何恺明MIT两名新弟子曝光：首次有女生入组，另一位是FNO发明者，均为华人

Core Insights - The article highlights the recruitment of two new Chinese students, Hu Keya and Li Zongyi, by AI expert He Kaiming at MIT, emphasizing their impressive academic backgrounds and contributions to the field of AI [1][4]. Group 1: Hu Keya's Background and Achievements - Hu Keya graduated from Shanghai Jiao Tong University and was involved in the Brain-Machine Interface Laboratory, focusing on AI applications in neuroscience [5][7]. - She authored a paper on self-supervised EEG representation learning, which was accepted at the EMBC conference, and presented her work in the U.S. [8][10]. - Hu participated in a project that improved self-supervised learning, leading to a paper accepted at the Cognitive Science 2025 conference [10]. - During her undergraduate studies, she interned at Cornell University, contributing to a project on program synthesis and code repair, resulting in a paper accepted at NeurIPS 2024 [11][12]. - Hu Keya led her team to win the "Best Paper Award" at the ARC Prize 2024 competition, showcasing her innovative approach to AI problem-solving [15][17]. - By the end of her undergraduate studies, she had published four high-impact papers, making her a highly sought-after candidate for PhD programs, ultimately choosing MIT [21][22]. Group 2: Li Zongyi's Contributions - Li Zongyi, known for his work on the Fourier Neural Operator (FNO), published a significant paper during his PhD that enabled the large-scale application of neural operators [27][29]. - The FNO allows neural networks to learn solutions to physical equations efficiently, significantly improving computational speed in various scientific applications [30][34]. - Li Zongyi's research has made him a key figure in the field of neural operators, with over 12,000 citations of his work [36]. - Currently, he is a postdoctoral researcher at MIT and is set to join New York University as an assistant professor in the upcoming fall [38][39]. Group 3: He Kaiming's Research Focus - He Kaiming has indicated that "AI for Science" will be a primary focus of his research in the coming years, aligning with the expertise of his newly recruited team members [46][48]. - The combination of Hu Keya's background in neuroscience and Li Zongyi's expertise in neural operators strengthens the team's capabilities in advancing AI applications in scientific research [48][49].