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--- projects [2011/09/06 00:12] – dymond
+++ projects [2015/08/26 21:56] – jarek
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-====== Currently offered Projects, Fall 2011 (updated September 3, 2011)  ======
+====== Proposed Projects for Fall 2015 ======
-(Listed in order received.)
+\\
+=====Clustering High-Dimensional Data Sets=====
-====== Building an autonomous motorboat ======
+**Supervisor: Suprakash Datta**
-**Supervisor**: Michael Jenkin
+Clustering is a basic technique for analyzing data sets. Clustering is the process of grouping data points in a way that points within a group are
+more similar to each other than points in other clusters. Many clustering algorithms have been developed over the years. However no single algorithm works well for all data sets. Further, most clustering algorithms have running times of the order of n^2 or n^3, so that they are not feasible for data sets with hundreds of thousands of points. In this project we will design good clustering algorithms for large real data sets. In particular we are interested in
+Biological data sets.
-**Required Background**: General CSE408x prerequisites
+Our data sets will include those obtained from Flow Cytometry data. Flow Cytometry is a common technique in many areas of Biology, particularly Immunology. Typical usage involves testing a blood sample for 25 attributes on a per-cell basis, and thus typical data sets are arrays of 500,000 points in a 25 dimensional space. The aim is to identify clusters that correspond to a biologist's notion of a cell "population". In addition to the size of the data, the factors that make this problem difficult are heterogeneity of population sizes and densities and overlapping populations. With the help of collaborators we proposed an accurate algorithm called SWIFT (Cytometry A. 2014 May;85(5):408-33) that successfully finds small cell populations of interest to Immunologists. This project attempts to design and implement algorithms that are faster than SWIFT but at least as accurate. The supervisor has collaborators in Immunology who are experts in interpreting and analyzing Flow Cytometry data. Their expertise will be used to design and validate effective clustering algorithms that can run on large data sets.
-**Recommended Background**: Robotics
+No Biology knowledge is required. The student should be a strong programmer. Knowledge of C/C++ is desirable but not essential. The work involves reading and understanding existing algorithms and working with the supervisor to design and implement improved algorithms and to measure the performance of the proposed algorithm(s).
-__Description__
+For more information, please send email to datta@cse.yorku.ca.
-An opportunity exists for a small number of students to build an autonomous motorboat using a RC motorboat as a base and integrating computation and control in the form of a Beagleboard. Students will participate in lectures and labs associated with CSE6324 (Part I). Interested students should attend the first lecture of CSE6324. See the departmental schedule for time and place.
+Required Background: General CSE408x prerequisites
-----
+\\
-:
-----
-====== Athenians Data Project ======
-**Supervisor**: Nick Cercone
+=====Metaheuristic-based Optimization techniques=====
-**Required Background**: General CSE408x prerequisites
+**Supervisor: Suprakash Datta**
-**Recommended Background**: Data Mining
+Optimization is a crucial step in many computational problems. For computational problems that seem (or are known to be) intractable, metaheuristic-based techniques often work well in practice. These are typically randomized algorithms, often inspired by physical or biological systems. Examples of such algorithms include simulated annealing, genetic algorithms and ant colony optimization. In this project we will focus on particle swarm optimization (PSO), a technique inspired by the search for food by flocks of birds or schools of fish. Briefly, a set (or population) of candidate solutions (called particles) are maintained at all times by the algorithm. These particles move in the search-space using simple rules that make use of the best solutions found so far by the particle as well as by the swarm. Movement of particles result in new particles being generated. The process is repeated until some termination criteria are met and the best solution found is output by the algorithm. While there is no guarantee of optimality, PSO has been shown to produce good or very good solutions for many practical problems. Many variants of PSO's have been proposed. In this problem we will study the performance of some PSO variants on both artificial and real optimization problems.
-__Description__
+The student should be a strong programmer. A good grasp of algorithms and knowledge of C/C++ are desirable but not essential. The work involves reading and understanding existing algorithms and working with the supervisor to design and implement improved algorithms and to measure the performance of the proposed algorithm(s).
