Microsoft recognizes the value of diversity in computing. The Microsoft Research Dissertation Grant aims to increase the pipeline of diverse talent receiving advanced degrees in computing-related fields by providing a research funding opportunity for doctoral students from groups underrepresented in computing (women, African-Americans/Blacks, Latinos, American Indians/Alaskan Natives, Native Hawaiians/Pacific Islanders, and/or people with disabilities).
Provisions of the award
- The 2018 Microsoft Research Dissertation Grant recipients will receive funding up to 25,000 USD for academic year 2018–19 to help them complete research as part of their doctoral thesis work.
- Microsoft will arrange and pay for travel and accommodations to grant recipients to attend a two-day Microsoft Research workshop in Redmond, Washington, in the autumn of 2018.
- The workshop will provide grant recipients an opportunity to present their research, meet individually with Microsoft researchers in their research area and receive career coaching from Microsoft researchers.
- PhD students must be enrolled at a university in the United States or Canada and doing dissertation work that relates to computing topics in which Microsoft Research has expertise (click on Research Areas at the top of the page for a full list).
- PhD students must be in their fourth year or beyond in a PhD program when they apply for this grant. The student must continue to be enrolled at the university in the autumn of 2018. Funding is for use only during their time in the PhD program; it cannot be used for support in a role past graduation, such as a postdoc or faculty position. The applicant will need to confirm their PhD program starting month and year, as well as their expected graduation month and year.
- Payment of the grant, as described above, will be made directly to the grant recipient’s university and dispersed according to the university’s policies.
- Applicants must attest that they self-identify with at least one group underrepresented in computing. This includes: women, African-American/Black, Latino, American Indian/Alaskan Native, Native Hawaiian/Pacific Islander, and/or people with disabilities.
How to apply
The 2018 Microsoft Research Dissertation Grant application period closes on Friday, March 30, 2018, at 11:59 PM Pacific Time.
- PhD students must apply directly for the grant.
- Applications must include:
- Curriculum vitae
- Thesis topic description (maximum two pages including references, font no smaller than 10-point)
- Description of how the grant would be used, including a budget (maximum one page)
- Month and year you entered the PhD Program and your expected graduation date
- Self-identification of your gender, race/ethnicity, and disability status
- Primary area of research (click on Research Areas at the top of the page for a full list)
- Contact information for three references who are established researchers familiar with your research (at least one of which must be from your primary academic advisor/supervisor and only one letter can be from a current Microsoft employee). Microsoft will automatically provide instructions and request a reference letter from each of your three reference contacts separately as you submit your application. Those auto-generated emails will be sent from Microsoft CMT “email@example.com”, which may end up in your spam folder. References will be asked to attach a letter to your application in our tool. Note that all three contacts must submit your reference letters by Monday, April 16, 2018, at 11:59 PM Pacific Time in order for your application to be considered. Due to the number of applications, we will not respond to questions asking if your references were submitted in time. You will receive an auto-generated confirmation each time one of your references submits a letter.
- Three to six names and email addresses of Microsoft researchers, chosen for topical relevance, who you would agree to be paired with as a mentor. A list of researchers and research areas can be found on our people webpage. Do not contact the researchers for the purpose of listing them as a potential mentor. Do not list researchers with a Corporate Vice President or Managing Director title.
- Funding can be requested to support items such as equipment, data, travel, tuition, and staff salary needed for research; the request is not limited to these examples.
- Applications must be submitted via the online application tool in any of the following formats: Word document, text-only file, or PDF. Email or hard-copy applications will not be considered.
- Applications submitted to Microsoft will not be returned. Microsoft cannot assume responsibility for the confidentiality of information in submitted applications. Therefore, applications should not contain information that is confidential, restricted, or sensitive.
- Incomplete applications will not be considered.
- Due to the volume of submissions, Microsoft Research cannot provide individual feedback on applications that do not receive grants.
Get answers to frequently asked questions about the Microsoft Research Dissertation Grant.
Yes, if you are an international student attending a school in the United States or Canada and meet the eligibility requirements.
This program includes only schools in the United States and Canada. If you are a student attending a school outside the United States and Canada, you are not eligible for this grant.
Students must still be enrolled in their PhD program during the autumn of 2018 in order to receive and use the grant. Grants are for completing dissertation research only, and cannot be used for support in a role past graduation, such as a postdoc or faculty position.
Students must be in their fourth year or beyond in a PhD program when they apply for this grant. Students must have started their PhD in September 2014 or earlier to be considered to be in their fourth year of the program for this year’s application process.
Grant review process
Reviewers will rate applications based on the technical/scientific quality and the potential impact of the proposed research.
