EECS4080/4088/4480/4070

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====== Proposed Projects   ======

Below is a list of 4080/4088/4480 projects proposed by faculty members. More projects may be added once they come in (normally in August). Please contact the supervisor directly you are in interested in a project. You can also contact faculty members individually to discuss possible projects. Click [[http://eecs.lassonde.yorku.ca/community/faculty-members/|here]] to see a list of faculty members, their research areas and their contact information.

====== Full-Stack Developer(s) ======
**Course:** EECS4080/4088

**Supervisor:** Prof. Uyen T. Nguyen 

**Contact:** utn@eecs.yorku.ca

**Project Description and Responsibilities:**
The student(s) will be responsible for developing a web application. The primary focus will be the development of the user interface, web services, API and database interactions, while ensuring system stability and responsiveness among all application modules.

**Responsibilities:**
  * Development of a modern web application with a responsible user interface, and a back-end responsible with processing user input and interacting with various API end points and database engines
  * Building reusable code and libraries for future use
  * Design and implementation of data storage solutions
  * Collaborate with other team members 

** Required Skills:**
  * Good knowledge of a back-end programming language such as Python or Java EE
  * Good understanding of front-end technologies and platforms, such as Javascript, HTML5, Angular or React
  * Good knowledge of RESTFul web API concept and architecture 
  * Good knowledge of database concepts such as SQL and NoSQL
  * Good knowledge of JSON or XML formats and libraries to produce them
  * Some understanding of code versioning tools, such as Git
  * Implementing automated testing platforms and unit tests

** Good to Have:** 
  * Understanding differences between multiple delivery platforms such as mobile vs desktop, and optimizing output to match the specific platform
  * Understanding of secure coding practices, and latest web development standards 
  * Recommended education level: 3rd year undergraduate or higher in Computer Science or equivalent program

**Notes:**
  * Email Prof. Uyen T. Nguyen (utn@eecs.yorku.ca) a copy of your resume listing courses, projects and prior experience relevant to the project.
  * A student completing this project successfully may be hired (paid) as a research assistant after the course is over to continue the next step of the project.


====== Building a Database of Dark Webpages ======
**Course:** EECS4080/4480/4088

**Supervisor:** Prof. Uyen T. Nguyen 

**Contact:** utn@eecs.yorku.ca

**Project Description and Responsibilities:**
  * Searching internet resources (google, reddit, dark web link archives, etc.) for links to dark websites of interest
  * Grouping and categorizing web pages
  * Developing graphs representing the data present on the found dark websites
  * Assist in the development of a dark web crawler
  * Assist in the development of information retrieval systems

**Required Technical Skills:**
  * Experience building programs in Python
  * Good understanding of object-oriented design
  * Experience with Windows and Linux environments
  * Experience with Excel and/or a commonly used graph generation program
**Required Non-Technical Skills:**
  * Strong teamwork skills
  * High organizational skills
  * Good time management skills (there will be weekly check-ins)
**Non-required Asset Skills:**
  * Knowledge of information retrieval methods
**Notes:**
  * Email Prof. Uyen T. Nguyen (utn@eecs.yorku.ca) a copy of your resume listing courses, projects and prior experience relevant to the project.
  * A student completing this project successfully may be hired (paid) as a research assistant after the course is over to continue the next step of the project.

====== Automation of Copyright Takedowns ======
**Course:** EECS4070/80/88/90/4480

**Supervisor:** Prof. James Andrew Smith 

**Contact:** drsmith@yorku.ca

COVID has accelerated the trend for delivering university courses online. This has been a boon to providing accessible learning modes to students.  However, it has also made it more likely for course content to be uploaded to and distributed on commercial, for-profit file sharing sites like Chegg and Course Hero, without permission of the content creator.

A copyright takedown process (e.g. DMCA) is in place on these commercial sites but it is cumbersome to use. The objective of this project is to semi-automate the take-down process in one of two ways:

1. Allow a copyright holder to identify a category of course material (e.g. a course name and number) a priori and engage a scheduled process which regularly scans a commercial site (e.g. Course Hero) and automatically submits takedowns on behalf of the copyright holder

2. Submit reports to the copyright holder when an identified category of course material is found on a commercial site (e.g. Course Hero) and asks the copyright holder whether a takedown request should be made on the holder's behalf.

**Required skills:** General programming skills

**Recommended skills:** Experience in Python (and perhaps Beautiful Soup) and/or Java and/or equivalent

====== Visualization of Course Maps at YorkU ======

**Course:** EECS4070/80/88/90/4480

**Supervisor:** Prof. James Andrew Smith 

**Contact:** drsmith@yorku.ca

Students at York have long been missing the ability to visualize the connections between courses when planning or reviewing their progress through their program.  We would like to make a web-centric visualization tool available to students that scrapes data from the official online course calendar so that students can better inform the decisions they make while studying at York.

This is a continuation of an existing open-source project written in Python.  Interested students will be asked to improve the existing code base so that:

1. A visualization can be produced and displayed on the web

2. Corrections to the existing data set (the University's calendar website) can be submitted to an online repository and reused

Students involved in the project will be required to maintain public-facing documentation. The result of this project will remain open source for further development by students, staff and faculty.

**Required skills:** General programming skills

**Recommended skills:** Experience in Python (and perhaps Beautiful Soup) and web-centric tools

/*
====== Characterizing, Understanding, and Detecting Software Bugs in Machine Learning Frameworks ======
**Course:** EECS4080

**Supervisor:** Song Wang 

**Contact:** <wangsong@yorku.ca>

Today, machine learning and its applications has been integrated into every part of our society. With the development and evolution of information technologies such as smartphones, self-driving cars, and robotics, the dependence of our society on machine learning systems continues to grow, which makes the impact and cost of bugs in these intelligent systems increase dramatically. Building reliable and secure machine learning systems has become an increasingly critical challenge for software developers. Thus, characterizing and understanding the root cause of software bugs in ML frameworks is critical to detecting and repairing buggy behavior.