-The Athenians Project is a multi-year, ongoing project of compiling, computerizing and studying data about the persons of ancient Athens.
-Possible project ideas for this term span from simpler ones such as
-how to present data in the best possible way, add spatial characteristics to existing data,
-add multimedia data, improve text searching, etc. to more complex ideas such as filling
-missing parts for the "broken" words on the existing inscriptions. Filling text for the broken
-words has been done in the past using expert knowledge. Those experts have establish
-certain rules/guidelines that may be possible to extrapolate in some kind of expert system
-when talking in IT terminology. Furthermore, any hypotheses on word completion enters
-the database with some likelihood. Associating probabilities with hypotheses introduces
-another opportunity for research projects.
-----
-:
-----
-====== Three-Dimensional Context from Linear Perspective for Video Surveillance Systems ======
+For more information, please send email to datta@cse.yorku.ca.
-**Supervisor**:  James Elder
+Required Background: General CSE408x prerequisites
-**Requirements**:  Good facility with applied mathematics
+\\
-__Description__
+=====Data visualization in Skydive=====
-To provide visual surveillance over a large environment, many surveillance cameras are typically deployed at widely dispersed locations.  Making sense of activities within the monitored space requires security personnel to map multiple events observed on two-dimensional security monitors to the three-dimensional scene under surveillance.  The cognitive load entailed rises quickly as the number of cameras, complexity of the scene and amount of traffic increases.
+**Supervisor: Jarek Gryz**
-This problem can be addressed by automatically pre-mapping two-dimensional surveillance video data into three-dimensional coordinates.  Rendering the data directly in three dimensions can potentially lighten the cognitive load of security personnel and make human activities more immediately interpretable.
+Skydive is a prototype system designed for database visualization using a concept of the so called
+data pyramid. The system is composed of three modules (DB - Database Module, D2I -
+Data-to-Image module, and VC - Visualizaton Client). Each is designed to use a different type
+of computer memory. The DB module uses disk to store and manage the raw data, and materialized
+data pyramids. The D2I module works with a small subset of the aggregated dataset,
+and stores data in main memory (RAM). The VC module uses the graphic card’s capabilities to
+perform more advanced operations – such as zooming, scaling, panning, and rotation – over the
+graphical representation of the data.
+Currently the system support three presentation models implemented within the Visualization
+Component, namely:
-Mapping surveillance video to three-dimensional coordinates requires construction of a virtual model of the three-dimensional scene.  Such a model could be obtained by survey (e.g., using LIDAR), but the cost and time required for each site would severely limit deployment.  Wide-baseline uncalibrated stereo methods are developing and have potential utility, but require careful sensor placement, and the difficulty of the correspondence problem limits reliability.
+• a 2D heat-map;
-This project will investigate a monocular method for inferring three-dimensional context for video surveillance.  The method will make use of the fact that most urban scenes obey the so-called “Manhattan-world” assumption, viz., a large proportion of the major surfaces in the scene are rectangles aligned with a three-dimensional Cartesian grid (Coughlan & Yuille, 2003).  This regularity provides strong linear perspective cues that can potentially be used to automatically infer three-dimensional models of the major surfaces in the scene (up to a scale factor).  These models can then be used to construct a virtual environment in which to render models of human activities in the scene.
+• a 2.5 D heat-map by 3D barchart; and
-Although the Manhattan world assumption provides powerful constraints, there are many technical challenges that must be overcome before a working prototype can be demonstrated.  The prototype requires six stages of processing:    1)The major lines in each video frame are detected.  2)  These lines are grouped into quadrilaterals projecting from the major surface rectangles of the scene.  3)  The geometry of linear perspective and the Manhattan world constraint are exploited to estimate the three-dimensional attitude of the rectangles from which these quadrilaterals project.  4)  Trihedral junctions are used to infer three-dimensional surface contact and ordinal depth relationships between these surfaces.  5)  The estimated surfaces are rendered in three-dimensions.  6)  Human activities are tracked and rendered within this virtual three-dimensional world.
+• a 2.5 D terrain (by mesh and UV-mapping).
