机器之心编辑部 刚刚，美国计算机协会 ACM（Association for Computing Machinery）公布了最新一届会士名单。 本年度新入选科学家中共有 71 人，他们的贡献涉及计算机图形学、网络安全、人机交互、数据管理、机器 学习、人工智能、算法、可视化等领域。 ACM 主席 Yannis Ioannidis 表示：这份入选名单代表了「我们领域当前正在发生的事情的快照。例如，今年 我们要表彰在计算机架构和软件工程等成熟学科工作的成员，以及在群体智能或场景识别等新兴学科的创 新者。」 机器之心对这些华人入选者进行了简单介绍（如有遗漏或错误，欢迎在留言区指正）。 Pei Cao ACM 创立于 1947 年，是全世界计算机领域影响力最大的专业学术组织之一。 ACM Fellow 是由该组织授予资深会员的荣誉，目的为表彰会员中对于计算机相关领域贡献前 1% 的学者， 其审查过程十分严格，每年遴选一次，研究员由同行提名，提名由委员会审查。 Pei Cao 是一位在业界极具影响力和知名度的技术专家与工程领导者。她曾先后在多家信息技术巨头任职， 包括谷歌和脸书，目前担任 YouTube 公司的工程副总裁 ...

其中，夏大文教授领衔的《面向智能终端的射频前端系统集成与视觉感知关键技术及应用》获科技进步 奖一等奖；廖娟博士、曾凡菊教授分别领衔的项目获自然科学奖二、三等奖；汤敏丽博士、吴小平教授 领衔的项目分获教育科普奖二、三等奖。 转自：贵州日报 本报讯（记者 夏华）近日，以"数智赋能 可信先行"为主题的贵州省计算机学会学术年会在贵阳召开， 凯里学院申报的5项成果获科技奖项。 ...

Core Insights - A total of 61 new leaders in the field of computer science have been inducted as ACM Distinguished Members, recognizing their significant contributions across various domains including medical AI, data management, and human-computer interaction [1][3][4]. Group 1: ACM Distinguished Members Program - The ACM Distinguished Members program, initiated in 2006, honors members who have demonstrated outstanding technical achievements and professional service, with only the top 10% of global members eligible for induction [4]. - Inductees must have at least 15 years of professional experience and have made a substantial impact in the computing field [4]. Group 2: Notable Inductees - Jianfei Cai from Monash University was recognized for his contributions to visual language understanding and visual computing [6]. - Sheng Di from Argonne National Laboratory was honored for his work in lossy compression and high-performance computing resilience [8]. - Daxin Jiang, founder of StepFun, received recognition for his contributions to context-aware search and language model expansion [10]. - Yu-Gang Jiang from Fudan University was acknowledged for his work in large-scale video analysis [14]. - Weiyi Shang from the University of Waterloo was recognized for his contributions to software performance and log engineering [18]. - Nan Tang from Hong Kong University of Science and Technology was honored for his work in AI-based data preparation [20]. - Huamin Wang from Style3D was recognized for his contributions to physics-based modeling and simulation in computer graphics and vision [24]. - Yubin Xia from Shanghai Jiao Tong University was acknowledged for his work in hardware-software co-design in computer systems [26]. - Junsong Yuan from the University at Buffalo was recognized for his contributions to human behavior and interaction modeling based on video [28]. - Mi Zhang from Ohio State University was honored for his work in mobile AI and AIoT applications [30]. - Rui Zhang from Huazhong University of Science and Technology was recognized for his contributions to data-centric systems and AI-driven big data applications [31]. - Ying Zhang from Meta was acknowledged for her contributions to the design and operation of large-scale production networks [33]. - Lei Zou from Peking University was recognized for his work in graph database query processing and optimization [35].

第三次工业革命后，互联网技术的广泛应用，计算机相关技术和产业的崛起，极大地改变了人类的生活 和生产方式。如果没有互联网的普及，今天我们可能连不出门就知天下事的便利都无法享受到。 接下来是德国。为了实现扩张计划，德国投入了大量资源，虽然经济和工业一度崩盘，但在战后成功重 建后，德国逐步迎来了经济的飞跃。进入21世纪后，德国继续稳固在欧盟的政治地位，同时在经济和科 技领域也不断取得进展。据了解，德国目前拥有45位顶尖计算机科学家，在第五次工业革命中，德国走 在了许多国家的前面。 最后看看中国。在中国，民众逐渐认识到互联网普及带来的巨大变革，但也意 识到如果在这一领域缺乏话语权，将是多么的危险。改革开放后，中国经济腾飞，人民的生活水平逐步 提高，从解决温饱问题到追求更高层次的发展，国家迅速迈向现代化。 为提升中国的计算机科技实力，计算机相关课程逐渐进入高校，中国的飞速发展与这些人才的培养密切 相关。据统计，中国目前在计算机领域拥有29位全球顶尖的科学家，未来在他们的推动下，中国在这一 领域有望取得更大突破。 总的来说，美国的科技水平越高，其经济、科技、文化等各个领域的飞跃发展也就越加明显。而美国成 为了全球更多科学 ...