This project will first conduct an empirical study to analyze and summarize unique characteristics of software bugs collected from four typical ML frameworks (PyTorch, TensorFlow, CNTK, and Theano). Based on the findings from the empirical study, we will further propose actionable guidelines for designing and exploring new software bug detection approaches to find new bugs on machine learning frameworks and their applications.

**Required skills:** General EECS4313 and EECS3311 prerequisites;

**Recommended skills:** Solid programming skills with Python and Java.

====== Image Processing for Social Coding ======
**Course:** EECS4088 (Capstone Project)

**Supervisor:** Maleknaz Nayebi 

**Contact:** <mnayebi@yorku.ca>

Software developers are increasingly sharing images in social coding environments such as stack overflow, GitHub, Bugzilla, and Slack. This growth is parallel to the general growth of in visual interactions in general purpose online social networks like Instagram, Facebook, and Pinterest. Developers' shared images are meaningful and provide complementary information compared to their associated text. These images extensively help in understanding the change requests, questions, or the responses submitted. Relying on these observations, we are working on automatically processing these images by first forming a database similar to ImageNet for software domain and then applying the text detection object detection and automated captioning techniques on these data. We will work with software teams and software developers to evaluate the usefulness of our methods and results. The project includes:

(i) Forming and structuring a dataset of crowd labelled images for software related images, 

(ii) Mining content and objects within developers’ shared images, 

(iii) Automatic captioning the images to describe the content. 

**Required skills:** Good knowledge of Python, Good knowledge on Machine learning, Good knowledge of image processing, Ability to work independently, Ability to communicate clearly. 

====== Release Management for Mobile Apps ======
**Course:** EECS4080

**Supervisor:** Maleknaz Nayebi 

**Contact:** <mnayebi@yorku.ca>

Release planning problem is addressing the question of what functionality should be included in any version and when that version should be released to different segments of users. Proper decision about the functionality of evolving software product releases is critical for the success or failure of a product.  The rise in popularity of mobile devices has led to a parallel growth in the size of the app store market, intriguing several research studies and commercial platforms on mining app stores. App store reviews are used to analyze different aspects of app development and evolution. This led into the concept of user driven release management. This project includes:

(i) Evaluating the applicability of four state of the art release management tools for mobile apps,

(ii) Testing and enhancing the prototype tools for these four release management techniques. 

**Required skills:** Good knowledge of Python, Ability to manage Git and Jupiter Notebooks, Good knowledge on Machine learning, Ability to work independently, Ability to communicate clearly. 


====== Estimating emotional state from a speech audio signal ======
**Course:** EECS4080/4088

**Supervisor:** Michael Jenkin 

**Contact:** <jenkin@eecs.yorku.ca>

When a robot interacts with a human it can be very helpful if the robot can estimate the emotional state of the person to whom it is talking. This estimation can be made in a number of ways, from the choice of words used, the visual cues obtained from a camera pointed at the person, and through an analysis if the speech signal obtained from a microphone listening to the speaker. This project is concerned with this last task. This project will apply modern recurrent neural networks, and in particular LSTM to the problem. The project will involve three major phases

(i) Background work: Understanding the problem of estimating speech emotion from the audio signal and a review of approaches to date. Identifying and obtaining access to appropriate datasets for training and evaluations.

(ii) Basic implementation: Based on the results of above, implement an existing LSTM-based approach to the problem and evaluate on the dataset identified above.

(iii) Integration with a social robot system (SENTRYNet) so that the robot can utilize this information in the development of dialog when interacting with speakers.

**Required skills:** General EECS408x prerequisites. Good knowledge of Python. Ability to work independently.

====== Automatic classification of Eurasian Water-Milfoil from sonar and visual data ======
**Course:** EECS4080/4088

**Supervisor:** Michael Jenkin 

**Contact:** <jenkin@eecs.yorku.ca>

Many lakes in Canada are infested with Eurasian Water-Milfoil (see Eurasian Water-Milfoil – Ontario's Invading Species ...www.invadingspecies.com › eurasian-water-milfoil). Eurasian Water-Milfoil (EWM) is an invasive water plant that is detrimental to the health of the lake which is infected. Treating such infections requires understanding where the infections are and the state of the infection. As part of a larger robot project, this project will develop a system for the automatic classification of sensor signals from an autonomous robot boat this is being deployed to monitor EWM infestation in a lake north of Toronto. This work will concentrate around the development of an Amazon Mechanical Turk to assist in labelling visual and sonar imagery to train a CNN to label infestation levels at different locations in the lake. The project will involve three major phases

(i) Assist in data collection. For the first few weeks of term (before the weather changes) you will help in data acquisition, editing and organization while reviewing the process of Mechanical Turk systems (such as the Amazon toolkit).

(ii) In consultation with domain experts, develop a model for infestation level and construct a Turk to apply this to a training dataset

(iii) Develop a DNN to label the multi-modal dataset and evaluate it.

**Required skills:** General EECS408x prerequisites. Good knowledge of Python. Ability to work independently. Ability to interact with subject matter experts. Willingness to participate in data collection sessions as scheduled in the early fall.

====== A framework for VR-based vestibular assessment tools ======
**Course:** EECS4080/4088

**Supervisor:** Michael Jenkin 

**Contact:** <jenkin@eecs.yorku.ca>

Commodity VR is already being used as part of ongoing assessment of a range of different conditions, including vestibular damage and its treatment. This project involves the development of a software library (written in Unity) to provide VR-based tools to support vestibular treatment both at the clinic and remotely. This work will build upon an existing code base but will (i) refactor the software so as to be useful as a more general library, and (ii) support a wide range of assessment and rehabilitation tools. This work will involve interaction with an off-site partner in their physiotherapy office. The project will involve

(i) review of VR-based vestibular assessment and treatment and the existing system and treatment/assessment systems

(ii) Understanding the existing code base and development of library structure to ensure a more device-agnostic input system

(iii) Development of a small number of treatment modules (2 or 3) to demonstrate the effectiveness of the tools/libraries developed

**Required skills:** General EECS408x prerequisites. Good knowledge of C#. Ability to work independently. 

*/

/*
**Recommended skills:** Good programming skills, good math skills, experience with Python
*/

/*
====== Serverless Computing Simulator ======
**Supervisor:** Hamzeh Khazaei 

**Contact:** <hkh@eecs.yorku.ca>

We are amid an evolutionary paradigm shift in cloud computing towards
serverless platforms. This change is due to several improvements over traditional cloud computing, like handling all the system administration operations,
improving resource utilization, potential operational cost savings, improved energy efficiency, and more straightforward application development. However,
current implementations have not yet reached the full potentials of serverless
computing. Global research and efforts are required for improving the efficiency
and performance of the serverless computation far beyond the current state. In
[[https://pacs.eecs.yorku.ca/|PACS Lab]], we are deeply involved in this global effort to improve the status quo.