-The student will work closely with graduate students and postdoctoral fellows at York University, as well as researchers at other institutions involved in the project.  The student will develop skills in using MATLAB, a very useful mathematical programming environment, and develop an understanding of basic topics in image processing and vision.
+The goal of the project is to implement two additional ways of data visualization as well as
+extend some of existing ones, that is:
-For more information on the laboratory: [[http://www.elderlab.yorku.ca]]
+. Implement and test functions for data pyramid-based visualization of time series.
-----
+. Implement functions for visualization based on cross-product of data pyramids.
-:
-----
-====== Estimating Pedestrian and Vehicle Flows from Surveillance Video ======
+. Add support for specular and normal maps for 2.5 D terrain presentation model.
-**Supervisor**:  James Elder
+Required Background: CSE 3421, Java programming course, (C programming course a plus)
-**Requirements**:  Good facility with applied mathematics
-__Description__
+\\
+=====Genome-wide identification of plant micro RNAs=====
-Facilities planning at both city (e.g., Toronto) and institutional (e.g., York University) scales requires accurate data on the flow of people and vehicles throughout the environment.  Acquiring these data can require the costly deployment of specialized equipment and people, and this effort must be renewed at regular intervals for the data to be relevant.
-The density of permanent urban video surveillance camera installations has increased dramatically over the last several years.  These systems provide a potential source of low-cost data from which flows can be estimated for planning purposes.
+**Supervisor: Katalin Hudak**
-This project will explore the use of computer vision algorithms for the automatic estimation of pedestrian and vehicle flows from video surveillance data.  The ultimate goal is to provide planners with accurate, continuous, up-to-date information on facility usage to help guide planning.
-The student will work closely with graduate students and postdoctoral fellows at York University, as well as researchers at other institutions involved in the project.  The student will develop skills in using MATLAB, a very useful mathematical programming environment, and develop an understanding of basic topics in image processing and vision.
+The Hudak Lab in the Biology Department has an opening for a fourth-year Honours student to assist with a bioinformatics project. We study the pokeweed plant, Phytolacca americana, which displays broad-spectrum virus resistance. To evaluate pokeweed gene expression, we recently sequenced the plant’s mRNA and small RNA transcriptomes under jasmonic acid (JA) treatment. JA is a plant hormone that mediates defence against pathogens and insect herbivores. We are interested in learning how pokeweed gene expression is regulated by miRNAs during biotic stress.  Please note: no previous knowledge of biology is required.
-For more information on the laboratory: [[http://www.elderlab.yorku.ca]]
+Working with the support of a PhD student, your project will involve:
+) Prediction of micro RNA (miRNA) targets on the basis of complementary sequence matches
+) Correlation of miRNA and mRNA expression changes to identify genes that are regulated by miRNAs
+) Conducting pathway analysis to determine which biological processes are controlled by miRNAs
+) Construction of a miRNA/target interaction network to visualize predictions
+This work will contribute to a scientific manuscript on miRNA-mediated gene regulation in pokeweed during response to JA.
+Requirements:
+) Pre-requisites as per EECS Calendar
+) Facility with script-writing/modification (in Perl or Python)
+) Preference for students with knowledge of statistics and familiarity with R programming
+) Able to begin in September 2015
+Learning outcomes:
+) Manipulate and analyze quantitative biological data
+) Develop and test hypotheses by modifying existing software and writing new script
+) Manage a CentOS computer server to store and facilitate ongoing research
+No knowledge of biology is required.
+For more information, please see:
+ Hudak Lab website- http://hudak.lab.yorku.ca/
+RNA sequencing- http://www.illumina.com/applications/sequencing/rna.html
+miRNAs- http://en.wikipedia.org/wiki/MicroRNA
+\\
+=====Dynamic Interface Detection and Control Project=====
+**Supervisor: Michael Jenkin**
+Contrary to most industries, fine chemical manufacturing is dominated by batch production methods. Increasing economic, environmental and safety pressures are motivating a turn towards continuous synthesis. Rather than making products in one big flask, continuous synthesis involves performing chemical reactions by flowing reagents through a tube. Working in this way provides more control over the reaction parameters leading to increases in product quality, and process efficiency and safety. The flow chemistry industry for fine chemical production is a relatively new but burgeoning field with a projected market capacity of billions of dollars by 2018.
