Alexius Lyle Wadell
Carnegie Mellon University
AR/VR Battery Research - 2023
The program is open to students in any year of their PhD study. We also encourage people of diverse backgrounds and experiences to apply, especially those from traditionally under-represented minority groups. Applications are evaluated based on the strength of the student’s research statement, publication record, and recommendation letters.
Winners of the Fellowship are entitled to receive two years of paid tuition and fees, a $42,000 annual stipend to cover living costs, various opportunities to engage with Meta researchers, and an invitation to the annual Fellowship Summit.
Having funded over 200 students from around the world since the Fellowship program's conception, we are proud to continue supporting exceptional PhD scholars in a variety of technology research domains. With the addition of close mentorship, the Meta Research PhD program aims to engage with our Fellowship winners, learn alongside them, and discover emerging opportunities in industry together.
Meta does not claim any right to work performed during or as a result of the Fellowship. All research conducted by the Fellow belongs to the Fellow. This excludes any work completed as a Meta employee, should the Fellow do an internship or consult during their Fellowship.
Applications Are Currently CLosed
Applications for the 2023 Fellowship cohort are now closed.
The program is open to students at all accredited universities around the world.
We will not be offering awards to candidates whose research is outside the specified research areas described in the Available Fellowships section. Please review each Available Fellowship description carefully to ensure you are aligned with the correct research area.
We are currently unable to provide funding for undergrads, graduates in different disciplines, or alternative funding such as small grants.
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Tuition money will be paid directly to the school. The total stipend of $42,000 will be paid to Fellow via direct deposit, unless otherwise specified. Stipends must be paid directly to Fellows. Stipend payment(s) are sent once a tuition invoice is received for the respective fall term each year.
The award funds are delivered during the fall term of the awarded year(s) and conclude at the end of the Spring term. If a Fellow graduates in the middle of the academic year, they will receive their full tuition for the semester, and half of their stipend amount (in alignment with the semester).
Transferring universities during the Fellowship should generally not pose an issue with payment.
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PhD students are welcome to apply for the Meta Research PhD Fellowship if their PhD is funded through other means. If an applicant is selected as a winner, we will review potential conflicts of interest and determine which funding they would have eligibility for (tuition vs. stipend, etc).
However, if a winner has accepted another offer, fellowship, or other multi-year award fund from a competing company or industry organization, they must disclose that information so we can determine if they are eligible to receive a Meta Research PhD Fellowship.
As part of the program, current Fellows are invited to Meta's headquarters in Menlo Park for the annual Fellowship Summit. At the Summit, Fellows can engage with other winners, share their current research, speak with Meta researchers and teams, and learn more about research at Meta.
Click on each of the Available Fellowships from the current application cycle (2023) below to learn more about each research team's focus.
We welcome applications from students doing research and developing high-performance software and hardware technologies for AI at datacenter scale. We are particularly interested in work at the intersection of algorithms (including model compression & numerical optimization), benchmarking (including perf models, profiling and debugging tools for accelerators & cluster architectures) as well as distributed systems (including distributed inference and training). Special attention will be given to development of software stacks and frameworks addressing software and hardware co-design of quantized distributed inference and low precision distributed training.
sw/hw co-design, high performance computing (hpc), gpu, accelerators, numerics, compression, quantization, sparsity, optimization, networking, storage, deep learning (dl), recommendation/personalization models, natural language processing (nlp), computer vision (cv)
We would like to support students who are advancing research in statistics and modeling. Areas of research include but are not limited to theoretic and practical models for bias and variance estimation and correction in models and datasets, uncertainty quantification, graph and structure representation learning, accurate and efficient labeled data collection, network science, active learning, multi-armed bandits, regression and classification, clustering and segmentation, entity linkage and data privacy. Applications of interest include but are not limited to user modeling; detecting, measuring and fighting abuse and violations; experimentation; surveys; monetization.