This project aims to address these shortcomings using analytical and datadriven methods to improve the performance, power efficiency, and adoption of
serverless computing for all industries. The project will be conducted in two
phases.
  - In the first phase, our goal is to build a serverless computing platform simulator which mimics the behaviour of public serverless computing offerings. The resulting simulator should produce a behavior similar to the trace of our experiments on Amazon AWS Lambda.
  - In the second phase, we will be modifying and optimizing the operational management layer policies in the simulator in order to improve the resource utilization of the system and the Quality of Service (QoS) indicators such as response time and system availability.

**Required skills:** General EECS408x prerequisites, interest and willingness
to learn about Cloud Computing, serverless computing in particular.

**Recommended skills:** Good programming skills, good math skills, experience with Python

====== Blockchain-based Serverless Computing Platforms ======
**Supervisor:** Hamzeh Khazaei 

**Contact:** <hkh@eecs.yorku.ca>

As the latest paradigm in cloud computing, serverless computing or functionas-a-service (FaaS) has recently gained a lot of attention both in academia and
industry. In serverless computing, the developer delegates the infrastructure
management tasks to the provider. As a result, the developer can focus on
designing and implementing the application instead of spending time on the
management, operation, and maintenance of the infrastructure.

Our research in PACS Lab1 has shown that personal computers have great
potential to be used as the underlying infrastructure for building green, economic, open and public serverless computing platforms. To do so, we leveraged
blockchain systems to introduce transparency in the computation as well as
the billing. This system has been proposed in a recently submitted paper in
which we also designed and implemented a preliminary prototype to show the
feasibility and validity.

In this project, the student will be involved in research and development of
the prototype of the proposed platform so that it can be used by all targeted
stakeholders in real world. The project includes some degree of research, and
both backend and front-end development.

**Required skills:** General EECS408x prerequisites; Python programming;
having interest in cloud computing and blockchain.

**Recommended skills:** Basic knowledge in Linux containers and microservice architecture, blockchain systems, Python and serverless computing.

====== The Platform for Modeling and Optimizing Serverless Applications ======
**Supervisor:** Hamzeh Khazaei 

**Contact:** <hkh@eecs.yorku.ca>

Coupled with the development of lightweight virtualization, specifically containers, is a growing trend in the paradigm of cloud computing shifting from Infrastructure-as-a-Service (IaaS) to Function-as-a-Service (FaaS). Many cloud service providers have launched their FaaS platforms where developers can host serverless functions with high-scalability, pay-as-you-go billing model, and reduced management overhead. However, such a new trend raises new important questions, including the predictability and optimization of the performance and cost of serverless applications.

In PACS Lab, researchers have been working on addressing these urgent needs in the serverless computing area not yet addressed by industries and academics. This project is based on our published and submitted papers in which we give practical solutions to performance modeling and optimization problems for the serverless computing paradigm.

This project will solve pain points for serverless application developers by providing an online ready-to-use platform for profiling, predicting, and optimizing serverless applications. The student will involve in developing a toolkit that integrates multiple APIs of major cloud service providers, automates the deployment, test, and performance profiling of serverless applications, and leverages analytical models to give developers informed performance and optimized application configurations. The project will involve studying the serverless architecture and developing a web application.

**Required skills:** General EECS408x prerequisites; experience with major cloud computing platforms and APIs, experience with any web framework.

**Recommended skills:** 
Experience with containers and serverless functions, solid programming skills.

*/

/*
====== Heart and Voice Signal Processing For Sleep Apnea Detection ======
**Supervisor:** Hossein Kassiri

Sleep apnea is a neurological condition where the patient’s breathing is interrupted during sleep, which can lead to excessive daytime sleepiness, irritability, and morning headaches. Left untreated, it increases the risk of numerous serious health issues, including high blood pressure, irregular heartbeat, and stroke. An estimated 860,000 Canadians reported being told by a health professional that they have sleep apnea, but many more people likely remain undiagnosed.

This project will be done in collaboration with a Toronto-based medical device company that is working on the development of a miniature wearable device for sleep monitoring and apnea detection. The project will be conducted in two phases. In the first phase, the goal is to study and evaluate the efficacy of using various sensory signal (i.e., biomarker) in sleep apnea detection. A short list of candidate biomarkers are selected as a result of literature review, and their importance in apnea detection is evaluated using pre-recorded labelled online datasets. In the second phase, a signal processing algorithm for sleep apnea detection is developed that uses the selected biomarkers from Phase I as its inputs. In addition to detection, the algorithm is intended to evaluate the episode’s severity, frequency, and patient-specific pattern.

The collaborating company will develop the hardware that contains the biosensors identified by the students and will be responsible for firmware development to control and extract data from the sensors. The company will also develop a mobile app that displays the data obtained, and produces test units that can be used by real human testers.

**Required skills:** General CSE408x prerequisites, good programming skills, good math skills, knowledge of C or MATLAB programming languages.

====== Patient-specific epilepsy seizure detection using machine learning ======
**Supervisor:** Hossein Kassiri

Accurate detection of neurological disorders such as epilepsy seizures using brain signals requires algorithms that can adjust themselves from patient to patient and from time to time. Data-driven algorithms using machine learning provide us with such patient-specific tools that allow for processing the data recorded from the brain and decide whether or not it can be classified as an abnormal activity for a specific patient.