+Extraction of the reaction mixture for purification and/or further processing is an important step in chemical manufacturing. This is a relatively straightforward operation in batch production, but offers several challenges for flowing processes. In order to facilitate continuous liquid extraction we require a sophisticated control system. This project involves designing, constructing and evaluating a pertinent practical problem in the field.
+A key step in the process takes place in a clear tube that is mounted vertically. The tube contains two fluids with a boundary between them. During the process material flows into and out of the tube from the top and the bottom. Chemical reactions take place within this tube and It is essential that the position of the boundary be monitored as its position in the tube is used to control the flow of materials into the tube.
+One way of solving this problem is to float a marker at the boundary between the two liquids and to monitor this boundary using a video camera. Although this approach solves the problem, it requires the introduction of a specific float within the tube. Can we build a system that monitors the boundary without resorting to the use of an artificial float?
+Specific goals of the project include:
+- Develop a computer vision system that can detect and monitor the interface between two miscible fluids of different density.
+- Evaluate the performance of the system over a range of different (and typical) fluids
+- Explore the use of different illuminant/filter choices to simplify the task for specific fluid combinations.
+The successful candidate(s) will have the experience of working with a diverse group of scientists and engineers toward the design and implementation of an automated liquid extraction device with applications across many industries. Upon successful prototyping, you will be able to interact with professionals in high-throughput manufacturing and system integration. Based on project success, you may be invited to join the MACOS(TM) team for implementation and process validation, which may involve opportunities in graduate school. You will have the opportunity to interact with the broad audience of MACOS(TM) technology including governmental regulatory agencies and industrial partners. This project will give you a great opportunity to apply your engineering expertise and gain experience in process implementation and technology transfer.
+For further information please contact,
+Michael Jenkin (jenkin@cse.yorku.ca) or Michal Organ (organ@yorku.ca)
+\\
+===== DDoS Attack using Google-bots =====
+**Supervisor: Ntalija Vlajic**
+**Recommended Background**: CSE 3213 or CSE 3214, CSE 3482
+Not long ago, botnets - networks of compromised computers - were seen as
+the most effective (if not the only) means of conducting Distributed Denial
+of Service (DDoS) attacks. However, with the growing popularity and prevalence
+of application-layer over other types of DDoS attacks, the DDoS execution
+landscape is becoming increasingly more diverse. An especially interesting
+new trend is the execution of application-layer DDoS attacks by means of
+skillfully manipulated Web-crawlers, such as Google-bots.
+The goal of this project is to design, implement and test a real-world
+framework consisting of the following: a) the attacker's web-accessible
+domain specially designed to attract Google-bots and then manipulate them
+into generating attack traffic towards the target/victim site; b) the
+victim's Web site set up in Amazon S3 cloud. In addition to the hands-on
+component, the project will also look into the statistical/numerical
+estimation of the framework's anticipated 'attack potential' relative
+to an actual (real-world) target/victim site.
+\\
+====== Attentive Sensing for Better Two-Way Communication in Remote Learning Environments ======
+**Supervisor**: James Elder
+**Required Background**: General CSE408x prerequisites, good programming skills,
+good math skills, knowledge of C and MATLAB programming languages
+One of the challenges in remote learning is to allow students to communicate effectively with the lecturer.  For example, when a student asks a question, communication will be more effective if the instructor has a zoomed view of the student’s face, so that s/he can interpret expressions etc.
-----
+The goal of this project is to apply attentive sensing technology (www.elderlab.yorku.ca) to this problem.  This technology is able to monitor a large environment such as a classroom and direct a high-resolution ‘attentive’ sensor to events of interest.
-:
-----
+In particular, working with a senior graduate student or postdoctoral fellow, the  successful applicant will:
+  - Study the problem of detecting hand-raises in the preattentive sensor stream
+  - Implement algorithms for detecting hand-raises based upon this investigation
+  - Evaluate these algorithms in a real-classroom setting, using proprietary attentive sensing technology
+====== Attentive Sensing for Sport Video Recording Markets ======
+**Supervisor**: James Elder
+**Required Background**: Good programming skills; Good math skills; Knowledge of C and MATLAB programming languages
+The goal of this project is to modify York University’s patented attentive sensor technology to the sport video recording market.  Specific application domains under investigation include skiing, indoor BMX parks, and horse tracks.
