The 2016-17 Microsoft Research Women’s Fellowship provided funding to a select list of academic universities that have awarded a US$20,000 fellowship to a woman who is interested in pursuing a PhD and in need of financial assistance. Of that amount, $18,000 was applied toward tuition costs and $2,000 covered travel expenses to a conference in the fellowship recipient’s field of study.
In addition, Microsoft Research created opportunities for each fellowship recipient to engage with Microsoft researchers in their domain of study and connect with each other in a collaborative community.
Provisions of the 2016 – 17 fellowship
- Each participating university selected a fellowship recipient who is interested in or currently pursuing a PhD at that institution, in financial need, and has high potential for engaging in research in the field of computing
- The fellowship was awarded to recipients for one academic year only and is not available for extension or renewal.
- The fellowship recipient had to remain an active, full-time student who is enrolled in PhD-level studies at one of the participating universities during the academic year of the award, or forfeit the fellowship.
Get answers to frequently asked questions about the Microsoft Research Women’s Fellowship program.
What happened to the Graduate Women’s Scholarship program?
Originally, the Microsoft Research Graduate Women’s Scholarship program was created to help women in their first years of their PhD study to cover financial costs and enable them to determine their research area. Over the course of the scholarship program, Microsoft Research granted financial awards to 70 women pursuing a PhD, which has helped to fund their education and increase visibility within their academic domain.
For the academic year 2016–2017, the program evolved into the Microsoft Research Women’s Fellowship.
Who was eligible to apply for the Women’s Fellowship?
The Microsoft Research Women’s Fellowship was eligible to students entering or enrolled in a PhD program at one of the participating universities for the 2016–2017 academic year.
Was an internship at Microsoft Research part of the program?
Internships are not included as part of the award. You may have the opportunity to apply for an internship if you desire but you are not required to do an internship.
What were the tax implications for this scholarship?
The tax implications for the award were subject to the policy at each university.
Will intellectual property be an issue if awarded the scholarship?
The Microsoft Research Women’s Fellowship program was not subject to any intellectual property (IP) restrictions.
Were simultaneous scholarships from other companies allowed?
Yes. Awardees were allowed to receive a scholarship from another company or institution for the same academic period.
Graduate Women’s Scholarship Recipients
The Microsoft Research Graduate Women’s Scholarship program was created to help women in their first years of their PhD study to cover financial costs and enable them to determine their research area. Microsoft Research recognizes these outstanding graduate students, who represent a selection of the best and the brightest in their fields.
Beginning with the academic year 2016–2017, the program evolved into the Microsoft Research Women’s Fellowship.
2016 Women Fellows
University of Texas at Austin
Long-term research goal: I work at the intersection of distributed computing, distributed systems, and databases. Specifically, I am interested in the theory and implementation of storage systems that must support applications that 1) operate at scale 2) span multiple regions 3) require near-constant availability.
University of California-Berkeley
Long-term research goal: My research goal is to integrate our understanding of our own human intelligence with our efforts to create artificially intelligent machines. How do we learn so robustly despite incomplete and noisy data? How do our vision and language systems differ relative to each other and relative to our more general cognitive abilities? By developing computational models of these human cognitive capacities, we may identify new methods of engineering intelligence, and, conversely, by exploring existing and novel models of these capacities, we may develop insights into understanding our own intelligence.
University of Washington
Long-term research goal: My current research is focused on automating performance analysis of Big Data analytics systems. Previously I have worked on caching and load balancing in large-scale distributed systems and experimentally evaluating algorithmic models for wireless networks. My research to date manifests in a broad question into what principles can help us identify and tackle pressing challenges in the complex computer systems that drive scientific discovery and online services that impact the daily lives and culture of billions.
Jeevana Priya Inala
Massachusetts Institute of Technology
Long-term research goal: I want to make programming better by automatically synthesizing the code that satisfies the user specifications.
Long-term research goal: As methods to learn patterns in data become more complex, they become harder to interpret. Deep learning represents the latest in this trend; it gives breakthrough results on image classification, machine translation and speech recognition, but these are areas where black box models are acceptable because the ultimate goal is to make high-quality predictions. However, in areas such as biology and medicine, a black-box predictor is often insufficient as the real value lies not with the prediction, but in the science behind the prediction. For example, if a model is trained to predict whether a certain protein binds to a given DNA sequence, the ultimate goal may be to discover the recurring patterns in the DNA that the protein has an affinity to. Therefore, the goal of my research is to develop techniques to make deep learning models interpretable, so that they can be used not just for prediction, but for insight and discovery.