This project is aimed at development and optimization of such a machine learning algorithm for early detection of epilepsy seizures. The student will use pre-recorded labeled data from an online standard dataset to train, cross-validate, and test the algorithm. The algorithm is later optimized for computational resource consumption.

**Required skills:** General CSE408x prerequisites, good programming and math skills, knowledge of C or MATLAB programming languages, basic knowledge of machine learning and pattern recognition (EECS 4404 or similar).

====== Mobile app development for interfacing with a brain implant ======
**Supervisor:** Hossein Kassiri

Our group of researchers in ICSL are working towards implementation of an implantable closed-loop microelectronic system-on-chip (SoC) for recording and processing of EEG signals to be able to detect and treat various neurological disorder patients.

Online monitoring and control of brain signals is one of the key features that can help the clinician significantly. Currently an electrical engineer has to be on-site to setup the system and adjust it upon clinician’s request. Therefore, a simple GUI that can be operated by a non-engineer enables the clinician to control the process entirely. The project’s goal is to develop a mobile application that is capable of receiving signals and sending commands through a Bluetooth link. Also the app should be capable of displaying the recorded signal.

The student is expected to have experience with mobile app development (iOS or Android).

**Required skills:** General CSE408x prerequisites, mobile app development (iOS or Android) experience.

====== Biometric access control ======
**Supervisor:** Amir H. Chinaei

Biometrics as a means of access control has been previously studied and
found to be a popular choice for guaranteeing authentication and
authorization. This includes: iris, voice, face, fingerprint, and hand
geometry recognition. Biometric features possess an if-and-only-if
relationship. `

This project investigates a solution that enables emergency medical
technicians to have simple and fast, remote and token-free, as well as
privacy-preserved and reliable access to patients’ medical information. The
idea is to provide the technicians with a mobile system including a
biometric reader device, through which they gain access to necessary
attributes of patients’ electronic health record using the patient’s
biometrics, such as fingerprint. Reliability is employed by exploiting the
uniqueness of a person’s fingerprint as a means of access control as well as
by precision of biometric reader devices, such as fingerprint scanners.
Privacy of patients is preserved by enforcing an arbitrary privacy policy.
In such system, the only required tokens are some biometric information;
patients need not to carry with them an additional token—such as a health
card, driving license, etc., to receive the service.

**Required skills:** General CSE408x prerequisites, passion for reading and
writing critiques, experience with embedded devices and programming.

====== Decentralized access control using ABAC and application plugins ======
**Supervisor:** Amir H. Chinaei

This project aims at designing and developing software prototype that helps
to advance security of information and privacy of users in web
applications--with the means of decentralized administration. The project
focuses on data security and user privacy in popular application domains
such as health information systems and social media. The goal is to devise
and integrate comprehensive mechanisms towards decentralized
privacy-preserved administration models, with web-based and user-friendly
interfaces and implemented by application plug-ins. The methodology is to
first analyze the privacy risks that exist in current web applications such
as in social media applications. A role-based only approach to data privacy
is not sufficient because role-assignment must be managed centrally to be
efficiently implemented. Thus, the assignment of a role to a particular
object for a particular subject is administrated by the system so there is
no way for a user to assign access rights beyond those defined by some
central authority. If no matching role is defined a priori, the user is left
with the difficult task of (1) attempting to create a new role (leading to
role explosion); (2) being overly restrictive in selecting a “close” role
(reducing system utility and limiting access below what is actually needed);
or (3) selecting a role that is too general, leading to potential breaches
in security or privacy violations. Instead, the proposed approach lies in an
attribute-based solution in which users can create objects, modify the
content, and control the access. It is obvious that a minimal set of
application-dependent corporation policies, to which all users comply, is
needed to avoid anarchy.

**Required skills:** General CSE408x prerequisites, passion for reading and
writing critiques, experience with web developer tools and plugin
development.

====== Privacy preserving constructs for programming languages ======
**Supervisor:** Amir H. Chinaei

Programming languages suffer from the lack of sufficient features that serve
privacy preservation and ensure data security in cyber spaces. Consequently,
many applications that have been developed by these languages are vulnerable
with respect to data security and/or user privacy. For instance, XML, a
popular underlying language for many web based applications, needs
enhancements onto its access control component, XACML, by adding features to
support privacy preservation. Developing extensions for data presentation
formats such as XML, XAML, JSON, etc. to make them more suitable for a
secure and trustworthy cyber space is an ongoing problem. Obviously, any
mechanism to define privacy policies in such documents needs to be supported
by the query languages too. One approach is to study XACML and XQuery and
investigate minimal modifications such that they support ad-hoc attributes
of privacy preservation. To measure feasibility and effectiveness of the
modifications, one may need to develop prototypes to the proposed solutions
and conduct experiments.

**Required skills:** General CSE408x prerequisites, passion for reading and
writing critiques in the areas related to SQL engine and data exchange
formats such as XML and JSON.

====== Building healthcare question answering systems ======
**Supervisor:** Amir H. Chinaei

In this project, the prospective student(s) will get the opportunity to
build question answering systems for healthcare or education applications.
The project involves simpler and more complex tasks: data collection using
open source search engines, data annotation, building machine learning
models, evaluation of the built system, etc. The students will involve in
one or several tasks depending their interests and skills.

**Required skills:** General CSE408x prerequisites, programming (preferably in
Python and Java) to interact with large datasets for experiments and
analyses.

====== Machine learning for real time access control ======
**Supervisor:** Amir H. Chinaei

As artificial intelligence methods continue to improve, so do the
opportunities of their applications on different industries. Finance and
healthcare databases include sensitive data that certain people should
access in a certain time and location. For example, health information (such
vulnerability to certain diseases) are information that only a healthcare
practitioner should access in a given time and location. Consider when a
practitioner needs to access an attribute of a patient during a surgery, or
when an employee tries to access to a particular data remotely, or when
employees change their positions over time in a company. In these and many
situations, granting and revoking data access needs to be updated online and
real time. To this end, there is a demand for intelligent systems for online
and real time access control. In this project, the prospective students will
get the opportunity to apply machine learning techniques on access control
data to learn patterns of users accessing data and to automatically learn
access control rules.

