Johns Hopkins University is one of nine universities selected by Amazon for its new AI PhD Fellowship program, an initiative that will provide nearly $68 million in funding over two years to more than 100 doctoral students nationwide.
In its inaugural year, the program will support seven Whiting School of Engineering doctoral students studying core AI topics in areas including machine learning, computer vision, and natural language processing. Additionally, three new Amazon-funded Whiting School fellows were announced through the JHU + Amazon Initiative for Interactive AI (AI2AI).
The AI PhD Fellows, chosen based on their proposals for research projects that have the potential for significant societal impact, receive tuition, a stipend, fees, a travel grant, and mentorship from Amazon scientists, along with Amazon Web Services cloud-computing credits to support their computational research.
Each fellow is matched with an Amazon research liaison—a senior scientist whose expertise aligns with their work. This mentorship is essential to the program’s success, according to Whiting School Dean Ed Schlesinger. “The funding will enable our students to explore topics that are at the cutting edge of their areas of inquiry, but it is through mentorship that they’ll learn how to transform their groundbreaking ideas into deployable systems that can enhance people’s lives,” Schlesinger says.
Rohit Prasad, senior vice president and head scientist in Amazon’s Artificial General Intelligence views collaborating with the some of the brightest PhD students at the nation’s leading research universities as big win for Amazon. “What makes this program special is how it brings together Amazon’s real-world experience across diverse industries with the fresh perspectives of these top researchers to cultivate the next generation of AI leaders,” Prasad says.
The first cohort of JHU fellows comes from five engineering departments, and their project span areas from data-driven materials discovery for clean energy to enabling large language models to navigate the complexities of diverse cultural, and ethical contexts.
Computer science student Chuanyang Jin aims to develop AI systems with advanced social intelligence that can learn and coexist with humans, noting, “Social intelligence isn’t just a theoretical ideal in cognitive science—it is a practical necessity. These capabilities are essential for AI systems to operate safely and productively alongside people in ever-changing contexts.”
Yang Zhao, a civil and systems engineering student is inspired by how the rapid spread of technology boosted productivity and improved people’s lives in Gansu—the county in China where he grew up. His Amazon-supported research explores the potential of foundation models to enable economic growth and improve people’s safety and quality of life. “My objective is to enhance the efficiency, trustworthiness, and interpretability of foundation models for domain-specific tasks in areas such as transportation and public health,” he says.
The other Johns Hopkins AI PhD Fellows and their areas of research are:
- Amandeep Kumar (Electrical and Computer Engineering): Studies computer vision and generative AI with the aim of enhancing the efficiency of long-form video generation.
- Tianhao Li (Materials Science and Engineering): Focuses on data-driven materials discovery, including high-entropy materials for clean energy, and developing AI framework for efficient material identification.
- Yuxin Ma (Applied Mathematics and Statistics): Studies deep learning theory and the connections between data structure and neural network performance.
- Caio Netto (Applied Mathematics and Statistics): Works on geometry-aware learning for non-Euclidean data to improve large language models’ interpretability, robustness, and efficiency.
- Jingyu (Jack) Zhang (Computer Science): Explores natural language processing with a focus on foundational model safety and alignment.
This initiative builds on Amazon’s history of supporting academic research at Johns Hopkins and complements AI2AI, which since 2022 has provided funding for faculty research and 17 doctoral fellows in machine learning, computer vision, natural language understanding, and speech processing.
The 2025-2026 AI2AI Fellows are:
- Siyuan Huang (Electrical and Computer Engineering): Studies AI, computer vision, large language models, multimodal learning, and person re-identification.
- Yen-Ju Lu (Electrical and Computer Engineering): Focuses on bridging speech and text through multimodal large language models to create more reliable and efficient spoken language intelligence.
- Yiqing Shen (Computer Science): Develops visual foundation models aimed at understanding and interpreting visual information for applications across various fields.
In addition to Johns Hopkins University, the other participating universities are Carnegie Mellon University, the Massachusetts Institute of Technology, Stanford University, the University of California, Berkeley, the University of California, Los Angeles, the University of Texas at Austin, the University of Illinois Urbana-Champaign, and the University of Washington.