Long-term research goal: In my research, I want to work on improving machine understanding of language use. In particular, I am interested in researching semantics and pragmatics. The information shared between two people taking part in a conversation not only depends on the individual words used and how they are combined, but the context, the participants’ individual knowledge about the world, why a particular word or phrase was chosen when another expresses the same logical meaning, etc. Could systems be developed which are able to extract the same depth of information that humans share in conversation?
Lucia Marisol Villacres Falconi
Georgia Institute of Technology
Long-term research goal: Marisol is a future PhD student at the Human-Centered Computing program at Georgia Tech. She is currently an Associate Professor in the Computer Science Program at the Escuela Superior Politécnica del Litoral (ESPOL), in Ecuador. She holds a a BSc in Computer Engineer from ESPOL and a Masters in Human-Computer Interaction Design from Indiana University Bloomington.
As a Computer Engineer born and raised in a developing country, she is drawn to explore the design of technologies that empower individuals and groups otherwise marginalized. Her research interests include critical design, information and communication technologies for development, emotional aspects of human-computer interaction, and educational technology.
Carnegie Mellon University
Long-term research goal: Ellen Vitercik is a computer science PhD student at Carnegie Mellon University, where she is advised by Nina Balcan and Tuomas Sandholm. She is interested broadly in theoretical computer science and artificial intelligence. Her research is focused on problems in the intersection of computational learning theory and mechanism design. Before joining CMU, she completed her undergraduate degree at Columbia University.
Long-term research goal: My research interests lie in using machine learning and human computer interaction techniques to interactively generate sonifications that use sound to represent data in the world around us. I am working on developing techniques that allow end users, who may not have any experience with sound or sonification design, to create their own sonifications and explore the sonic design space. In my spare time I enjoy being outside with my husband and two dogs, from hiking and rock climbing to working in the garden.
Rui (Shirley) Yang
University of Illinois at Urbana-Champaign
Long-term research goal: My current research topic is about the distributed algorithm optimization in camera sensor network and I would like to work on the optimization in distributed systems and in cloud environments after attending University of Illinois at Urbana-Champaign.
I participated in research group in my sophomore year, when the rigor and innovation of research appeal me a lot. During the efforts for my first published paper, I gradually master the basic methods of scientific research and make clear my interests with many creative ideas. I will continue to do my best in the future and wish to foster collaborations with researchers at Microsoft.
2015 Graduate Women Scholars
Computer Science—Carnegie Mellon University
Research area interest: programming languages, information security, logic
Long-term research goal: The focus of my research is to develop formalisms and tools that will provide strong security guarantees for information. My work lies at the intersection of programming languages and security because I believe that language and logic-based formalisms aid in the precise reasoning that is necessary to provide complex security guarantees.
Receiving this fellowship gives me the tools and ability to pursue my interests in programming languages and information security unhindered. Further, the conference stipend enables me to attend more programming languages and security conferences and help me better bridge ideas from these two communities to do interdisciplinary research.
Computer Science—Stanford University
Research area interest: computer graphics, human-computer interaction
Long-term research goal: My research interests lie primarily in the intersection of computer graphics and human-computer interaction. On the side, I am passionate about dance, photography, and design, and love that I can incorporate these interests into my research through work in areas ranging from animation to interaction design.
I have a diverse range of cross-discipline interests. Having a scholarship means I will have more freedom to branch out and explore projects of larger scope.
Electrical and Computer Engineering—University of Illinois, at Urbana Champaign
Research area interest: speech and natural language processing; algorithms, theory and cryptography; human-computer interaction, etc.
Long-term research goal: My research is focused on probabilistic graphic models which provide a unifying framework to model our beliefs about the world. I am interested in efficient learning of the inherent parameters and make inferences with the model, in the context of natural language processing applications.
I have had the privilege of working with Microsoft Research during my undergraduate studies. I am passionate about my academic studies and this fellowship will serve to encourage this commitment.
Material Science and Mechanical Engineering—Harvard University
Research area interest: hardware devices
Long-term research goal: My research explores the intersection of design and manufacturing in robotics. The goal of my research is to use novel manufacturing methods to make robotic solutions less expensive and more accessible. I hope to lower barriers to mass fabrication of customizable robots by exploring the use of soft structures as well as flat composites and origami-inspired construction.