**Required skills:** General CSE408x prerequisites, programming (preferably in
Python and Java), passion for reading and writing critiques in the area of
data security and machine learning.

====== Detecting and Visualizing anomalies in dynamic networks ======
**Supervisor:** Aijun An

In this project, the goal is to detect and visualize anomalies in dynamic graphs. Graphs are powerful tools to model networks and relationships between their entities. Many of the real-world graphs are dynamic in which nodes and edges are being added and deleted over time. Some of the dynamic network examples include social networks and computer networks. Anomalies are any deviation from the normal. For example, in a computer network, communications are normal over time until a single machine is attacked by a large number of other machines at a specific time point. We work on finding time points that an anomaly occurs and nodes, edges or subgraphs that are responsible for this anomalous behavior. This project focuses on finding and visualizing anomalies in a stream of graphs. The student will first use a visualization tool to visualize the network over time. This helps in better understanding the changes in the structure of the network. There are various visualization tools available to use for this purpose. In the second phase, the student will implement a graph anomaly detection method and combine it with the visualzation program so that the graph stream can be monitored through visualization and anomalies can be detected and illustrated in an online fashion. This project is a part of a collaborative project with IBM and the student will work closedly with a PhD student in the project.

**Required skills:** Good programming skills in Python and Java.

**Recommended skills:** Experience with visualization tools is very helpful, Interest in algorithms for graphs.

====== Graphical User Interface for Power System Simulator ======
**Supervisor:** Afshin Rezaei

The project is to develop a user-friendly Graphical User Interface (GUI) for a power system simulator program. Similar to all circuit simulation programs, the GUI should provide a library of the system components. These elements include not only the basic circuit elements such as resistor, capacitor, and inductor but also more complex equipment models such as transformers, generators, etc. The library elements can be dragged and dropped on the design page. The user would be also able to add new elements to the library. Each element has its own dialog box for entering the parameters which is displayed by double-clicking on that element. The elements will be connected by the user. The GUI should provide the common tasks for drawing, removing, grouping, and construction of a circuit. The GUI can write an output data file of the system element parameters and connections and call an available executable program to run. After, the GUI will display the simulation results.

**Required background:** General CSE408x prerequisites, good programming skill, good knowledge of GUI design tools

====== Development of a Standalone Power System Optimization Toolbox ======
**Supervisor:** Afshin Rezaei

Finding the optimum system condition and maximum/minimum of analytical or numerical functions are of fundamental needs and widely used in various fields of Engineering. This project is to develop a standalone optimization toolbox based on Intel Visual FORTRAN for power system applications. FORTRAN language with its highly developed math library is a powerful tool to solve complicated mathematical problems. A group of such mathematical problems are those dealing with the optimization algorithms particularly the curve fitting and global optimization methods such as genetic algorithm. 
In this project, the developer is expected to explore Intel FORTRAN Math Kernel Library (MKL) and Intel Mathematics and Statistics Library (IMSL) and develop a program code in FORTRAN to call built-in functions and perform the requested optimizations specified by the user. Due to compatibility of the MS Visual Studio with both FORTRAN and C++, some parts of the code can also be developed in C++.  

**Required background:** General CSE408x prerequisites, good programming skill, good math skill, good knowledge of Intel FORTRAN and C++


====== Palpation Task Trainer ======

**Supervisors:** Petros Faloutsos (EECS) and Iris Epstein (School of Nursing)

Palpation of head and neck region is an integral part of a complete physical health assessment performed by both physicians (e.g., physician assistant; family doctor; Ear Nose and throat specialist and surgeon) and Nurses (Nurse practitioners, registered nurses). During palpation practitioners use their sense of touch with knowledge of anatomy of the head and neck to feel, differentiate and characterize the masses within their anatomical landmark (e.g.,lymph nodes; fat; size; texture; movements). With increase prevalence of cancer in head and neck early detection and appropriate referral and treatments are paramount. In 2016, George Brown College Capstone Engineering program together with the help of the nursing lab simulation specialist constructed a head and neck normal task trainer (prototype 1) with 32 touch sensors (see image bellow). During a multidiscipline conference in May 2017 we tested the task trainer with over 47 experts’ practitioners (Doctors and Nurses). Two important themes emerged from the survey. First, the need to render the task trainer more realistic (e.g., the touch of the skin and bonny structure). The second, focus on making the task trainer more interactive. The purpose of this project is to create a second prototype with an interactive gaming capabilities during a head to neck palpation.  Perhaps creating an algorithm gaming from simple to complex palpation assessment skills (e.g., to create a game around not only palpating to locate the mass but also to characterizing it.). Possible directions:
1. Head to neck anatomical structure - Making the task trainer more "real" with anatomical / bone/ cartilage/ glands structures. 
2. Head and neck skin - Because we are focusing on palpation touching the skin and making the skin respond to touch is important. 
3. Head to neck engaging and interactive - Several health care providers perform palpation. In fact there is a hierarchy among them (nurse vs doctor; family doctor vs Ear Nose and throat). Creating some kind of interactive game to find and characterize the gland with multidiscipline.

**Required Background:** Standard prerequisites,some knowledge of C++. 

**Other experience:** Knowledge of computer graphics (e.g. EECS3431)  and  familiarity with programming computer games would be useful for the gaming aspect, while familiarity with making and 3D printing  might be useful for developing the prototype system.

**Resources and readings:** Here are two links to articles we published. The reference list has more resources
http://www.ijocs.org/clinical-journal/head-to-neck-task-trainer-to-teach-palpation-skills-back-to-basic-12036.html
http://www.sciedu.ca/journal/index.php/jnep/article/view/11461


====== Custom Camera App using the Andriod Camera 2 API ======


**Supervisor:** Michael S. Brown

Cameras have a number of processing steps that convert the incoming sensor image to the final sRGB-JPEG image.  These steps are collectively referred to as the "camera processing pipeline".  The camera processing pipeline has traditionally been fixed in a camera's onboard hardware. This made changing it difficult to develop a custom camera application. The new Camera 2 API for Android, however, allows developers significant more control over the entire imaging pipeline.

