Apple is committed to supporting the academic research community and its invaluable contributions to the world. We offer fellowships, scholarships, and awards to graduate and postgraduate students who are harnessing the power of technology to help people and the planet.
Meet the Apple Scholars.
Ethics and Technology
Postdoctoral fellowships
Apple University, in a joint program with Stanford University’s McCoy Family Center for Ethics in Society, hosts postdoctoral fellows whose research focuses on issues at the intersection of ethics and technology.
Abby Jaques
Ethics and Politics of Technology
Stanford University
Stanford University
Abby is focused on the big questions at the intersection of human and artificial intelligence: What does it take to get tech right? And how do we make sure the technologies we build are good for everyone?
At MIT, Abby developed a new theory of the nature of intentional action. Now she is focused on how artificial intelligence can affect human behavior and its potential moral and political impacts. She has also developed a new, practice-based method of ethics for engineers, and she contributed to a series of grant-funded efforts aimed at democratizing AI through formal and informal education.
Hardware Technologies, Integrated Circuit Engineering, Artificial Intelligence, and Machine Learning
PhD fellowships
Awarded to emerging leaders pursuing research in areas related to electrical engineering, computer engineering, and computer science with a focus on cutting-edge technology and Apple core values.
McKenzie van der Hagen
Hardware Support for Encrypted Computing
Carnegie Mellon University
Carnegie Mellon University
McKenzie is working on novel computer architectures that would allow low-power IoT devices to participate in encrypted computing at the edge.
An enormous amount of data is collected and processed at every moment through Internet of Things (IoT) devices. It takes a lot of power to protect the privacy of everyone using connected technology. One way to address privacy in the world of IoT is through homomorphic encryption techniques, which enable computation directly on encrypted data. But that takes complex mathematics and huge data structures. McKenzie’s work aims to develop specialized computer architectures to support these massive operations within the modest constraints of low-power IoT devices. Ultimately she hopes to take the concept of encrypted computing from optimistic theory to practical reality through hardware support.
Jaya Narain
AI for Health and Wellness
Massachusetts Institute of Technology
Massachusetts Institute of Technology
Jaya is using personalized machine learning and naturalistic data to help children with nonverbal autism spectrum disorder (ASD) communicate with the world around them.
Of the 3.5 million people in the United States who have ASD, about 30 percent are nonverbal. But that doesn’t mean they don’t communicate. Parents and caregivers can often interpret vocalizations, gestures, and differences in tone that may be missed by others. Jaya is using the knowledge that primary caregivers have to train machine learning models to help interpret nonverbal cues. She hopes that her research can have a profound impact on how children with nonverbal autism navigate their space and communicate with new people.
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Ishwarya Ananthabhotla
Speech and Natural Language
Massachusetts Institute of Technology -
Yahav Bechavod
Privacy Preserving Machine Learning
Hebrew University of Jerusalem -
Graham Gobieski
On Device Machine Learning
Carnegie Mellon University -
Mitchell Gordon
Human-Centered Machine Learning
Stanford University -
Jeong Joon Park
Augmented Reality and Computer Vision
University of Washington -
Nathan Serafin
Hardware for Efficient Computing
Carnegie Mellon University -
Yang Song
Fundamentals of Machine Learning
Stanford University -
Xinyi Wang
Speech and Natural Language
Carnegie Mellon University -
Yifan Wang
Augmented Reality and Computer Vision
ETH Zurich -
Bingzhe Wu
Privacy Preserving Machine Learning
Peking University -
Yiren “Aaron” Zhao
On Device Machine Learning
University of Cambridge -
Tijana Zrnic
Fundamentals of Machine Learning
University of California, Berkeley
Hardware Technologies and Integrated Circuit Engineering
Masters scholarships
Awarded to outstanding students completing their masters degrees in advanced hardware technologies and specializing in computer architecture, system on chip design, verification, and validation.
Anna Li
Electrical and Computer Engineering
Carnegie Mellon University
Carnegie Mellon University
Anna began her academic journey at Carnegie Mellon doing what all of her peers were doing: pursuing software. However, she soon found herself far more invested in the hardware beneath.
Anna’s interest shifted from software to hardware during her first hardware course, Structure and Design of Digital Systems. She found that even though hardware description was entirely different from programming, she was still able to use her strengths: logic, problem-solving, and developing algorithms. Now she is doing what she feels she was meant to do — working at the intersection of hardware and software.
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Tarana Laroia
Electrical and Computer Engineering
Carnegie Mellon University -
Ryan Oh
Electrical and Computer Engineering
Carnegie Mellon University -
Deanyone Su
Electrical and Computer Engineering
Carnegie Mellon University
Stay tuned.
There’s more to come.
The Apple Scholars program is currently invitation-only. Check back to find out more as the program expands. And to learn more about students who believe in the power of technology, share our values, and are passionate about making the world a better place.