The JHU + Amazon Initiative for Interactive Artificial Intelligence (AI2AI) solicits research proposals from faculty for advancing the state of the art in all aspects of interactive AI.
Topics of particular interest in Academic Year 2022-2023 are listed below.
- 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.
Compelling proposals on other topics that address interactive AI are also welcome.
Eligibility: Full-time tenure-track and research-track faculty members with a primary appointment in the Whiting School of Engineering are eligible to submit proposals as principal investigators. Collaborative proposals led by WSE faculty with faculty from other JHU divisions are also welcome.
Note: Faculty who will be Amazon Scholars in AY 2022-2023 are eligible to submit proposals, but must adhere to JHU Conflict of Interest policies and procedures.. These individuals are encouraged to consult with Laura Evans at [email protected] well in advance of proposal submission.
Preproposals and Information Session: Prospective proposers are strongly encouraged to submit a preproposal (abstract) of no more than 1 page by (COB) June 7th, so that Amazon scientists with matching interests may be identified. The “AI2AI Kick-off Meeting and Information Session” is scheduled for June 15th, wherein a set of presentations to describe the kinds of research AI2AI wishes to support will be made. The presentations will be followed by breakout sessions with small groups of faculty considering a proposal submission and Amazon scientists from teams that wish to engage with them and receive feedback.
It is hoped that this exchange will serve as a matchmaking exercise, enabling the development of well-focused proposals that are aligned with the interests of the PI and Amazon.