The support of the Microsoft Research Graduate Women Scholarship gives me the opportunity to pursue my interest in novel manufacturing methods for electromechanical systems for which I am very grateful.
Statistics—University of California, Berkeley
Research area interest: nonparametric statistics, causal inference
Long-term research goal: I am interested in developing statistical methodology to be used in observational studies that aim to improve social and health outcomes. Traditional methods typically involve simple parametric models and small sample sizes, but recent developments in technology, computing power, and data collection have highlighted the need for more sophisticated methods. My research focuses on applying robust nonparametric statistics and machine learning to causal inference problems. The goal is to make reliable inferences while making minimal assumptions about the models generating the data.
Part of my job as a statistician is to make new methods available to practicing researchers in other fields. The Microsoft Scholarship will enable me to engage with people outside my own department from whom I can learn more about software development and data science. By doing so, I will be able to write programs to make novel methodology accessible to those who will apply it to real-world problems. I hope that my useful contributions to Statistics and my recognition as a Microsoft Graduate Women’s Scholar will encourage other females to study quantitative sciences.
Computational Systems Biology—University of California, Los Angeles
Research area interest: algorithms, computational biology, machine learning
Long-term research goal: I want to develop computational methods to solve problems in biology and medicine, and currently work on efficient algorithms for genomic analysis. Technological advances have given us enormous volumes of genomic data and other biological data, with more to come. Many challenges exist in extracting useful information from this wealth of data, providing great opportunity to advance medical knowledge through computer science.
This scholarship will support me at a crucial stage in my early career and allow me to focus on research. The conference and travel support will also help facilitate innovative, interdisciplinary, and collaborative work.
Linguistics—University of Washington
Research area interest: hybrid (machine learning + rule-based) approaches in computational linguistics
Long-term research goal: I want to develop algorithms which can extract information about languages’ grammars from poorly structured data. This will help create quality language tools, such as grammar checkers and machine translation systems, for low-resource languages and contribute to cultural conservation efforts
The scholarship will allow me to invest time in my research goals early. Reading more papers, attending more talks and developing and pursuing small research questions is necessary background for a successful dissertation, so I greatly appreciate the opportunity to spend more time on these things as early as my second year in the program. It also means a lot to me that I first got the idea to study computational linguistics because I worked at Microsoft NLG as a contractor, and now Microsoft is supporting me in this further.
Computer Science—Georgia Institute of Technology
Research area interest:programming languages—program analysis and repair, learning systems
Long-term research goal: Software systems touch almost every aspect of the human experience, and are becoming increasingly large and complex as they tackle ever-more challenging problems. Defects in such software can cause widespread damage and can be costly to fix. It is thus important to develop software analysis techniques and tools to improve software quality. My long-term research objective is to develop techniques for program analysis and repair that scale to large and complex programs by learning from previous data in innovative ways.
What this scholarship means to me: This scholarship award has highly motivated and encouraged me. It enables me to give my undivided attention to the research problems I am passionate about. It will help me foster collaborations with researchers at Microsoft who are working on closely related problems in this important area.
Electrical Engineering—Yale University
Research area interest: artificial intelligence, cognitive science, human-robot interaction
Long-term research goal: Outsourcing computation and data to remote computing and networking equipment raises the concern of potential sensitive data leakage. Currently, many software schemes are put forward to protect sensitive data, but they introduce considerable overhead or the software—only protections may be bypassed. My research aims to leverage hardware to create hardware—software architectures that provide increased security, resistance to variety of hardware and software attacks, all while remaining efficient.
Microsoft’s Graduate Women’s scholarship is of great help to pay for the tuition and stipend, so I can be more concentrated on my research. Thanks to the support for conference travel, I can present my work at renowned conferences, meet with other researchers, and catch up on the latest developments in the field.
Computer Science—Cornell University
Research area interest: artificial intelligence, natural language processing
Long-term research goal: I aim to synthesize natural language processing and unsupervised machine learning technologies to create accessible tools for those outside computer science. My hope is that these will allow digital humanities researchers and curious individuals alike to investigate language corpora. I specifically wish to focus on better inference models for “poorly behaved” language, such as old English text or modern dialogue on social media.
Thanks to this scholarship, I can work to obtain more comprehensive human evaluation information for the design of new metrics to evaluate language models. I can also work on large-scale parallelization of difficult language inference tasks. Finally, I hope this scholarship will help connect me to the immensely talented NLP researchers at Microsoft Research.