The primary goal of this project is to develop custom camera applications that manipulate individual components of the imaging pipeline (e.g., custom white-balance, custom colour mapping, custom tone-manipulation, etc.).   These applications will all be built on top of the Camera 2 API for Android phones.

**Required Background:** General EECS 408x prerequisites, knowledgeable with photography, experience with Java programming for Android platforms.


====== Ultrasound simulation/trainer ======

**Supervisor:** Burton Ma

Trans-esophageal echocardiography (TEE) is the standard of care for most cardiac surgeries and interventional cardiology procedures. It uses a thin and flexible ultrasound probe that is inserted down the esophagus in position beside the heart, and the echocardiographer adjusts the position and orientation of the probe from outside. For new clinicians, learning how to adjust the probe into the correct location for various views of the heart can be quite challenging.

The primary goal of this project is to develop an open source, inexpensive software simulation for training clinicians in the use of TEE ultrasound. Starting with a 3D-plus-time CT or MRI heart dataset, we will create simulated ultrasound images, and use a mouse to simulate the translation and rotation of the ultrasound probe. The software platform will render the simulated ultrasound, and provide the user with feedback on how well they can identify the standard TEE views. This project will involve a collaboration with clinicians in Toronto and London, Ontario.

**Required Background:** General CSE408x prerequisites,some knowledge of C++, knowledge of computer graphics would be useful (e.g. EECS3431)





====== Data-driven conceptual modeling within on-line communities ======

**Supervisor:** M. Baljko

The wealth of data to be obtained from online communities is already well acknowledged.  This EECS4080 project will investigate techniques for obtaining, analyzing, and visualizing this data in conjunction with a digital humanities research project.   The digital humanities project is seeking to investigate questions about how disability, ableism, and activism is taken up within on-line discourse within certain types of online communities.  The 4080 project will entail, among other tasks, tasks such as: to extend an existing code base that performs web-scraping; to develop scripts and techniques to work with large volumes of data; to analyze scraped data; and to visualize results.  This 4080 project will entail working closely with the supervisor and a doctoral candidate, with weekly meetings.

**Required Background:** General EECS408x prerequisites; strong software design and implementation skills (Java), prior experience with (or willingness to learn) information visualization software (Tableau), an undergraduate course in statistics is preferred


====== Proposed Project: Tangible Interactive Device Design and Evaluation, Assistive Technology ======

**Supervisor:** M. Baljko

The objective of the 'ENAbling MEdia for Literacy' (ENAMEL) research project is to develop and to evaluate the digital technologies that are required by stakeholders.  These technologies tend toward low-cost, DIY variants (such as 3D printing and low-cost single-board computers, such as Raspberry Pi and Arduino) and open source software. These technologies provide innovative and new approaches to supporting the development of functional knowledge in learners (primarily children) concerning printed and written materials.  This project espouses user-centered, rather than technology-centered, design approaches, and seeks to critically reflect on the hidden assumptions, ideologies and values underlying the design of such technologies.   The ENAMEL project is currently supporting two projects.  The first project is focused on supporting learning of early-level Braille by children (in North America).  The second project is focused on capacity building for grass-roots production of Assistive Technology (focused on speech and language supports) for use in Special Education contexts in an East Africa country.
This 4080 project will investigate the design, fabrication, and evaluation techniques for either the Braille project or the Speech/Language Assistive Technology project.  The project will start with an in-depth learning phase so that the student becomes familiar with the current state of this multi-year research project.  The remainder of the project will entail either software or hardware development or conducting a usability study, depending on the both the needs of the project and the learning objectives of the 4080 student.  The student must be able to work effectively in a multi-disciplinary team environment.

**Required Background:** General EECS408x prerequisites; EECS3461; knowledge in at least two of the following knowledge areas: Java, iterative UI design methodologies, tangible interface building (using Raspberry Pi or other single board computers or microcontrollers), 3D modeling (preferably OpenSCAD), assistive technologies, critical disability studies





====== Distributed leader election for simple robots ======

**Supervisors:** Michael Jenkin and Patrick Dymond

**Project:** How should a group of autonomous agents moving within multiple locations choose and maintain a leader to coordinate and control them? Utilizing the concept of an infection algorithm — a process much like the spread of a disease in which agents infect each other with information — it is possible to develop a probabilistic approach to this kind of leader election problem. Solutions to this type of problem finds wide application in distributed computing, and in particular distributed computing of autonomous agents and sensors which must compute information about control structures with limited information about the presence/absence of potential leaders in the environment.

To make this project more specific, and given the limited time available for an undergraduate student project, this project will explore certain properties of leader election algorithms, both with real and simulated groups of robots. Using a simulator, performance bottlenecks in the infection algorithm will be studied, considering cases where direct communication is limited to agents in the same local area. Simulations will be supported using a collection of real devices (Android devices) who can communicate with each other in the local environment using bluetooth and/or WIFI. If time permits, the project will also study possible enhancements of the infection algorithm as well as develop better upper bounds for the problem.

**Required skills:** knowledge of Java or Python. Interest in algorithms for a distributed collection of simple robot agents. Completion of 3rd year courses in computer science or computer engineering.

====== Asynchronicity in infection algorithms ======

**Supervisors:** Michael Jenkin and Patrick Dymond

**Project:** How does changing the model of synchronization changing run time bounds on infection algorithms?

Infection algorithms are a class of algorithms within which individual agents exchange information via infection. That is, the algorithm proceeds by the various agents transmitting (infecting) each other with information. Under an assumption of synchronization — that is, a model in which no two agents can infect each other at precisely the same time — it is possible to derive models of expected time until all agents have been infected. But how does this algorithm adapt when agents can actually infect each other simultaneously? This project will explore this problem. First, a simple simulation algorithm will be implemented to test infection rates when it is assumed that at a given time instant only one infection can occur. This algorithm will then be generalized to a model under which within a given time interval more than one infection can occur. Experimental validation will explore how existing infection algorithms perform under this more realistic model. Simulations will be supported using a collection of real devices (Android devices) who can communicate with each other in the local environment using bluetooth and/or WIFI.

