Mechanical Engineering: Research Guide

Emotions are a fundamental part of human psychology—a complex process that has long distinguished us from machines. Even advanced artificial intelligence (AI) lacks the capacity to feel. However, researchers are now exploring whether the formation of emotions can be computationally modeled, providing machines with a deeper, more human-like understanding of emotional states.

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.

A speech study by a research team from The University of Texas at El Paso has identified an underappreciated aspect of speech in English and Spanish speakers that could lead to improvements in artificial intelligence (AI) spoken dialogue systems.

Large Language Models, like ChatGPT, are learning to play Dungeons & Dragons. The reason? Simulating and playing the popular tabletop role-playing game provides a good testing ground for AI agents that need to function independently for long stretches of time.

If you use consumer AI systems, you have likely experienced something like AI "brain fog": You are well into a conversation when suddenly the AI seems to lose track of the different ideas you have been talking about and how they fit together.

The data inputs that enable modern search and recommendation systems were thought to be secure, but an algorithm developed by Cornell Tech researchers successfully teased out names, medical diagnoses and financial information from encoded datasets.

Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but many systems struggle when real-world data do not match ideal conditions. Measurements collected from different instruments, experiments or simulations often vary widely in resolution, noise and reliability. Traditional machine-learning models typically assume those differences are negligible—an assumption that can limit accuracy and trustworthiness.

The sheen of satin, the subtle glints of twill, the translucence of sheer silk: Fabric has long been difficult to render digitally because of the myriad ways different yarns can be woven or knitted together.

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI models. Unlike generative diffusion models, the team's Discrete Spatial Diffusion approach honors scientific and physics principles. The team validated their model on two challenging scientific applications—subsurface rock microstructures and lithium-ion battery electrodes—with promising results.

커프 없이 비침습 혈압 측정이 가능한 초음파 센서 개발 - 기계연-KIST, 인체 피부부착형 PMN-PT 초음파 센서 세계 최초 개발 - - 커프 없이 연속 혈압 측정 가능… 의료·헬스케어 웨어러블 기술의 새 전환점 - - 유연기판·저온 솔더 공정으로 고성능 압전 초음파소자 구현, 초음파 혈압센서 상용화 기대 - □

In Proceedings of the SIGGRAPH Asia 2025 Conference Papers, a research team affiliated with UNIST reports a new AI technology that can animate 3D characters to mimic the exact movements shown in a single 2D image, all while preserving natural proportions and avoiding distortions. This development could reduce the barriers to creating 3D content for the metaverse, animation and gaming industries.

Artificial intelligence (AI), particularly deep learning models, are often considered black boxes because their decision-making processes remain difficult to interpret. These models can accurately identify objects—such as recognizing a bird in a photo—but understanding exactly how they arrive at these conclusions is a significant challenge. Until now, most interpretability efforts have focused on analyzing the internal structures of the models themselves.

□ 국가과학기술연구회(이사장 김영식) 산하 한국기계연구원(원장 류석현, 이하 기계연)은 한국산업안전보건공단이 주관한 ‘근로자 건강증진활동 우수사업장’으로 재선정돼, 지난 12월 17일 선정패를 수여받았다. 이번 재선정은 2022년 최초 인증 이후 두 번째로, 기계연은 향후 3년간 우수사업장 자격을 유지하게 된다. □ ‘

Video games have come to be regarded as valuable educational resources. Through a combination of interactive environments and learning objectives, they have proven to be an effective tool in multiple fields, from school education to corporate training. However, their full adoption in formal education remains limited by a lack of curricular integration and clear strategies to incorporate them into educational programs, a lack of specific teacher training and a shortage of technological and technical resources.

At first glance, artificial intelligence looks like a software developer's dream. A recent McKinsey & Company report found that programmers generated code up to 45% faster with the help of generative AI.

"Brainrot" is what many people call the chaotic, fast-moving memes, sounds and catchphrases that spread across TikTok, Roblox and online gaming and into playgrounds. An example is the endlessly repeated chant of "six-seven," which still echoes through houses and schools across the country—to the bewilderment (or annoyance) of many teachers and parents.

KIMM-NEXT 50, “기계로 50년, 세상을 움직이다!” - 기계연 류석현 원장, 2026년 시무식에서 'KIMM-NEXT 50' 선언 - - 새로운 50년의 출발로 대한민국 기계기술과 제조혁신 선도 - □ 한국기계연구원(원장 류석현, 이하 기계연)이 창립 50주년을 맞아 ‘KIMM-NEXT 50, 새로운 50년의 출

A research team affiliated with UNIST has unveiled a novel AI system capable of grading and providing detailed feedback on even the most untidy handwritten math answers—much like a human instructor.

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to four-digit multiplication, a task taught in elementary school, even state-of-the-art systems fail. Why?

Every task we perform on a computer—whether number crunching, watching a video, or typing out an article—requires different components of the machine to interact with one another. "Communication is massively crucial for any computation," says former SFI Graduate Fellow Abhishek Yadav, a Ph.D. scholar at the University of New Mexico. But scientists don't fully grasp how much energy computational devices spend on communication.

누구나 버튼 한 번으로 식중독 진단… 기계연, 자동화 통합 시스템 개발 - 기계연, 탈리·전처리·분자진단 통합한 ‘식중독균 16종 고속 전자동 진단 시스템’ 국내 최초 개발- - 버튼 한 번으로 식중독 검사까지… 식품 안전관리의 패러다임 전환 - - 현장에서 비전문가도 1시간 내 결과

You might have seen headlines sounding the alarm about the safety of an emerging technology called agentic AI.

MIT researchers have developed a new method for designing 3D structures that can be transformed from a flat configuration into their curved, fully formed shape with only a single pull of a string.

Whether you're a scientist brainstorming research ideas or a CEO hoping to automate a task in human resources or finance, you'll find that artificial intelligence (AI) tools are becoming the assistants you didn't know you needed. In particular, many professionals are tapping into the talents of semi-autonomous software systems called AI agents, which can call on AI at specific points to solve problems and complete tasks.