2014 Graduate Women Scholars
Electrical and Computer Engineering—University of British Columbia, Vancouver
Research area interest: surgical robotics
Long-term research goal: The focus of my research will be concentrated on augmenting the sensory perception of a surgeon performing telesurgery with robotic surgical systems. Incorporating haptic feedback or enhanced visual perception will provide information useful for surgical guidance, allowing the surgeon to complete the operation more knowledgably, with greater efficiency, and with fewer complications. My goal is to make surgical tools more effective to offer greater benefit to patients.
Robot Manipulation—Carnegie Mellon University
Research area interest: robotics, manipulation, machine learning
Long-term research goal: The goal of my research is to enable robots to effectively use their environment as a whole to accomplish complex manipulation tasks. I aim to expand a robotic manipulator’s dexterity allowing robots to interact with objects in new and useful ways.
Systems, Architectures, Mobility, and Networking—University of Pennsylvania
Research area interest: I am interested in utilizing hardware mechanisms to address current computer system vulnerabilities in a multi-core processor environment.
Long-term research goal: I would like to demonstrate how computer hardware designs can provide an environment that is both secure for the user, as well as efficient in both chip area and execution time.
Statistics and Data Science—University of Notre Dame
Research area interest: statistical disclosure limitation, missing data sets, clinical trial design and analysis
Long-term research goal: As the era of information and technology continues to dominate, big data offers tremendous benefits for education, medical research, national security, and other areas through data-driven decision making, discovery and process optimization. However, one of the crucial concerns is the extreme risk of exposing personal information of individuals who contribute to the data when sharing it among collaborators or releasing it publically. My solution involves statistical disclosure limitation (SDL), or methods of data privacy and confidentiality. This will preserve participant privacy without altering the integrity of the original data by creating multiple, synthetic data from predicted values using Bayesian Statistics.
Machine Learning, Adaptation, and Intelligence—University of Michigan
Research area interest: embodied cognition, robotics, cognitive architecture
Long-term research goal: The goal of my research is to equip robots with the cognitive skills they need to handle real-world environments in an intelligent, human-like fashion. It is fascinating that, despite years of AI research, robots are consistently confounded when confronted with the complexities of the real world. I am interested in leveraging the reasoning powers of a cognitive architecture to improve the way an embodied agent interacts with its environment.
Large-scale distributed computing—Columbia University
Research area interest: optimization, parallel computing, cloud computing, and machine learning
Long-term research goal: I am very interested in conducting fundamental research on interdisciplinary problems at the intersection of Mathematics, Computer Science, and Electrical Engineering. On the application side, my current focus is on communication systems, energy networks, and large-scale dynamical systems. I primarily work on the computational aspects of these systems, such as resource allocation using distributed algorithms, compressed sensing, and optimal decentralized controller design. This research has a strong engineering component and as a solid mathematical element that relies on algebraic graph theory, nonlinear optimization, and control theory, among others.
Human Centered Design and Engineering—University of Washington
Research area interest: human-computer interaction, visualization
Long-term research goal: My research is focused on human-computer interaction. I am interested in building visual analytics tools to help people better understand data. In addition, I am passionate on developing technologies to support collaboration. My long-term goal is to bridge the gaps between disciplines so that people from different fields could easier work together to solve problems in the world.
Hardware Devices—Rice University
Research area interest: nanoelectronics and nanoscale device fabrication
Long-term research goal: My main research focus is to characterize, modify, and enhance the properties of two-dimensional nanostructures based on grapheme, in order to make them more suitable for applications in the field of electronics and solar cells. For this purpose, I propose to use atomic scale imaging techniques such as the scanning tunneling microscope. My work will provide insight into the physical and electronic structure of the grapheme based materials upon modification at a local scale with atomic precision.
Machine Learning, Adaptation, and Intelligence—Georgia Institute of Technology
Research area interest: artificial intelligence, cognitive science, human-robot interaction
Long-term research goal: In the endeavor to improve robots to a point where they can behave and think as humans do, it is increasingly important to discover how humans reason and acquire skills. I am exploring how advances in cognitive science can impact how we interact with robots to develop innovative, intelligent systems. In particular, I aspire to develop analogical reasoning in the robotics research field, thus expanding the effectiveness of learning from human-robot interactions.