+The general problem is to use attentive sensing technology (www.elderlab.yorku.ca) to visually detect and track multiple moving agents (e.g., skiers, riders, horses) and to select specific agents for active high-resolution smooth pursuit.
+The student will work with senior graduate students, postdoctoral fellows and research scientists to help modify the attentive sensing technology to operate in these domains.   Specific tasks include:
+.     Ground-truth available datasets
+.     Evaluate current attentive algorithms on these datasets
+.     Modify these algorithms to improve performance on these datasets
+------------
+\\
+====== JPF in a Jar ======
+**Supervisor:** Franck van Breugel
-====== Tandem repeat detection using spectral methods ======
+Description:
+JPF, which is short for Java PathFinder, is an open source
+tool that has been developed at NASA's Ames Research Center.
+The aim of JPF is to find bugs in Java code.  Instead of
+using testing to find those bugs, JPF uses model checking.
+The facts that JPF is downloaded hundreds of times per month
+and that some of the key papers on JPF have been cited more
+than a thousand times reflect the popularity of JPF. In
+fact it is the most popular model checker for Java.
-**Supervisor**: Suprakash Datta
+A study done by Cambridge University in 2014 found that the
+global cost of debugging code has risen to $312 billion annually.
+Furthermore, on average software developers spend 50% of their
+programming time with finding and fixing bugs.  As a consequence,
+advocating the use tools, such as JPF, may have significant impact.
-**Required Background**: The student should have completed undergraduate courses in Algorithms and Signals and Systems.
+Installing JPF is far from trivial.  The tool itself has been
+implemented in Java.  Therefore, it should, in theory, be
+feasible to encapsulate JPF in a Java archive (jar) file.
+This would make it significantly simplifying the installation
+process of JPF and, therefore, make the tool more easily
+accessible to its potential users.
-**Recommended Background**: Some background in Statistics is desirable but not essential.
+The aim of this project is to attempt to put JPF in a jar.
+Since JPF relies on a number of configuration files, so-called
+Java properties files, incorporating these properly into the
+jar is one of the challenges.  Setting JPF's classpath is
+another challenge.  Since JPF changes almost on a daily basis,
+our modifications to JPF should ideally be limited to only a
+few classes, yet another challenge.
-__Description__
+In this project you may collaborate with graduate students
-DNA sequences of organisms have many repeated substrings. These are called repeats in Biology, and include both exact as well as approximate repeats. Repeats are of two main types: interspersed repeats (which are spread across a genome) and tandem repeats, which occur next to each other. Tandem repeats play important roles in gene regulation and are also used as markers that have several important uses, including human identity testing.
+of the DisCoVeri group (discoveri.eecs.yorku.ca) and
+computer scientists of NASA.  For more information, feel
+free to send email to franck@cse.yorku.ca.
-Finding tandem repeats is an important problem in Computational Biology. The techniques that have been proposed for it fall into two classes: string matching algorithms and signal processing techniques. In this project, we will explore fast, accurate algorithms for detecting tandem repeats and evaluate the outputs of the algorithms studied by comparing their outputs with those of available packages, including mreps (http://bioinfo.lifl.fr/mreps/), SRF (http://www.imtech.res.in/raghava/srf/) and TRF (http://tandem.bu.edu/trf/trf.html).
+**Required Background:** General CSE408x prerequisites
+\\
+------------
+\\
-The student will implement existing spectral algorithms based on Fourier Transforms and on an autoregressive model. He will then make changes suggested by the supervisor, and evaluate the effect of the modifications. Throughout the course, the student is required to maintain a course Web site to report any progress and details about the project.