statistics, active learning, measurement, graphs, networks, reinforcement learning, deep learning, noise, bias, taxonomy, clustering, modeling, privacy, experimentation, entity deduplication, representation learning, sampling, survey, label, accuracy, bayesian modeling, bandit, uncertainty
We are interested in students working on novel battery geometries and cell architectures such as flexible and stretchable batteries. We are also interested in supporting diagnostic methods for analyzing battery degradation such as plating, internal shorts, and for detecting manufacturing defects. Manufacturing-related topics for consumer electronics batteries, like pre-lithiation methods for silicon anodes, are relevant. Battery management systems, including but not limited to protection, gauging, charging for small capacity batteries, are also areas of interest. Other areas of interest include algorithms to improve battery performance and minimize battery degradation and fundamental work on understanding limits of Li-metal batteries, solid-state batteries, and silicon anodes. Proposals for topics not listed here, but pertaining to batteries and battery technologies with a focus on consumer electronics, are also welcome.
battery, lithium ion, fast charge, consumer electronics, lithium plating, swelling, flexible,
We would like to support students who are working on advancing the state-of-the-art in computer graphics and efficient real-time rendering for augmented and virtual reality. Topics of interest include but are not limited to ray tracing and ray casting hardware, neural rendering, neural-based 3D asset, split/distributed rendering, image and video compression, geometry processing and compression, differentiable/inverse rendering, perceptual rendering, high quality avatars, global illumination, scene prefiltering, and rendering complexity reduction.
graphics hardware design, ray tracing, ray casting, neural rendering, neural 3d asset, split rendering, compression, streaming, differentiable rendering
The metaverse is the next evolution of social connection. 2D and 3D spaces in the metaverse will let you socialize, learn, collaborate and play in ways that go beyond what we can imagine today. Bringing the metaverse to life requires careful consideration of known and unknown questions regarding privacy and integrity as well as how to create an inclusive and equitable metaverse for users and bystanders alike. To that end, we would like to support students whose research sits at the intersection of future technologies (augmented reality, virtual reality, video presence, etc.) who are working on projects that demonstrate how we can keep people safe online or how these technologies can be used/designed inclusively and in a way that’s accessible. Successful applicants can come from a variety of disciplinary backgrounds, but we’re especially interested in seeing applications from those with backgrounds in the social sciences, HCI, communication, or public health.
metaverse, social science, communication, wellbeing, integrity, safety, privacy, collaboration, inclusivity, diversity, qualitative research methods, quantitative research methods, mixed methods research
We would like to support PhD students in the area of Human-Computer Interaction (HCI) who have established research programs in intelligent user interfaces, adaptive interfaces, ubiquitous computing, sensing, haptics, input and interaction design. Of particular interest (but not exclusively) are students who have applied their research towards solving challenging HCI problems in the domain of AR/VR. Through this fellowship, we are hoping to support and grow diverse talent amongst top HCI PhD candidates.
adaptive interfaces, intelligent user interfaces, ubiquitous computing, input devices, sensing, haptics, gesture, human centered ai, human-ai interfaces, human understanding, and interaction design, tangible computing, multi-touch
We would like to support students who are working on advancing the state-of-the-art in human understanding for AR/VR. Topics of interest include, but are not limited to, tracking and modeling humans and objects, action and gesture recognition, non-rigid fusion and reconstruction (e.g. NeRF), image synthesis (e.g. GAN), segmentation, differentiable rendering, novel text input techniques, novel sensors / sensor fusion (e.g. EMG, accelerometer, ...) and efficient ML techniques to run these methods on AR/VR devices.
tracking and modelling humans and objects, action and gesture recognition, non-rigid fusion, reconstruction (e.g. nerf), image synthesis (e.g. gan), segmentation, differentiable rendering, novel text input techniques, novel sensors / sensor fusion, emg, accelerometer, efficient ml techniques, ar/vr devices
We aim to connect with innovative students who can work from the fundamental principles of optical physics, computational optimization, and material science to achieve major breakthroughs. This includes the fields of source development, nano-optics, optical system design, novel optical materials and processes, diffractive optics, metasurfaces, and machine learning algorithm development.