Data Management and Data Mining—University of Massachusetts Amherst
Research area interest: big data analytics, database systems, distributed systems
Long-term research goal: I plan to continue working on big data analytics in distributed systems and in cloud environments. Motivated by the needs of low-latency analytics and scalability of cluster computing, I plan to focus on the development of new platforms and techniques that can scale analytics to large data sizes while at the same time being able to return new results and insights with low latency. I hope that such scalable, low-latency analytics will benefit many users ranging from traditional data-intensive applications to new data-driven scientific disciplines such as social science and genomics.
2013 Graduate Women Scholars
Computer Science—Stanford University
Research area interest: machine learning, data mining
Long-term research goal: I would like to aim my future research in the field of machine learning and its applications to a range of domains including language processing, information retrieval, and social networks.
Lilian de Greef
Computer Science and Engineering—University of Washington, Seattle
Research area interest: ubiquitous computing
Long-term research goal: I want to work at the intersection of multiple disciplines to develop technologies that beneficially impact people’s lives. For example, I am currently working with computer vision, HCI, machine learning, and medicine to use smartphones to detect dangerous levels of jaundice, or yellowing of the skin, in newborns.
Computer Science Department—University of Illinois, Urbana-Champaign
Research area interest: compute security; mobility and networking
Long-term research goal: My research aims to provide the general population with affordable and convenient access to the healthcare systems. I will focus on defining an open sensor system for mHealth in order to help users secure their medical data. This scholarship will help me focus on research that I hope will generate significant outcomes and impact the future of healthcare.
Mathematics—Carnegie Mellon University
Research area interest: algorithms, combinatorics, and optimization
Long-term research goal: I would like to continue working in areas relating to graph theory and algorithms, in particular, I would like to improve on current approximation algorithms for NP-Hard problems.
Electrical Engineering and Computer Science—Northwestern University
Research area interest: perceptually based image processing
Long-term research goal: I plan to work on image analysis techniques based on models of human perception. The human visual system is amazingly good at analyzing images and extracting useful information, and thus provides inspiration, feasibility clues, and performance goals. In particular, I am interested in developing statistical techniques for visual texture analysis and the extraction of material properties.
Support via the Graduate Women Scholarship will allow me to devote all my time to my research at what I expect to be a critical point in my graduate career. The scholarship support for attending academic conferences will also contribute to advancing my academic development by enabling me to learn about cutting-edge techniques in my field.
Computer Science and Engineering—University of Michigan, Ann Arbor
Research area interest: embedded systems, ubiquitous computing, security
Long-term research goal: I would like to explore the potential for embedded systems to enable major advancements in quality of life and environmental interactions. In particular, I see opportunities for impact in remote health and science in developing regions, responsive and energy-efficient buildings, and networks that are quick and cheap to deploy in areas with limited Internet connectivity. Additionally, as sensor-based applications become more and more integrated with our lives, I would like to investigate ways of providing useful sensor-based services while preserving privacy.
Computer Science—University of California, Santa Barbara
Research area interest: wireless networks, information and communication technologies for development (ICT4D)
Long-term research goal: I want to develop holistic connectivity solutions for under-resourced communities with limited connections to the Internet. My chief goal is to develop wireless networks that promote information contribution and production in addition to information consumption. In particular, I am interested in making last mile connections as effective as possible for knowledge sharing and educational purposes.
Computer Science Department—University of British Columbia
Research area interest: artificial intelligence, human computer interaction, machine learning
Long-term research goal: For a truly advanced artificial intelligence to interact with a human, it must be able to perceive information from the many implicit communication channels used in everyday conversation. I would like to make use of methods for reasoning in the face of uncertainty, as well as machine learning, to build an emotionally perceptive artificial intelligence that can interact in a manner similar to a human. I believe this could have many beneficial applications, from Intelligent Tutoring Systems, to assistive technologies, to helping individuals suffering from autism spectrum disorders.
Parisa Khanipour Roshan
Interactive Computing—Georgia Institute of Technology
Research area interest: online communities, social support, social change
Long-term research goal: I am interested in studying how we can use online tools to support disconnected individuals who are part of the same community, whether it is a pre-existing community, like the survivors of abuse, or an emerging one, such as social media spontaneous volunteers during a crisis.
