Fellowships for PHD Students

The JHU + Amazon Initiative for Interactive Artificial Intelligence (AI2AI) invites applications from outstanding PhD students for fellowships in the 2023-2024 academic year. Awardees, who will be designated Amazon Fellows, will receive a full stipend, 20% tuition, and student health insurance for the fall 2023 and spring 2024 semesters. Additionally, they will be nominated for a paid summer internship at Amazon in 2024, during which they will gain valuable industry insights and experiences via engagement with Amazon researchers.

AI2AI is seeking to advance the state of the art in all areas of interactive AI technologies that will enhance interactions between humans and intelligent machines. The initial research foci of the initiative includes, but is not limited to, the following research areas:

  • Computer Vision:
    Visual representations for a wide variety of video and image understanding tasks, such as activity/action recognition, scene understanding, body pose estimation, etc., especially those capable of supporting few-shot learning.
  • Speech and Language:
    Paralinguistic information from speech; speech recognition in highly challenging environments; dialectal, code-mixed, and multilingual language understanding; robust language understanding for evolving vocabularies, entities, topics, and domains; knowledge extraction, representation and injection into speech recognition and language understanding systems; reasoning on knowledge graphs; machine translation and massively multilingual processing; etc.
  • Green AI:
    Efficient learning via innovation in training and inference algorithms, in models (e.g., sparse models, retrieval augmented architectures), via knowledge distillation and hardware acceleration, and learning with limited resources (e.g. with less data or on edge devices).
  • Multimodal AI:
    Interactive, multi-turn, multi-modal retrieval with text and image inputs, learning from cross-modal context in multimodal settings.
  • NEW Security:
    Automatically identify malicious vs. benign activity in Linux cloud-based environments (using IP/domain reputation, attack chain alert fusion, command line executions, obfuscation detection, etc.) Computer Vision and Video Indexing techniques for physical security and identification of malicious activity.
  • NEW Responsible AI Approaches for Data:
    Automatically assessing accuracy of human-labeled data; redacting sensitive, private or objectionable content from data; generating realistic synthetic data for model training; quantifying and mitigating bias in training data to attain equitable model performance; and estimating the complexity of a human-labeling task for allocating quality-control resources.

Applicants must be enrolled full time and in good standing in a WSE PhD program or PhD program in a WSE affiliated department, be in their third year or higher in AY 2023-2024, and have exhibited outstanding academic performance. Exceptionally outstanding students in their second year in AY 2023-2024 also are eligible. Applications from those working in AI who are women and/or identify as members of underrepresented groups are particularly encouraged.

All applicants should submit the following materials by April 20 for full consideration:

  1. A resume listing their educational history, awards/honors, refereed publications, and a link to their web page describing scholarly accomplishments and/or other relevant considerations;
  2. A personal statement describing their research interests and plan (two pages maximum).

Applicants also must provide the names of 1) a WSE faculty member and 2) an additional mentor/supervisor (may be from industry), who will send detailed letters of recommendations in support of their applications directly to AI2AI.

All documents should be submitted in PDF format through the AI2AI submission portal.

The application period for 2023 has closed.