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Undergraduate Programs

Xerox Engineering Research Fellows

2018 Research Opportunities

Electrical and Computer Engineering


Professor Cristiano Tapparello
Department of Electrical and Computer Engineering
cristiano.tapparello@rochester.edu

Research Project Descriptions

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.


Professor Mark Bocko
Department of Electrical and Computer Engineering
mark.bocko@rochester.edu

Research Project Descriptions

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.


Professor Zhiyao Duan
Department of Electrical and Computer Engineering
zhiyao.duan@rochester.edu

Research Project Descriptions

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.


Professor Marvin Doyley
Department of Electrical and Computer Engineering
m.doyley@rochester.edu

Research Project Description

Research Project #1: Using Medical Imaging to Improve Pancreatic Cancer Therapies

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.


Professor Stephen Wu
Department of Electrical and Computer Engineering
stephen.wu@rochester.edu

Research Project Descriptions

Research Project #1: Developing new transistors from 2D materials

To continue the rapidly advancing pace of electronics technology, researchers are now looking beyond conventional silicon transistors. Recently with the discovery of graphene (Nobel Prize 2010), and several of its analogous 2D cousins, a new path to create faster, cheaper, and more functional electronics has been opened. We will be focusing on exploring new 2D materials, and interfacing them with multifunctional oxide materials to create new devices that will populate the new electronics landscape in the coming years. Students will work in multiple settings, learning both microfabrication techniques in the cleanroom, as well as electrical device characterization techniques in our low-noise measurement lab. Primary guidance will be provided by Prof. Stephen Wu. 

Research Project #2: Developing new topological electronics from quantum materials

A remarkable number of new topologically non-trivial quantum electronic materials have been identified recently. These materials offer new types of functionality and controllability that go well beyond what conventional electronics can do. Exploiting these new degrees of freedom can lead to significant advancements for the electronics industry as Moore's law comes to a close.  In our lab we will be focusing on exploring the spin transport properties of these materials to generate topological spintronic devices.  Students will work in multiple settings, learning both microfabrication techniques in the cleanroom, as well as materials growth and characterization in our materials synthesis lab. Primary guidance will be provided by Prof. Stephen Wu.


Professor Gaurav Sharma
Department of Electrical and Computer Engineering
gaurav.sharma@rochester.edu

Research Project Descriptions

Research Project #1: Assessing Disease Progression and Treatment Efficacy for Parkinson's and Huntington's Diseases Using Data Analytics on Body Worn Sensors

Parkinson's and Huntington's diseases are characterized by debilitating motion irregularities: such as tremors, unsteady gain, involuntary movements, and lack of coordination. This project seeks to use analytics on data captures from minimally obtrusive sensors worn at multiple points on the body for detecting and classifying motion irregularities, for quantifying the duration of such symptoms, and for characterizing the efficacy of medication in mitigating these symptoms.

Research Project #2: The Full-Spectrum Mobile Experience: UR Color Barcodes

UR researchers have recently invented a color version of the seemingly ubiquitous mobile barcodes that allow us to layer three independent pieces of information within each barcode by using the "spectral diversity" afforded by color printing and capture. In this project, we are looking to develop an easy to use mobile application and to test how the capability for layering can be advantageously used for student activity flyers and other events around campus.

Research Project #3: Adaptive Color Visualization for Color Deficient Observers on Android Smartphones

Around 7-10% of the male population in North America has some form of color deficiency.  These viewers often find it difficult to tell the difference between certain colors that appear clearly different to observers with normal color vision. The color deficiency is particularly problematic when it causes a loss of discriminability of different objects or when a color deficient individual must engage in a conversation involving standard color terminology designed for color normal viewers. As increasingly popular personalized imaging devices, smart phones can be used as tools to help color-deficient users overcome their deficiency. As a participant in this research you will help develop and deploy techniques for improved color visualization on Android smartphones by specifically exploiting the adaptivity and personalization that these devices offer.

Research Project #4: Noncoding RNA Gene Search: Unlock the hidden information in Genomes

With the widespread availability of high throughput sequencing technology, vast datasets of genomes are now available to researchers for exploration. Conventional protein coding genes can be located within these large genome data sets with relative ease using BLAST and other alignment tools. Noncoding RNAs (ncRNAs) that serve a direct functional role instead of providing a recipe for protein synthesis, however, present a challenge for genomic analysis. Across species ncRNAs are conserved in secondary structure rather than in sequence and they are therefore not discovered by common sequence alignment based search tools. With the discovery of an increasing number of ncRNAs it is clear that they represent the next frontier in advancing our understanding of the genomes. As a participant in this research, you will develop and evaluate new computational methods for identifying ncRNAs. 