Applications will be reviewed by researchers from Microsoft Research with appropriate topical expertise. The three to six Microsoft researchers who the applicant referenced as people they would agree to be paired with as a mentor could be among those asked to review that applicant’s submission.
Selected grant applicants will receive notification no later than Friday, June 30, 2018. Due to the volume of submissions, Microsoft Research cannot provide individual feedback on applications that do not receive research grants.
Grant award details
Persons awarded a Microsoft Research Dissertation Grant in June will receive their financial award in July or August of that year. Microsoft sends the payment directly to the university, which then disperses funds according to its guidelines.
No. This award will be provided as an unrestricted gift with no terms and restrictions applied to it. No portion of these funds should be applied to overhead or other indirect costs.
The tax implications for the research grant are based on the policy at the university.
The Microsoft Research Dissertation Grant is not subject to any intellectual property (IP) restrictions.
If you accept a Microsoft Research Dissertation Grant, you may receive another fellowship from another company or institution during the same academic period. However, if your tuition and/or stipend are being covered by a fellowship award, then you should not request tuition/stipend funds from the grant as part of your budget.
Johns Hopkins University
Dissertation Title: Nanoengineering for Tunable Energy-Efficient Optoelectronics
Colloidal nanomaterials, such as semiconductor quantum dots, are of interest for various optoelectronic applications due to their size-tunable optical properties, distinctive electronic structure, and low-cost fabrication. Color-tuned and semi-transparent photovoltaics, devices with controlled and tunable reflection and transmission spectra, are of significant interest due to their potential applications in building-integrated photovoltaics, vehicular heat and power management, and multijunction photovoltaics. High-performance computing technologies coupled with advanced optimization methods have made it possible to rapidly and efficiently design and predict new device structures without having to rely on costly, time- and resource-intensive “trial-and-error” lab-based experiments in the field of optoelectronics. My project focuses on using nanoengineering techniques, including multi-objective optimization algorithms, plasmonic nanoparticle enhancements, and hybrid-materials-based surface modifications, to design and build colloidal quantum dot-based devices with controlled optical and electrical properties for the next generation of inexpensive and ubiquitous light harvesting, detection, and emission technologies.
Juan Camilo Gamboa Higuera
Dissertation Title: Transfer of Robot Motor Behaviors from Low-Fidelity Domains
I’ve been working on algorithms for synthesizing controllers for a six-legged underwater autonomous vehicle, to perform a variety of navigation and pose control tasks. These algorithms allow us to specify data collection tasks, e.g. coral reef monitoring, from high level objectives encoded as numerical cost functions. To reduce the amount of data needed for each task, and since models of underwater dynamics are computationally expensive, we use model-based reinforcement learning techniques where the models are data-driven. A problem with these approaches is that, even if they are data efficient, collecting new data is expensive. I’m investigating techniques that mitigate this cost by re-using prior knowledge, from simulation or similar environments. Our current approach, which we call policy adjustments, allows us to transfer previously learned controllers by reasoning about the discrepancies between the source of the knowledge (a simulator) and the deployment environment (a physical robot in the ocean).
Dissertation Title: Efficient, Privacy-Preserving, Secure Cloud Computation and Storage
Adopting cloud services to reduce operational, maintenance and storage costs, is becoming increasingly common. However, outsourcing data and computations, is opening up new challenges in terms of integrity and privacy of the data and the computations on them. Along with such important security and privacy concerns, availability, and scalability are major factors in such settings. My thesis addresses various problems in this space of secure storage and computation outsourcing. In summary, the main contributions of my thesis are the following.
- Designing models and protocols for outsourced queries on structured dynamic data with efficiency, integrity and privacy guarantees along with prototype implementations.
- Designing efficient (general) verifiable computation primitives for data-intense applications along with prototype implementations.
- Developing an expressive framework for efficient graph queries on encrypted networks along with prototype implementations.
- Designing efficient protocols to facilitate secure storage of encrypted data in the cloud while enabling deduplication.
University of Maryland, Baltimore County
Dissertation Title: Smart Algorithms via Knowledge Management of Safe Physical Human-Robotic Care
The beginning of a new era in safe assistive robotics will occur when people with disabilities and seniors let intelligent software control a mobile robotic manipulator to safely reposition their body and limbs. Our goal is to explore the intersection between providing physical care and robotics, and how it is possible to translate safe patient handling and mobility guidelines into smart human-robotic interaction (HRI) algorithms. For a mobile manipulator with knowledge-managed algorithms. we propose to create an accessible low fidelity 3D Web interface for manipulating a high degree-of-freedom robot to safely reposition the human body and limbs. Our efforts seek to standardize protocols and regulations for how artificial intelligence agents related to physical HRI can achieve body and limb repositioning tasks. As assistive robotics become more mainstream, these best practices can improve safety in direct physical care in the process of repositioning the human body with a mobile robotic arm.