optical physics, computational optimization, source development, nano-optics, optical system design, novel optical materials
We would like to support students working in innovative Antenna, RF and Wireless Communication technologies for the future AR/VR. Topics of interest include but are not limited to Transparent Antennas, Small antennas, Millimeter-wave Antennas, metamaterials and metasurfaces, Millimeter-Wave Integrated Circuits and Systems, RF Coexistence, Wireless Energy, Wireless Sensing, MIMO, 5G and Beyond, Wireless Architecture, Wireless Standards and Policy. Students who are self-motivated with strong research and publication records are recommended to apply.
transparent antennas, small antennas, millimeter-wave antennas, metamaterials and metasurfaces, millimeter-wave integrated circuits and systems, rf coexistence, wireless energy, wireless sensing, mimo, 5g and beyond, wireless architecture, wireless standards and policy
We would like to support students who are working on technologies related to sound capture and rendering systems, including virtual audio, with applications towards next-generation communications systems. Areas of research include but are not limited to microphone array processing, speech enhancement and noise reduction, spatial audio, including signal encoding, compression and decoding, acoustic propagation simulation, HRTF personalization and equalization, and auditory perception. In addition, we are interested in research related to perceptual evaluation and optimization, and user experience research. Our goal is to enable natural communication and interaction with realistic acoustic perception in virtual contexts.
microphone array processing, speech enhancement and noise reduction, spatial audio, including signal encoding, compression and decoding, acoustic propagation simulation, HRTF personalization and equalization, auditory perception
We would like to support students working in speech and audio processing for human-human communication in challenging situations. Topics of interest include but are not limited to perception of sounds by humans, speech enhancement, auditory scene analysis, acoustic event detection, audio-visual modeling and sentiment analysis.
speech enhancement, speaker separation, noise reduction, microphone array, auditory scene analysis, acoustic scene analysis, acoustic event detection, audio-visual modeling and sentiment analysis, hearing impairment, auditory modeling, audiology
We would like to support students who are advancing research in the social sciences with computational approaches. Topics of interest include models and analysis of online communities and interactions, information diffusion, algorithmic amplification, social capital, social vulnerability, migration, social issues beliefs and attitudes, civic participation, equity in online spaces, economic opportunity and mobility, and social science in the metaverse. A student’s research may study online platforms and technologies directly, or it may leverage novel datasets and methods to study the topics of interest. A focus on populations outside of Western markets or with underserved/marginalized groups is encouraged.
computational social science, data science, social network analysis, information diffusion, social capital, social vulnerability, migration, civic engagement, equity, economic opportunity, economic mobility, algorithmic amplification
We welcome applications from students working on novel approaches to data systems architecture and usage, including, but not limited to, improving the efficiency and reliability of large scale data processing systems, improving the interaction between database software and the underlying hardware, exploring novel techniques around query processing and data indexing, formatting, partitioning, and movement, transaction processing, replication, as well as novel approaches to privacy and security in data management.
data management, databases, big data, query processing, data indexing, transaction processing
We welcome applications from students working on a broad set of topics related to all kinds of distributed systems, including but not limited to fault tolerance, reliability, overload protection, system and container management, scale, performance, efficiency, and security.
distributed systems, scale, reliability, overload protection, system management
We support students who are passionate about applied or theoretical work in the areas of game theory, optimization, operations management and econometrics. Example research topics of particular relevance include ad auction design, two-sided mechanism design, mechanism design for social good, applications of combinatorial and convex optimization at large scale, and the intersection of econometrics and machine learning. We also encourage and welcome applications from researchers doing work on other topics in the disciplines above broadly relevant to economic and resource-allocation problems in the context of digital technologies.
