Core Viewpoint - The article discusses the 2024 ACM Doctoral Dissertation Award, highlighting the significance of the awarded research on human-AI collaboration in mental health support, addressing the shortage of professional psychologists and the increasing mental health issues globally [2][3][4]. Group 1: Awarded Research - The awarded dissertation by Ashish Sharma focuses on improving accessibility and quality of mental health support through human-AI collaboration, particularly in the context of a shortage of trained professionals [4][8]. - The AI-assisted mental health tool developed by Sharma has over 160,000 users, with more than 50% of them coming from households earning less than $40,000 annually [5]. - The research includes a randomized trial involving 300 peer supporters, demonstrating that AI feedback can enhance empathetic communication in conversations [10]. Group 2: Honorary Nominations - Two additional dissertations received honorary nominations: one explores the use of pseudorandom distributions to reveal inherent computational limitations in low-complexity models, while the other focuses on how large language models utilize vast amounts of training data [5][19]. - The first honorary nominated dissertation by Alexander Kelley discusses explicit pseudorandom distributions for restricted computation models [16]. - The second honorary nominated dissertation by Sewon Min examines the data usage in large language models, emphasizing their context learning capabilities and the development of nonparametric language models [19][21].