Electrical Engineering and Computer Science—University of California, Berkeley
Research area interest: computer networks, machine learning
Long-term research goal: I am interested in Internet research. What excites me about this research area is that the Internet was developed in a rather ad-hoc manner, where people kept iterating over existing solutions as demands changed. Now, with ever-increasing traffic and evolving technologies, there is a tremendous scope of improvement and I would like to make a significant contribution to it.
2012 Graduate Women Scholars
Computer Science Department—Princeton University
Research area interest: human-computer interaction
Long-term research goal: I am particularly interested in interactive systems involving music and machine learning. I aim to develop systems that improve people’s lives in meaningful ways.
Information Science Department—Cornell University
Research area interest: human-computer interaction
Long-term research goal: I want to help people remember, find, understand, and create information via personalized and adaptive interfaces. My principle goal is to study how systems can be made more aware of a user’s attributes, task context, and social connections in order to generate and refine long-term semantic models about an individual’s abilities, interests, and intentions that can be applied to intelligent systems. I am particularly interested in applications in the domains of recommender systems and example-centric problem solving.
Mathematics Department—University of California, San Diego
Research area interest: algebraic dombinatorics
Long-term research goal: I would like to build bridges between algebra and combinatorics by making use of results in both fields to solve questions in areas of common interest, such as in the theory of symmetric functions.
Algorithms, Combinatorics, and Optimization (Mathematics)—Georgia Institute of Technology
Research area interest: theory and complexity applications in social choice/preference theory
Long-term research goal: I want to aim my research towards a field where I can do more computation work while simultaneously studying fascinating theoretical mathematical puzzles. I’d love to end up working in preference prediction and network theory.
Computer Science Department—University of Toronto
Research area interest: decision making under uncertainty, computational economics
Long-term research goal: My overall research goal is to develop models and algorithms that allow people and organizations to make optimal decisions with partial information (for example, uncertainty about the environment or incomplete preference information) in real-world settings. I am particularly interested in bringing together insights from economics, machine learning, and algorithm design to solve these types of problems.
Engineering Sciences and Applied Mathematics Department—Northwestern University
Research area interest: mathematical biology, climate modeling
Long-term research goal: I hope to apply analytical and computational methods to analyzing models concerning the Earth’s cryosphere, in particular, the effects of the varied reflectivity of the ice and water. In doing so, as well as in further research, I hope to shed light on the mathematical and physical properties of tipping points present in many complex systems.
Computer Science—University of California, Berkeley
Research area interest: human-computer interaction
Long-term research goal: I am hoping to explore 3-D printing and how it can be made more accessible and useful: for example, through the design of printable electronics and re-imagining of user interfaces for 3-D modeling. That manufacturing and design knowledge gain a new foothold among hobbyists and youth is critically important for keeping jobs in the country and encouraging personal learning and growth.
Biomedical Informatics Program—Stanford University
Research area interest: using machine learning and computational methods for neuroimaging analysis
Long-term research goal: I aspire to work on data-driven methods that combine multi-modal neuroimaging data to provide insight to the structure and function of the human brain. My long-term goal is to develop infrastructure to allow for semantic accessibility of imaging data, and tools that might be utilized to identify biomarkers of neurological disease.
Computer Science Department—University of North Carolina at Charlotte
Research area interest: educational video games, games for learning
Long-term research goal: I hope to develop polished and engaging video games that facilitate learning. I have a particular interest in developing games that teach programming and other creative problem solving skills to middle school students in order to increase interest in computer science among underrepresented groups with hopes of strengthening the computer science and STEM [science, technology, engineering, and mathematics] pipeline. I also want to see my current middle school programs expanded to the high school level via an AP Computer Science course that we are developing at UNC Charlotte. I think it would be cool to see my work/research being used in real classrooms, helping the teachers make learning fun.
Language Technologies Institute, School of Computer Science—Carnegie Mellon University
Research area interest: information retrieval
Long-term research goal: I would like contribute to a better search experience for users everywhere by developing better search techniques suited for different domains, such as microblogs, and exploring novel ways to present the results of a search.
2011 Graduate Women Scholars
Computer Science Department—Michigan State University
Research area interest: algorithms and networking
Long-term research goal: I would like to aim my future research towards discovering solutions to challenging problems that are important to society and about which I am passionate. I also see myself contributing to computer science education research, particularly with regards to new and better methods for integrating computer science into core curriculum for high school students.
Economics Department—Stanford Graduate School of Business, Stanford University
Research area interest: market design
Long-term research goal: I hope to use tools in stochastic process and operations research to develop models in efficient market design. In particular, I am interested in how theoretical models in microeconomics can be used to explain human behavior, help solve social welfare problems, improve political institutions, and design more efficient methods for raising government revenue.
