华人AI科学家视频系列之一 扎克伯格最近疯抢AI科学家，尤其是华人科学家，动不动就开出1亿美元甚至2亿美元的薪酬包。 有一位AI大神似乎被忽略了。 今年3月，Facebook首席AI科学家杨立昆在一次访谈中，提到了"一件不为人知的事"，科学（AI）领域 被引用次数最多的论文，是关于深度学习领域的，来自10年前的2015年，这篇论文起源于北京。 这篇论文的主要作者叫做，何恺明。 《自然》杂志给出了一个21世纪引用量最高的最新Top 25，排在第一位的就是"Deep Residual Learning for Image Recognition"， 是一篇关于ResNets研究的论文，作者包括何恺明、张祥雨、任少卿和孙剑。 何恺明是何方神圣？ 何恺明1984年出生于广州，他在执信中学的时候，因为获得全国物理竞赛一等奖，拿到了清华大学的保 送资格，但他还是参加高考来证明自己。以标准分900分的成绩，成为当年广东省9位满分状元之一。 2007年何恺明进入香港中文大学读研，师从汤晓鸥。港中大认识何凯明的，都说他是超级拼命三郎，早 上六点多出门晚上十二点回寝室，天才还这么拼命，"普通人没法玩"。2011年博士毕业后，进入 ...

Core Viewpoint - Kaiming He, a prominent figure in computer vision, has recently joined Google DeepMind as a part-time distinguished scientist after obtaining tenure at MIT, indicating a strategic collaboration between academia and industry in AI research [1][2][5][7]. Group 1: Kaiming He's Career and Achievements - Kaiming He is recognized as a legendary figure in the computer vision field, having received his undergraduate degree from Tsinghua University and his PhD from the Chinese University of Hong Kong under the supervision of Xiaodong Wu [9][10]. - He co-authored the award-winning paper "Single Image Haze Removal Using Dark Channel Prior" in 2009, marking a significant achievement for Asian researchers in the CVPR conference [10]. - After completing his PhD in 2011, he worked at Microsoft Research Asia and later joined Facebook AI Research (FAIR), where he developed the influential ResNet architecture, which has been cited over 280,000 times [11][12][15]. - His research contributions include notable works like Faster R-CNN and Mask R-CNN, the latter winning the best paper award at ICCV 2017 [15][18]. Group 2: Recent Developments and Collaborations - Kaiming He joined MIT's EECS department in 2023, marking a return to academia after a significant tenure in the industry, which garnered attention and speculation about Meta's loss [16][18]. - His recent research focuses on model performance optimization, including advancements in image generation techniques and the development of highly compressed tokenizers for text generation [20]. - He has collaborated with Google DeepMind on various projects, including the paper "Fractal Generative Models," which introduced a new paradigm for generating high-resolution images [22][23]. - The collaboration with DeepMind has been ongoing, with previous joint efforts addressing challenges in visual autoregressive models and proposing solutions for scaling these models [25][27].