Dissertation Title: Interpretable Machine Learning for Human Decision Making
My research primarily focuses on exploring how machine learning can help improve real world decision making in domains such as health care and criminal justice. To this end, my thesis addresses various challenges involved in developing and evaluating interpretable machine learning frameworks which can complement and provide insights into human decision making. More specifically, my thesis focuses on the following diverse yet related research directions: developing frameworks which can be used to compare the effectiveness of algorithmic and human decision making, building models for obtaining interpretable and diagnostic insights into the patterns of mistakes made by human decision makers, learning accurate and interpretable models (or approximations to existing machine learning models) which can complement human decision making. The main contribution of my thesis is to address these problems under realistic assumptions which hold in real world decision making such as presence of unmeasured confounders and limited availability of labeled data.
Indiana University, Bloomington
Dissertation Title: Examining the Implementation of the Health Information System in Mozambique: Understanding the Experiences of Health Care Workers with ICTs
My study examines the implementation of the health information system (HIS) in Mozambique and the roletechnologies play in educating health professionals for better delivery of care. Through a comprehensive examination of the HIS, from development to roll-out, I analyze the relationship between colonial and (post)colonial governmental top-down policies and compare them to the on-the-ground reality of using information and communications technology (ICTs) to provide health education given social, economic, and political realities in Mozambique. Part of the problem with studies of technologies in poor parts of the world is that they are often conducted by highly educated researchers and are conducted in English. However, majority of the population in poor nations does not speak English. Such studies become irrelevant to the life experiences of those being studied. I will disseminate findings from this study in Portuguese and English through talks and publications in U.S., Mozambique, and other international venues.
Martez Edward Mott
University of Washington
Dissertation Title: Accessible Touch Input for People with Motor Impairments
Touch-enabled devices such as smartphones, tablets, and interactive kiosks are some of the most pervasive technologies in the world today. As a result, touch has emerged as one of the most dominant forms of input for computing devices. Despite the overwhelming popularity of touch input, it presents significant accessibility challenges for millions of people with motor impairing conditions such as cerebral palsy, muscular dystrophy, and Parkinson’s disease. My dissertation research takes an ability-based design approach toward improving the accessibility of touch-enabled devices for people with motor impairments. I intend to create intelligent interaction techniques that allow people with motor impairments to touch in whichever ways are most comfortable and natural for them, and for the system to react as if it was touched precisely.
Shadi A. Noghabi
University of Illinois at Urbana-Champaign
Dissertation Title: Building Large-scale Production Systems for Latency-sensitive Applications
In this era of increased engagement with technology, many latency-sensitive applications processing large amounts of data have emerged. For example, we expect social networks to show hashtag trends within minutes, data from IoT to be processed within seconds, and online gaming to react within milliseconds. In all these diverse areas, handling large scale data in a real-time fashion is crucial. At scale, providing low latency becomes increasingly challenging with many complexities in distribution, scaling, fault-tolerance, and load-balancing. My research has focused on developing techniques that broadly explore these issues with particular attention to end-to-end latency and building massive-scale solutions. Most of my work is deployed in large-scale production systems with hundreds of millions of users. My research contributions span a wide range of frameworks including: Ambry (LinkedIn’s mainstream geo-distributed media store), Apache Samza (a stream processing engine used by LinkedIn, Uber, TripAdvisor, etc.), and Freeflow (a high-performance container networking solution).
John R. Porter
University of Washington
Dissertation Title: Understanding and Improving Real-World Video Game Accessibility
My dissertation work attends to the intersection of accessible human-computer interaction and video game design. Games continually grow more complex, pervasive, and significant in 21st century life. However, due to inaccessibility, games are often actively disabling experiences for many gamers with impairments, systematically excluding them from full participation in an increasingly important activity. Therefore, my work proposes to understand the play experiences of gamers with impairments and offer novel design solutions for mitigating the accessibility barriers they face. My proposed investigations seek to understand how accessibility barriers manifest in mainstream games, to empower gamers with impairments to better navigate the landscape of game accessibility through novel information design, and to address underlying institutional concerns that perpetuate systemic accessibility issues in the game development industry through education interventions.
Andrew S. Stamps
Mississippi State University
Dissertation Title: Applications of Heterodox Rendering Methods to Visualization
Information visualization is an illustrative method to depict data, and the structure of this data is not necessarily known beforehand. The classic rendering via rasterization of visualization primitives tends to minimize extraneous details; every drawn pixel or glyph has a tight correspondence to the data on which it is based. A simple line chart for example. It is thought that a more expressive or artistic rendering of data might harness additional insight through abstraction, or even an emotional connection. These expressive methods which I have classified as Heterodox Visualization (HV) methods, include non-photorealistic rendering (NPR), stylized rendering processes like pixelization, and other rendering approaches, like those that mimic natural media e.g. painting or sketching. To date there has been little systematic guidance covering how these HV methods could be applied to information visualization. My research will help determine, through experiment, which techniques pose a benefit to different types of visualizations.