Computer Science Department—Virginia Polytechnic Institute and State University
Research area interest: cyber security, network anomaly detection, and forensics
Long-term research goal: The goal of my research is to develop a novel security framework for networked computers that provides robust defense against malware attacks and is difficult for malware to circumvent. Specifically, my research will focus on modeling and characterization of human-user behaviors, developing protocols for fine-grained traffic-input analysis, and preventing forgeries and attacks by malware.
Computer Science Department—University of Toronto
Research area interest: artificial intelligence—knowledge representation and reasoning
Long-term research goal: My long-term objective is to pursue a career in research in the field of artificial intelligence, where my research can be applied to challenging real-world problems. I find artificial intelligence to be an exciting field because of its interdisciplinary nature. Application areas where I would like to have an impact include electronic commerce and medicine. I am especially inspired by collaboration between researchers in the field of artificial intelligence and the field of computational biology that aims to tackle problems that profoundly affect people’s lives.
Electrical Engineering and Computer Science—Massachusetts Institute of Technology
Research area interest: speech and natural language processing
Long-term research goal: I would like to dedicate my work to improving machines’ abilities in understanding humans. Making machines easier to communicate with and behave more like humans are my research goals.
Computer Science Department—University of Pittsburgh
Research area interest: computer/information security
Long-term research goal: I would like to pursue research in the IT field, and contribute to the development of communication security.
Computer Science Department—Carnegie Mellon University
Research area interest: game theory and logic
Long-term research goal: I hope to use techniques from logic and programming languages to develop general frameworks in which to describe and prove properties of games and mechanisms.
Electrical Engineering and Computer Science—University of California, Berkeley
Research area interest: computer networks
Long-term research goal: I have a broad interest in networking, specifically in inter-domain, wide area settings. I am particularly excited about Internet measurement, network architecture, and network security.
Computer Science and Engineering Department—University of Washington, Seattle
Research area interest: human-computer interaction; natural language processing
Long-term research goal: I am interested in studying how Human Computer Interaction techniques can improve Natural Language Processing applications. In the domain of machine translation, for example, NLP algorithms can be very effective at translating literal meanings, but struggle with interpreting cultural cues that are embedded in text. Feedback from end-user communities with appropriate domain knowledge can augment the results of machine translation in such situations. By exploring visualization techniques and support for active learning in NLP applications, I hope to find novel ways of enabling people to engage with information.
Department of Electrical Engineering and Computer Science—University of Michigan, Ann Arbor
Research area interest: wireless, embedded, and networked systems
Long-term research goal: At the University of Michigan, our team is working to create an ecosystem of phone-centric, square-inch footprint sensors that will be useful in both mobile health care and as reference designs for a broader community. We aim to demonstrate the possibility of parasitically powering external peripherals and transferring data to and from a mobile device, such as a Windows smartphone using only its audio headset port. This work will marry low-power sensing with the mobile phone’s computation, communications, and display technologies focused on transforming mobile phones into leading-edge data collection devices. We hope that our effort will make headway for the integration of other sensing peripherals for monitoring blood pressure, blood glucose, and body temperature with the mobile phone. It may be a small but important step towards enabling mobile healthcare technology for delivering accurate medical information anytime anywhere.
2010 Graduate Women Scholars
Adriana Lopez, New York University
Ailar Javadi, Georgia Institute of Technology
Ariel Levavi, University of California – San Diego
Arthi Ramachandran, Columbia University
Azalia Mirhoseini, Rice University
Betelhem Mateos Mekisso, Oklahoma State University
Eleanor O’Rourke, University of Washington – Seattle
Gabriela Marcu, Carnegie Mellon University
Jinyan Guan, University of Arizona
Olga Turanova, University of Chicago
2009 Graduate Women Scholars
Xide Lin, University of Illinois – Urbana-Champaign
Laura Grupp, University of California – San Diego
America Holloway, University of California – Irvine
Jing-Jing Liu, Massachusetts Institute of Technology
Jin Joo Lee, Georgia Institute of Technology
Dafna Shahaf, Carnegie Mellon University
Michaela Goetz, Cornell University
Tamara Denning, University of Washington
Meromit Singer, University of California – Berkeley
Katrina Panovich, Massachusetts Institute of Technology