economics & computation, algorithmic game theory, econometrics, mechanism design, market design, causal inference
We would like to support PhD students in the area of Human-Computer Interaction (HCI), social computing, social sciences or related fields who have established research programs in understanding the impact of social media on people and society, focused on key social or informational outcomes. Topics of interest include but are not limited to well-being, fairness and equity, civic engagement, and health. Methods may cover qualitative (e.g., ethnographic, interview, etc.) or quantitative (e.g., survey, experiments, computational, etc.) approaches. A focus on populations outside of Western markets or with vulnerable/marginalized groups is encouraged.
misinformation, polarization, equity, health, climate change, politics, crisis, hate speech, violence, well-being
We would like to support students active in the research and development of scalable, performant, reliable, efficient and secure wired network infrastructure across AI/Machine Learning applications, data centers, the wide area (IP and optical), and Internet peering. The networking technologies span the entire networking stack (L1-L7); range from chip/interface/system hardware design to distributed systems for control, data, and management planes; and cover the whole network lifecycle, from planning/design/analytics, to provisioning/deployment/migration, to monitoring/troubleshooting/visualization. This also includes applications of related disciplines such as machine learning, optimization and algorithmic theory, and formal verification to the networking domain.
ai infrastructure, host networking, software defined networking, kernel bypass, RDMA, traffic engineering, network management, networking hardware, Internet
We would like to support students who are working to understand people's digital privacy experiences across social media and messaging (e.g., privacy concerns, privacy needs, privacy feature use). The ultimate impact of these research topics should be aimed at improving people's privacy experiences through improved data practices, transparency, privacy education, and/or privacy controls (e.g., shaping privacy feature designs across open and encrypted networks as well as advertising products). Please note that students who are studying technical privacy solutions (e.g., differential privacy) should apply to the Security and Privacy fellowship vs. this one.
data practices, privacy concerns, privacy needs, privacy features, privacy education, privacy design, privacy transparency, privacy controls, privacy settings, privacy user experience, end-to-end encryption user experiences, privacy-forward advertising
Applications are welcome from students who are interested in the design and implementation of programming languages and related tools. Topics of interest include, but are not limited to: program synthesis, type systems, static analysis, optimizing compilation, runtimes, formal specification and verification, and high-level support for features such as concurrency, data privacy, control of side effects, and probabilistic and differentiable programming.
programming languages, compilers and run-times, type systems, static analysis, dynamic analysis, testing and verification
We would like to support students with established proficiency in the field and passion about maximizing utility while addressing consumer needs via privacy-enhancing technologies. Topics of interest include but are not limited to: privacy-preserving analytics, private record linkage and aggregation, privacy-preserving machine learning, privacy of messaging, and anonymous credentials. Students may showcase research proposals that leverage an assortment of technologies such as federated learning, federated analytics, differential privacy, trusted execution enclaves, multi-party computation, homomorphic encryption, and more.
dp for anonymization, dp for database management systems, re-identification measurement, asymmetric mpc, multi-key record linkage, complex aggregations in mpc, ppml - model capacity, ppml - trust models, dp in ppml, ppml - mixed training datasets
We want to support students who think critically about the policies that shape the long-term impact of technology on society. We encourage applications from candidates who investigate how governments, technology developers, and the academy can contribute to the development of technologies in the interest of democracy and the open internet. Possible topics could include, but are not limited to, data privacy, the economics of information, the role of standard-setting bodies, and so on. This is an interdisciplinary field, and we welcome applications primarily from the social sciences, STS, history, and the humanities.
technology policy; democracy; international organizations; privacy; information economy; standards-setting bodies; amplification; philosophy of technology; user psychology; polarization
Human Computer Interaction - Social Media, People, and Society - 2023
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross Girshick
Mikel Artetxe, Holger Schwenk
Elissa M. Redmiles, Jessica Bodford, Lindsay Blackwell