Vasuki Narasimha Swamy
University of California, Berkeley
Dissertation Title: Real-time Ultra-reliable Wireless Communication
My research focuses on designing wireless communication protocols for Internet-of-Things (IoT) applications that require low-latency and high-reliability. This can enable exciting new interactive and immersive applications such as exoskeletons, inter-vehicle communication for self-driving cars, robotics & factory automation, virtual & augmented reality, high-performance gaming, and the smart grid. I am developing wireless communication protocols that employ simultaneous relaying by all radios in the network. This allows us to overcome bad channels and guarantee the latency requirements. My early work dealt with understanding the fundamental limits of using cooperative communication for high-performance applications. Currently, I am exploring the key physical layer requirements that are needed to implement these protocols. I am modeling how synchronization and channel estimation impacts the performance of these protocols. Ultimately, understanding the fundamental limits of high-reliability and low-latency wireless will enable us to engineer exciting applications.
University of California, Berkeley
Dissertation Title: Hybrid Aesthetics – A New Media Framework for the Computational Design of Creative Materials, Tools, and Practices within Digital Fabrication
Technology plays an important role in both constraining and guiding how users explore, express, and innovate in a variety of creative tasks. Practices are emerging which blend both physical and computational techniques and materials providing new opportunities to expand the aesthetic repertoire available to creative practitioners. This thesis contributes a framework for understanding how to create these hybrid elements and develop materials, tools, and practices that stimulate the imagination to explore a wider gamut of creative expressions. Through a series of design tools, the thesis introduces data structures that break constrictive digital modes of practice, conceptual framings for guiding aesthetic exploration, and design principles for the adoption, sharing, and teaching of hybrid techniques. This work serves as a bridge between art and technology and challenges the narrative of who can participate and use digital fabrication technologies to include traditional artists, designers, and the broader community of creative practitioners.
Give your dissertation a boost with a grant from Microsoft Research
Dissertation Grant Winners Announced
New Dissertation Grant provides support to under-represented groups in computing
Fellowships offer graduate students the opportunity to apply their talents at research centers, universities, and nonprofit organizations worldwide. Students refine their skills as they work to address issues of regional, national, and international importance.
Each year, a limited number of fellowships are awarded to graduate students in an effort to help the university achieve a more diverse graduate student body. A variety of factors may be used for the purpose of increasing diversity at the university, including gender, race, ethnicity, national origin, sexual orientation, disability, or other protected classifications consistent with the university’s nondiscrimination policy. These awards provide tuition support, and are recommended by the student’s academic department or college. There is no work requirement associated with the fellowship.
Fulbright is the largest U.S. exchange program offering opportunities for students and young professionals to undertake international graduate study, advanced research, university teaching, and primary and secondary school teaching worldwide. The Fulbright U.S. Student Program offers two types of grants for graduate students: the research/study grant and the English Teaching Assistantship (ETA).
Dissertation Completion Fellowships
The Graduate Dissertation Completion Fellowship provides doctoral candidates close to completing their dissertation with the financial support needed to spend their final semester writing. The award provides a one-semester stipend that is half of the current academic year stipend rate. In addition, both the student’s one-credit registration fee and health fees will be covered by the award for the semester. The award must be used during the semester for which it is awarded and may not be deferred. For more information on the Dissertation Completion Fellowship, visit Northeastern’s Research site.
Graduate Thesis/Dissertation Research Grant
The Thesis/Dissertation Research Grant is designed to help full-time graduate students meet the costs associated with completing their thesis or dissertation research, to improve the quality and impact of their research, and/or to support research endeavors intellectually independent of the advisor. Allowed expenses include, but are not limited to:
- Travel to special library or museum collections, archives, laboratories, or other research facilities
- Access to libraries, databases, or other information sources not otherwise available
- Hiring consultants or special services
- Remuneration of research subjects or supporting undergraduate research assistants
- The purchase of specialized reagents, supplies, software, or equipment not otherwise available (which will remain the property of the university)
Proposals to fund specialized training will be eligible for consideration only if such training is clearly necessary for the applicant’s thesis or dissertation research.
For more information, visit Northeastern’s research site. You can also contact Ginny Leung, fellowships and grants assistant for the Office of the Provost, by email at firstname.lastname@example.org or by phone at 617.373.6904.