Historical Context & Gender Bias in Computer Science - The field of computing was initially filled with women, but their work was often seen as clerical rather than coding [1] - Unlike other academic subjects, female participation in computer science declined after the peak of second-wave feminism in the 1970s [1] - Sexist advertisements and articles in the 1960s portrayed women in computing as primarily valued for their appearance or ability to support men [1] - The erasure of individual women's contributions in computer science was aided by referring to them as groups (e g, "the Eniac Girls") rather than by name [2] Barriers to Women's Advancement - Subtle discrimination, such as undermining comments and being relegated to menial tasks, significantly limited women's flourishing in computer science [2] - Women in computer science at MIT experienced a "fishbowl syndrome," feeling isolated and constantly scrutinized [2] - Lack of female mentors and encouragement in the 1980s contributed to women leaving the field [2] Call to Action & Future Outlook - Small changes in words, actions, and self-reflection about assumptions are crucial for creating an inclusive future [3][4] - Asking hard questions about actions in industry, academia, and social situations is essential for progress [4][5] - Recognizing women's individual contributions and autonomy is a necessary step, as progress is ongoing [6] - Allies, both female and male, are essential for creating a supportive environment [9]

Until he was named South Korea’s new science minister in July, Bae Kyung-Hoon was largely unknown in political circles, having spent his career focused on computer science https://t.co/EcxaOPP0mW ...

least I could do is like you know wear less wear clothes because my story isn't stitched into the clothes in fact it's stitched into every phase that I've taken that brought me here and um let me ask you one thing how many of you have joined engineering um let's say out of family any hands raised I think it's a big number uh don't worry I'm also that confused keep as well um I mean I'm fascinated of computers from childhood like I would say full standard and my loving mom wants me to become a doctor and she ...

Generative AI Impact on Identity - Generative AI models pose a serious threat to human identity by enabling the creation of fake versions of individuals using their data [6] - AI models can mimic voices with short audio recordings, leading to misuse, as seen with celebrities like Tom Hanks and Scarlett Johansson [7] - Scammers are using AI to generate fake faces and voices of loved ones to deceive seniors, and harmful content like undressing apps is being created [8] Impact on Creative Professionals - Generative AI models are trained to mimic the creations of artists, impacting their identity and livelihoods [11] - Artists are losing jobs and income due to AI-generated mimics overshadowing their work, leading some to quit or reconsider their careers [12] - Artists face a dilemma: share their work and risk it being used to train AI models, or disconnect from the community [13][14] Solutions and Tools - Glaze and Nightshade were developed as tools to protect visual artists by adding modifications to artwork that mislead AI models [16][17] - Glaze protects artistic style, while Nightshade protects individual objects or copyrighted characters [18][19] - These tools have been downloaded over 10 million times by artists from more than 160 countries [21] Regulatory and Future Considerations - The research team testified in front of state legislatures in California and Illinois on data and identity privacy, leading to regulation bills being signed into law [23] - New protective tools are being developed to disrupt deep fake facial models and undressing apps, with other researchers working on protecting audio and music [24] - Protecting creativity and identity is essential for the future, as highlighted by children's concerns [26][27]

Core Viewpoint - The 2025 China Computer Conference opened in Harbin, Heilongjiang Province, focusing on the theme "Digital Intelligence Empowerment, Infinite Possibilities" to explore advancements and future trends in digital intelligence technology [1] Group 1: Conference Overview - The conference is organized by the China Computer Society and hosted by Harbin Engineering University and Harbin Institute of Technology [1] - It aims to promote the deep integration of computing technology with economic and social development [1] Group 2: Topics and Sessions - The conference features over 150 specialized forums covering nine thematic areas, including foundational models of artificial intelligence, machine learning theory and mechanisms, data management and governance for AI, reinforcement learning, and reasoning [1] - Key areas of focus include artificial intelligence, big data, and cloud computing, which are currently trending topics in the industry [1]

Core Insights - The article discusses the urgent need for advanced network infrastructure to support large language model training and data center security in the context of rapid advancements in intelligent computing and future networks [2][3]. Group 1: Research Achievements - The research group led by Assistant Professor Liu Guyue from Peking University has made significant contributions, with five high-level papers accepted at ACM SIGCOMM 2025, making it the highest-publishing research group from a university this year [2][3]. - The acceptance rate for SIGCOMM 2025 was only 16.1%, with 461 submissions and only 74 accepted [2]. Group 2: Key Research Papers - **InfiniteHBD**: Proposes a transceiver-centered high-bandwidth domain architecture that overcomes scalability and fault tolerance issues in large model training, achieving a cost reduction to 31% of NVL-72 and nearly zero GPU waste [6][8]. - **DNSLogzip**: Introduces a novel approach for fast and high-ratio compression of DNS logs, reducing storage costs by approximately two-thirds, saving up to $163,000 per month per DNS service node [11][12]. - **BiAn**: A framework based on large language models for intelligent fault localization in production networks, reducing root cause identification time by 20.5% and improving accuracy by 9.2% [13][14]. - **MixNet**: A runtime reconfigurable optical-electrical network structure for distributed mixture-of-experts training, enhancing network cost efficiency by 1.2 to 2.3 times under various bandwidth conditions [15][18]. - **Mazu**: A high-speed encrypted traffic anomaly detection system implemented on programmable switches, successfully protecting over ten million servers and detecting malicious traffic with approximately 90% accuracy [19][22]. Group 3: Overall Impact - The five research outcomes collectively form a comprehensive technological loop across architecture, data, operations, and security, driving the efficient, reliable, and intelligent development of next-generation network systems [3].