Research Project #5: Principled Machine Learning Methods for Multiple Sequence Alignment

The alignment of sequence data is a fundamental task in analyzing genomic data, which shares several commonalities with string comparison. For aligning two sequences, hidden Markov models have emerged as the model of choice for aligning two sequences. For more than two sequences, several heuristics have been proposed that operate on sequences in a pair wise fashion. In this project, we seek an alternate more principled framework for multiple sequence alignment using principled machine learning methods. As a participant in this research, you will be involved in developing, implementing, and evaluating new techniques for multiple sequence alignment.


Professor Roman Sobolewski
Department of Electrical and Computer Engineering
roman.sobolewski@rochester.edu

Research Project Descriptions

Research Project #1:Terahertz Photonics (TWO students)

The field of THz science and technology is still in its infancy, but has already gained a very large international interest due to its numerous applications ranging from ultrahigh speed communication systems to medical imaging and diagnostics, industrial quality control, and security screening. In conventional terms, we can talk about the “THz gap,” i.e., a region of the electromagnetic radiation spectrum where it is very difficult to successfully operate either “classical” electronic or photonic devices. For even the fastest FET-type transistor structures, the THz frequency of operation is extremely high, while for optics the THz radiation wavelength is far too long, since the energy of THz quanta is much smaller than the thermal energy at room temperature.

There is an opening for summer research for TWO students. They will be involved in the state-of-the-art research aimed towards generation, propagation, and, subsequent, time-resolved detection of sub-picosecond (THz-bandwidth) electrical transients. Our THz spectroscopy system has an operational frequency bandwidth extending 3.5 THz and is very well suited for ultrafast, noninvasive characterization of various novel electronic materials and nanodevices. As an example, there are our studies of nonequilibrium carrier dynamics in isolated graphene nano-flakes, imbedded in a polymer medium and forming a nanocomposite. We are especially interested in students with interest in optics and electromagnetism, and with a working knowledge of MATLAB.

Research Project #2: Intrinsic Nanodevices (ONE student)

Intrinsic nanostructures exhibit unique physical properties that are a direct consequence of their nano-scale parameters and the quantum mode of operation, in contrast to scaled down versions of well-known conventional devices. One of the best-known examples is a nonlinear, asymmetric nano-channel diode (ANCD), also called self-switching diode (SSD), invented in 2004 by Song et al. Unlike conventional, e.g., p-n diodes, the ANCD performance is not based on a vertical structure and the junction barrier, instead, it produces diode-like characteristics through nonlinear carrier transport in depletion-controlled nano-channel. The ANCD planar geometry allows for a flexible design and easy integration as multi-element sensors. Indeed, ANCDs have been demonstrated to be viable THz detectors and, based on Monte Carlo simulations, are expected to be efficient THz generators.

There is an opening for summer research for ONE student. She or he will be involved in the state-of-the-art research aimed towards testing and, subsequent, analysis and numerical simulation of operation of ANCDs. Our laser-based photoresponse system has a sub-picosecond time resolution; thus, it is ideally suited for ultrafast, noninvasive characterization of various novel electronic materials and nanodevices. As an example, there are our integrated, “experiment-on-chip” studies of nonequilibrium carrier transport in semiconductor structures, as well as ANCDs photoresponse in a single-optical–photon limit. We are especially interested in students with interest in nanoscience and with a working knowledge of MATLAB.


Professor Yuhao Zhu
Department of Computer Science and Department of Electrical and Computer Engineering
yzhu@rochester.edu

Research Project Descriptions

Research Project #1: Storage Optimization for Virtual Reality Videos

Virtual Reality will have profound social impact and enhance human abilities in transformative ways. For instance, VR offers the potential to solve the opioid epidemic as VR experience is shown to reduce patient pain more effectively than traditional medical treatments. However, today's VR experience is far from desirable because today's computer systems are fundamentally lagging behind the unprecedented computation requirement VR technologies entail. As a first step toward improving the VR experience, this project will focus on using machine learning techniques to optimize the delivery of 360-degree VR videos from the VR service providers (e.g., Youtube, Facebook) to end-user devices (e.g., Google Carboard and Samsung Gear VR). We will examine both algorithmic limitations as well as operating/storage system-level inefficiencies.

Research Project 2: Image Signal Processor Design for Stereo Camera Systems

Image Signal Processor (ISP) is at the heart of any modern camera. It converts raw camera sensor data to RGB frames that can then be processed by various computer and robotics vision algorithms. This project focuses on the ISP design for stereo camera systems that use multiple camera sensors to obtain depth information from the scene (e.g., Microsoft Xbox Kinetic and Intel RealSense). We will focus on understanding the computation inefficiencies in today's stereo camera ISPs, and design better image signal processing algorithms and hardware systems.