Xerox Engineering Research Fellows
2018 Research Opportunities
Electrical and Computer Engineering
Research Project #1: MOTIVE—MANET Optimization Through Interaction, Visualization and Evaluation
Wireless ad hoc networks are infrastructure-less networks developed to meet the needs of a variety of applications where infrastructure-based wireless networks are difficult to deploy and maintain. Given the increasing availability of mobile devices that natively support ad hoc communication protocols, we explore different techniques for efficient resource management of large scale ad hoc networks. Our research includes developing techniques to:
- Create multihop ad hoc networks by interconnecting commercially available mobile devices,
- Acquire device and network information
- Utilize the acquired information to optimize the network operation, including network maintenance as well as task distribution within the multi-hop ad hoc network.
As an example, we have created a system to visualize pertinent network information, allowing network operators to quickly identify bottlenecks, locate lost or disconnected nodes, and re-assign network roles in response to a node current situation. By coupling this information with geographical information, displaying the nodes and connections on a map, operators can more easily trouble shoot errors that arise from environmental or network conditions.
Research Project #2: MEDAL—MEDical Application Language
Healthcare is rapidly evolving from reactive and hospital-centered to preventive, proactive, person-centered and focused on well-being rather than disease. To ease the evolution towards such a proactive and patient-centered healthcare system, we developed ManageMyCondition, a standard framework for rapid development and deployment of medical condition management applications on Android devices. Using ManageMyCondition, we have developed three mobile applications, which aim at helping parents manage their child’s asthma (ManageMyAsthma) and improving the compliance to prescribed medications in oncology patients (ManageMyMedications and ManageMyPatients). Our research now includes porting of these applications to iOS devices and the development of a novel programming language called MEDical Application Language (MEDAL), which enables healthcare professionals with no prior programming experience to rapidly develop and deploy custom medical condition management applications. By developing application templates and a Graphical User Interface (GUI), our goal is to create a mobile application development framework that will transform how medical applications are developed, making development of these applications accessible even to non-programming experts.
Note: Both of these projects are in collaboration with Professor and Dean Wendi Heinzelman, Edmund A. Hajim School of Engineering and Applied Sciences.
Research Project #1: Spatial audio display development and testing
We have developed methods to exercise spatial and temporal control of flat-panel loudspeakers employing arrays of force actuators mounted to the panel. This enables us to control the spatial properties of the sound radiated by the panel. We are looking for a student with strong computational and laboratory skills to join our group in working on this project. We are especially interested in a student with prior experience in programming FPGAs. Project 2 - Computational audio for virtual reality. We are developing multiple methods for rendering 3D sound for virtual reality applications, both headphone based methods and free-space rendering methods. There is an opening for a summer research student with interests in one of the following areas: computational modeling, audio perception and qualitative testing, or experimental acoustics.
Research Project #2: Computational audio for virtual reality
We are developing multiple methods for rendering 3D sound for virtual reality applications, both headphone based methods and free-space rendering methods. There is an opening for a summer research student with interests in one of the following areas: computational modeling, audio perception and qualitative testing, or experimental acoustics.
Research Project #1: Large-scale Sound Retrieval through Text and Vocal Imitation
This project builds up on our recent work on sound retrieval through vocal imitation, which allows users to search sounds in a small database using their vocal imitation as queries. In this project, we will bring this technique to a larger scale. Our idea is to combine text-based search with vocal imitation-based search and to design better interaction mechanisms. The student will be involved in the whole cycle of research and development, including data collection and cleaning, software development, experiments and result analysis. The student will work under the guidance of Professor Zhiyao Duan and one of his PhD students.
Research Project #2: Developing An Intelligent Music Editor
Imagine that you recorded a string quartet but found that the cello voice was too soft. You wanted to boost its volume without affecting the other parts. Existing audio editors such as Adobe Audition, however, only allow users to modify/process the entire audio mixture instead of the sound sources. Intelligent audio editors such as Melodyne are able to separate the music mixture into notes, but the separation quality varies much. In our lab, we have developed a technology to separate the music mixture into sound sources in a robust score-informed fashion. It uses the score information to accurately separate the music mixture into sound sources. The users can then modify different aspects (e.g., volume, pitch, timbre, timing) of individual sound sources without affecting the others. In this project, the student will develop an audio editor based on this technology. The student will work under the guidance of Professor Zhiyao Duan and one of his PhD students. Students with advanced programming skills/interface design are preferred.
Pancreatic cancer is the fourth leading cause of all cancer-related deaths in the United States, and it is projected to be the second leading cause by 2020. 94% of patients diagnosed with this disease die within 5 years. The disease is difficult to treat because high tissue pressure within tumors inhibits effective chemotherapy drug delivery. Currently, no technique can effectively measure tissue pressure noninvasively. In this project, we will develop image and signal processing techniques for measuring tissue pressure noninvasively using ultrasound and cutting-edge imaging modalities such as optical fluorescence tomography. We will also perform studies in animal models to see if these techniques can be used to improve treatments that are currently used for patients with this deadly disease. In addition to developing signal processing techniques, the students will learn how to model drug delivery within tumor models. The students will be part of a diverse team, which includes Ph.D. researchers and clinicians. Student applicants should have strong analytical and laboratory skills.