Apple Scholars in AI/ML

THIS APPLICATION IS FOR CS STUDENTS ONLY.

The Apple Scholars in AI/ML PhD fellowship program recognizes the contributions of emerging leaders in computer science and engineering at the graduate and postgraduate level. The PhD fellowship in AI/ML was created as part of the Apple Scholars program to support the work of outstanding PhD students from around the world, who are pursuing cutting edge research in machine learning and artificial intelligence.

The monetary award will be directed to the nominating universities in the form of an unrestricted gift to fully support the nominee(s) selected, disbursed annually. Please confirm with your university development or corporate relations office that they are willing to accept this gift structure before nominating students.
• Gift amount covering full tuition and fees (enrollment fees, health insurance) for (2)
academic years
• $40,000 USD gift each year to help with living expenses and related expenses
• $5,000 USD gift each year to support research-related travel and associated
expenses

Scholars will also receive:
• 2 year mentorship with an Apple researcher
• Internship opportunities for one or both summers of their fellowship*
• Invitation to the PhD Scholars Summit in Cupertino, CA**

• Internship offers are dependent on student status, and contingent upon necessary requirements for
  employment being met according to relevant employment law.
  **Due to evolving travel restrictions related to COVID-19, the Summit will be postponed until it is safe for all
  Scholars to travel internationally

The fellowship focuses exclusively on the following research areas:

Privacy Preserving Machine Learning (Federated Learning, Differential Privacy, Cryptographic Tools, Secure Multiparty Computation)
On Device Machine Learning (Model Compression, Model Representation, Hardware/Software Integration, Model Personalization)
Human-Centered Machine Learning (Social Signal Processing, ML for Multimodal Interaction, ML Design and Human Factors, Usable ML Tools and Products, Interactive ML)
AI for Health and Wellness (ML and RL for Mobile Health, Time Series Representation Learning, Physiology- Informed Machine Learning, Modeling Multi-Modal Sensor Data)
AI for Accessibility (Accessible User Experiences, Automatic Personalization/Adaptation, interactions via New or Combined Modalities, Participatory Design with People with Disabilities)
AI Ethics and Fairness (Bias and Fairness in AI, Interpretable AI, Introspection)
Speech and Natural Language (Speech Recognition, Text to Speech, Conversational and Multi-Modal Interactions, Machine Translation)
Knowledge Graph Generation and Database Systems (Knowledge Extraction and Information Retrieval, Knowledge Inference, Large-Scale Graph Data Management, Machine Learning and Data Systems Integration)
AI for Autonomous Systems (Reinforcement Learning, Imitation Learning, Multi-Output Models, Imbalanced Data)
Augmented Reality and Computer Vision (3D semantic scene understanding, SLAM and Relocalization, Neural Network Architectures for 3D, Computational Photography and Videography, Visual Representative Learning, Active Sensing)
Fundamentals of Machine Learning (Deep Learning, Reinforcement Learning, Unsupervised & Self-Supervised Learning, Optimization, Interpretability)
AI and Manufacturing (Hardware Aware AutoML, Few-Shot Learning, Weakly-Supervised / Semi-Supervised Learning)

Eligibility:

Applicants must be full-time doctoral students pursuing research in one of the topical areas listed above.
Applicants must have either two or three years remaining in their graduate program. Students with less than two years, or more than three years, remaining in their graduate program are not eligible.
Students of any citizenship/nationality are eligible.
Note: A maximum of only two nominations from a given university may be for students who do NOT self-identify as a member of a group traditionally underrepresented in the field of computing (see paragraph below).
Applicants may NOT be supported at the time of application by another industry-sponsored full fellowship.
A university may submit up to five nominations. However, if more than two are submitted, then in order to increase opportunities for students who are underrepresented in the field of computing, additional nominees must self-identify as a woman, non-binary, Black/African American, American Indian/Alaskan Native, Hispanic/Latinx, Native Hawaiian/Pacific Islander, and/or person with a disability. In other words, if a university chooses to nominate more than two nominees, then the third, fourth, and fifth nominees must self-identify with one of the underrepresented groups mentioned above.
A campus review panel assembled by the Graduate College will select up to five finalists for consideration in the national competition.