one area of a massively important discipline.

Launched into the mainstream with ChatGPT, today’s generative AI models have applications in every field and discipline; tomorrow’s impacts will be wide-reaching. Given its broad applications, the challenges within AI are many. Its transformative power works in both directions and the potential risks are roughly commensurate with the potential rewards.

Electrical engineering is a rich field with challenges for tomorrow’s engineers. Sitting at one of the most interesting crossroads of science and technology, its territory stretches across microelectronics, energy systems, telecommunications, and robotics. Much overlap exists between its different research areas, and that overlap is mimicked in many of the field’s largest potential breakthroughs.