**Required skills:** knowledge of Java or Python. Interest in algorithms for a distributed collection of simple robot agents. Completion of 3rd year courses in computer science or computer engineering.

====== Simultaneous localization and mapping (SLAM) aided by a single unique directional landmark ======

**Supervisors:** Michael Jenkin and Patrick Dymond

**Project:** How can a simple SLAM algorithm be improved if it is known a priori that there exists in the environment a single unique landmark that provides both position and orientation information?

SLAM algorithms have been developed for a large number of different environments, and for relatively straightforward environments such as those found indoors, the problem can in many ways be considered solved. However, current algorithms have in the main concentrated on a general version of the problem in which no a priori information is assumed about the environment. From theoretical results we know that a single directional landmark is sufficient to solve the SLAM problem algorithmically, but can we exploit this result within the traditional probabilistic framework found in SLAM algorithms? Starting with a standard vision-based SLAM algorithm, this project will explore how a single landmark can be used to drive exploration and critically, drive algorithmic loop closure.

**Required skills:** knowledge of Java or Python. Interest in algorithms for robots. Completion of 3rd year courses in computer science or computer engineering.


====== Immersive Virtual Worlds ======


**Supervisor:** Robert Allison

We have a new and unique fully immersive virtual environment at York. The student would develop interactive 3D virtual worlds to study self motion perception and human computer interaction in a virtual world. In particular, working with a senior graduate student or postdoctoral fellow, the successful applicant would model 3D environments, render them in a virtual reality display and develop/implement interaction methods to control and interact with the simulation. Artistic background or skill would be an asset but is not required.

**Required Background:** General EECS408x prerequisites, good programming skills, previous work with computer graphics would be helpful


====== Virtual Walking Devices ======

**Supervisor:** Robert Allison

Simulating effective walking in an immersive virtual environment is challenging. Working with a senior graduate student, the successful applicant would help to develop a circular treadmill interface to support virtual walking metaphors.

**Required Background:** General EECS408x prerequisites, good programming and mechanical skills

====== Adapting a 3D Printer for Paste Extrusion ======

**Supervisor:** James Smith

3D printers are an enabling technology for engineering design. However most low- to medium-end printers can only extrude plastics through a hot-end extrusion system. A local company has developed a nozzle and pump system for pastes that can be integrated with existing printers. A student group is sought to design a mounting bracket for an existing TAZ 4 printer that can be used to augment its ABS extruder with a Discov3ry paste extruder. The bracket is to be printed with the TAZ and the design is to be released publicly to the open-source community. Sample prints, calibration routines and possible modifications to the printer's software may be required. Experience with programming and hardware are important prerequisites.

**Required Background:** General CSE408x prerequisites

====== Peer-to-Peer agent based applications in smart power grids ======

**Supervisor:** Hany Farag

Multi-agent systems have been mentioned recently as a potential technology for several operational control objectives in smart power grids. The multi-agents technology allows the rapid and detailed creation of a system model and creates a robust framework for distributed control. The distributed control structure consists of components called control agents. These control agents try, through communication and negotiation with other control agents, to: 1) determine the current state of the system and/or subsystems and 2) make decisions (set their local actuators or communicate with other agents) in such a way that their own objectives are met as closely as possible and any constraints are satisfied.

This project aims to implement formulated distributed constraint optimization (DCOP) in a multi-agent platform for two objectives in smart grids: 1) voltage regulation and 2) electricity market,. There are several Java-based open source platforms for peer-to-peer agent based applications e.g. (JADE, Jadex, Jason,..etc). With the help of the supervisor, the student will choose the platform that suits the required applications. Also, the student will implement the formulated DCOP in the suitable multi-agent platform to test its effectiveness and robustness. Toward that end, an interface between the multi-agent platform in Java environment and the power grid simulator in MATLAB environment is required to transfer the measurements from MATLAB to the multi-agent platform and then transfer the actions from the multi-agent platform to MATLAB in real-time.

The student should be a strong Java and MATLAB programmer. He should have prior knowledge about multi-agent platforms such as JADE. The work involves reading and understanding the formulated DCOP in smart grids and working with the supervisor and master/PhD student(s) to implement the developed algorithms and to measure the performance of the developed algorithm(s) in the multi-agent platform.

**Required Background:** General CSE408x prerequisites


====== Clustering High-Dimensional Data Sets ======

**Supervisor:** Suprakash Datta

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.

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.

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).

For more information, please send email to datta@cse.yorku.ca.

**Required Background:** General EECS408x prerequisites


====== Metaheuristic-based Optimization techniques ======

**Supervisor:** Suprakash Datta

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.

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).

**Required Background:** General CSE408x prerequisites


====== Genome-wide identification of plant micro RNAs ======

**Supervisor:** Katalin Hudak

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, 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

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.


====== DDoS Attack using Google-bots ======


**Supervisor:** Natalija Vlajic

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.

**Recommended Background**: EECS 3213 or EECS 3214, EECS 3482


====== Attentive Sensing for Better Two-Way Communication in Remote Learning Environments ======

**Supervisor:** James Elder

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

**Required Background:** General CSE408x prerequisites, good programming skills, good math skills, knowledge of C and MATLAB programming languages

====== Attentive Sensing for Sport Video Recording Markets ======

**Supervisor**: James Elder

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: 1. Ground-truth available datasets 2. Evaluate current attentive algorithms on these datasets 3. Modify these algorithms to improve performance on these datasets.

**Required Background:** Good programming skills; Good math skills; Knowledge of C and MATLAB programming languages

====== JPF in a Jar ======

**Supervisor:** Franck van Breugel

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.

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.

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.

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.

In this project you may collaborate with graduate students 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.

**Required Background:** General CSE408x prerequisites 

====== Model-based Design and Development of Embedded Systems with Code Generation Tools ======

**Supervisor:** Jia Xu

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.