-----
-:
-----
-====== Touch- and Gesture-based Text Entry With Automatic Error Correction ======
+====== Mining Software Repositories Data======
-**Supervisor**: Scott Mackenzie
+**Supervisor:** Zhen Ming (Jack) Jiang (zmjiang at cse dot yorku dot ca)
-**Required Background**:
+**Required Background:** Good programming skills in Java; Good analytical and communication skills; Knowledge in AI and statistics; Interested in large scale software analysis
-CSE3461 (or equivalent), CSE3311 (or equivalent), CSE4441 (or equivalent)
-A student wishing to do this project must be well versed in Java, Eclipse, and developing java code for the Android operating system.
+**Short Description:** Software engineering data (e.g., source code repositories and bug databases) contains a wealth of information about a project's status and history. The research on Mining Software Repositories (MSR) aims to transform the data from static record-keeping repositories into knowledge, which can guide the software development process. For example, one can derive correct API usage patterns and flag anomalous (and potentially buggy) API usages by mining the source code across many projects in GitHub and Google Code. In this project, the student(s) will research and develop an efficient infrastructure, where MSR researchers and practitioners can share and analyze such data.
-**Recommended Background**:
+\\
-Possession of an Android touch-based phone or tablet would be an asset, but is not essential.
+------------------
+\\
-__Description__
-This project involves extending a touch-based text entry method to include automatic error correction.  The method, as is, uses Graffiti strokes entered via a finger on a touch-based Android tablet.  The stroke recognizer works fine, but it is not perfect.  Some strokes are mis-recognized while others are un-recognized.  The fault is sometimes attributable to the recognizer, but, often, the fault is simply that the user's input was sloppy.  The work involves developing, integrating, and testing software.  The core software is already written, but automatic error correction is lacking. The primary task of the added software is to receive a sequence of characters representing a word and matching the sequence with words in a dictionary.  If a match is found, all is well (presumably).  If a match is not found, the search is extended to find a set of candidate words that are "close" to the inputted sequence.  "Close", here, involves using a minimum string distance algorithm (provided).  The user interface must be modified to present the user with alternative words in the event an error occurred.  The user selects the desired word by tapping on a word in the list.  The project will involve testing the new input method in a small user study and writing up a report describing the work and presenting the results of the user study.
+======Model-based Design and Development of Embedded Systems with Code Generation Tools======
-----
+**Supervisor:** Jia Xu
-:
-----
-====== Early Breast Cancer Detection based on MRI’s. ======
-**Supervisor**: Amir Asif
+**Required Background:** At least a B+ in Embedded Systems (CSE3215), MATLAB, C programming skills, solid experience in using a microcontroller
+such as Arduino.
-**Required Background**: General CSE408x prerequisites
+**Project Description:**
-**Recommended background**: Signal processing, i.e. CSE3451
+Model-based design with code generation tools can be used for simulation, rapid prototyping, and hardware-in-the-loop testing of embedded systems. This project explores model-based design and development of embedded systems on various hardware platforms with code generation tools. The selected student will develop and test embedded systems using model-based design and code generation tools such as MathWorks MATLAB /Simulink Coder.
-Project Description: This research will develop advanced computer-aided, signal
+\\
-processing techniques for early detection of breast cancer using the available
+------------------
-modalities. In particular, we propose to develop time reversal beamforming imager,
+\\
-based on our earlier work in time reversal signal processing, for detecting early stage
-breast cancer tumours from MRI data.
-Our preliminary work has illustrated the type of
-results that are possible for breast cancer detection by applying time reversal signal
-processing on MRI breast data. In this research, we propose to extend these results to
-provide a quantitative understanding of the practical gains provided by time reversal
-in MRI based breast cancer detection and its limitations. This will be accomplished
-a local hospital, and running our algorithms on these datasets. The first step is
-important to check the validity of our algorithms. The next step is to compare the
-estimated locations of the tumours (as derived with our algorithms) to their precise
-locations as identified by the pathologists. The second step will quantify the accuracy
-of our estimation algorithms.
-----
+======C2000 Concerto Microcontrollers======
-:
-----
-====== Developing Fast Speech Recognition Engine using GPU ======
-**Supervisor**: Hui Jang
+**Supervisor:** Jia Xu
-**Required Background**:
+**Required Background:** At least a B+ in Embedded Systems (CSE3215),
-General prerequisites
+strong C programming skills, solid knowledge of microcontrollers
+**Description:** The C2000 Concerto family of microcontrollers combines
+two cores on a single-chip with on-chip low latency interprocessor communication between the two cores: a C28x 32-bit control core for
+real-time control with faster/more loops and small sampling window;
+and an ARM 32-bit Cortex-M3 host core for communications and general purpose. The selected student will evaluate the capabilities of the
+C2000 Concerto family of microcontrollers through testing and investigating open source software for real-time control applications
+that runs on C2000 Concerto Microcontrollers.
-__Description__
+\\
+------------------
+\\
-Recently, Graphics Processing Units (GPU's) have been widely used as an extremely fast computing vehicle for a variety of real-world applications. Many software programs have been developed for GPU's to take advantage of its multi-core parallel computing architecture (see gpgpu.org). In the past few years, we have developed a state-of-the-art speech recognition engine using anti-C at York and it runs very well in a normal CPU-based platform. In this project, you are required to port this engine (the C source code is available) based on the standard CUDA or OpenCL library to make it run in GPU's. It has been reported that this may lead to a speedup of at least 10 times faster in many speech recognition tasks [1][2].
+======Real-Time Bidding Platform======
-During the recent years, there is an increasing demand in the job market for programmers who can use GPU's for general purpose computing tasks. This project will serve as a perfect vehicle for you to learn such a cutting-edge programming skill.
+**Supervisor:** Jia Xu
-References
+**Required Background:** At least a B+ in Operating System Fundamentals
+(CSE3221), strong Ubuntu/Linux, C++ programming, GCC, TCP/IP skills
-[1] Kisun You, Jike Chong, Youngmin Yi, Gonina, E., Hughes, C.J., Yen-Kuang Chen, Wonyong Sung, Keutzer, K., "Parallel Scalibility in Speech Recognition: inference engines in large vocabulary continuous speech recognition," IEEE Signal Processing Magazine, pp.124-135, No. 6, Vol 26, Nov 2009.
+**Description:** Real-time bidding (RTB) is a new method of selling and buying online display advertising in real-time one ad impression at a time. Once a bid request has been sent out, all bids must be received within a strict deadline - generally under 100 milliseconds, including network latency. This project explores RTBkit, an open source SDK allowing developers to create customized real time ad bidding systems (for Media Buyers/Bidders).
-[2] Jike Chong, Ekaterina Gonina, Youngmin Yi, Kurt Keutzer, "A Fully Data Parallel WFST-based Large Vocabulary Continuous Speech Recognition on a Graphics Processing Unit," Proc. of Interspeech 2009, Brigton, UK, 2009.
+\\
-----
+------------------
-:
+\\
-----
-====== Solving Polynomials ======
-**Supervisor**: Mike McNamee
+======Circuit and Board Design for a Pulsed Ground Penetrating Radar======
-**Required Background**:
+**Supervisor:**Sebastian Magierowski
-General prerequisites plus course in Numerical Methods, and knowledge of programming, preferably Fortran
+**Description:** The project requires the construction of components for a ground penetrating radar.  The students would have to design microwave boards for the high-frequency components of this unit, on both the transmitter and the receiver.  On the transmitter side the board would take a 5-MHz input clock, run it through a series of off-the-shelf amplifiers and then through a shaping circuit that would convert the input into an outgoing series of pulses (still at 5-MHz repetition rate) less than 400-ps in duration each.  The bandwidth of the signal is roughly 2-8 GHz and hence requires very careful board layout.  The receiver would be a time-shifted sampler, used to sample the returning pulses in progressive periods.  This radar circuit is ultimately intended to be positioned on a rover doing ground analysis.
-__Description__
+**Required Background** A background in undergraduate-level electronics is very important.  Experience with board level implementations and knowledge of microstrip lines would be helpful, otherwise the basics would have to be picked up during the project.
-In this project you will compare several efficient methods for solving polynomials.
+\\
-----
+------------------
-:
+\\
-----
+More project proposals may be added here in the first week of the winter term.
+\\
+------------------
+\\
+\\