**Required Background:** At least a B+ in Embedded Systems (EECS 3215), MATLAB, C programming skills, solid experience in using a microcontroller such as Arduino.

====== C2000 Concerto Microcontrollers ======

**Supervisor:** Jia Xu


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.

**Required Background:** At least a B+ in Embedded Systems (EECS3215), strong C programming skills, solid knowledge of microcontrollers

====== Real-Time Bidding Platform ======


**Supervisor:** Jia Xu

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).

**Required Background:** At least a B+ in Operating System Fundamentals (EECS3221), strong Ubuntu/Linux, C++ programming, GCC, TCP/IP skills


====== Circuit and Board Design for a Pulsed Ground Penetrating Radar ======


**Supervisor:** Sebastian Magierowski

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.

**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.



====== Tilt Target Selection on Touchscreen Phones ======


**Supervisor:** Scott MacKenzie

Touchscreen mobile devices commonly use a built-in accelerometer to sense movement or tilting actions of the device. Tilt is commonly used the change the orientation of the display between portrait and landscape. Gaming is another common use for tilting actions. However, tilt may also be used for target selection, as a replacement for touch. This research project will evaluate tilt as an input primitive for target selection on touchscreen mobile devices.

Readings: MacKenzie, I. S., & Teather, R. J. (2012). FittsTilt: The application of Fitts’ law to tilt-based interaction. Proceedings of the Seventh Nordic Conference on Human-Computer Interaction – NordiCHI 2012, pp. 568-577. New York: ACM.

**Required Background:** General 4080 prerequisites, EECS 3461, and (preferably) EECS 4441. Interest in user interfaces and human-computer interaction (HCI). Students can use their own Android phone for the project or one supplied by the course supervisor.

====== Enabling SaaS access to an experimental AI planner ======

**Supervisor:** Sotirios Liaskos 

This project involves enriching and integrating a set of fairly complex scripts, which are components of an Artificial Intelligence (AI) planner, and exporting them to the public in a Software-as-a-Service (SaaS) fashion.

The components are various Unix executables and LISP programs that need to interact in complex ways. The components may be residing in different servers in different universities. Currently integration is performed manually, at the expense of usability. Thus, we aim at constructing a module that: (a) integrates involved components to deliver output in one call, (b) exports a unique web interface (preferably following WSDL/SOAP) to be easily accessed by custom front-end tools by anyone, anywhere, (c ) offers a simple front-end for human users.


**Required Background:** Good knowledge of Unix tools / Python, Perl or Awk. Comfort with algorithms and programming. Essential: 2031 – Software Tools. Desired: 3402 – Functional & Logic Programming, 3101 – Design and Analysis of Algorithms, 4302 – Compilers and Interpreters.


====== Predicting Angular Error in Rigid Registration ======


**Supervisor:** Burton Ma

Registration is a fundamental step in image-based surgical navigation. Several (seemingly) different approaches for predicting distance errors in registration are known, but for some surgical procedures, the angular error in registration is more important. This project will validate an approach for predicting angular error in registration; the student will use a combination of simulated and actual registration data for testing purposes.

====== Calibration of a Tracked Pointer ======

**Supervisor:** Burton Ma

Description: Tracked pointers are the most common tools used in surgical navigation systems. A typical pointer has a tracked target on one end and a sharp or ball tip on the other end. Finding the location of the tip relative to the target is a calibration problem. One solution to the calibration problem involves pivoting the pointer about the tip while tracking the target; if the tip is kept stationary, then the target moves on the surface of a sphere. Fitting the tracking data to the surface of a sphere yields the location of the tip as the sphere center. Unfortunately, the calibrated tip position obtained using such a spherical calibration has high variance. This project will investigate how much variance there is in the calibrated tip position, and methods for reducing the variance of the calibrated tip position.

====== Simulation for Forest Fire Detection ======

**Supervisor:** Rob Allison

Detection of forest fires is a challenging activity that requires considerable training. The objective of this project is to implement a virtual reality simulation to incorporate key aspects of this task and then to perform an evaluation with a small user study.


**Required Background:** General EECS408x prerequisites

**Recommended Background:** EECS3431 or EECS4471 or equivalent

====== Study of self-motion perception in microgravity ======


**Supervisor:** Rob Allison

This is a computer graphics project to present visual motion stimuli to an observer. The software will experimentally control scene content, collect user responses and control the camera trajectory to simulate the desired self-motion profile.

**Required Background:** General EECS408x prerequisites

**Recommended Background:** EECS3431 or EECS4471 or equivalent

====== Stereoscopic cinema calculator ======

**Supervisor:** Rob Allison

Directors of three-dimensional movies sometimes use 'stereo calculators' to compute the simulated depth of objects in the film show to the viewer in order to maximize the stereoscopic effects and maintain comfortable viewing. However current calculators have limited ability to visualize the results of the calculations. This project will combine stereo calculations with visualization software to assist the director in artistic and technical decisions.

**Required Background:** General EECS408x prerequisites

**Recommended Background:** EECS3431 or EECS4471 or equivalent

====== Computer pointing devices and the speed-accuracy tradeoff ======

**Supervisor:** Scott MacKenzie

**Required Background:** General 4080 prerequisites, EECS3461, and (preferably) EECS4441

**Recommended Background:** Interest in user interfaces and human-computer interaction (HCI). Understanding of experiment design. Experience in doing user studies.

====== One key text entry ======


**Supervisor:** Scott MacKenzie

**Required Background:** General 4080 prerequisites, EECS3461, and (preferably) EECS4441

Recommended Background: Interest in user interfaces and human-computer interaction (HCI). Understanding of experiment design. Experience in doing user studies.

====== The Algorithmics Animation Workshop ======


**Supervisor:** Andy Mirzaian

The URL for Algorithmics Animation Workshop (AAW) is http://www.cs.yorku.ca/~aaw. The main purpose of AAW is to be a pedagogical tool by providing animation of important algorithms and data structures in computer science, especially those studied in courses CSE 3101, 4101, 5101, 6114, 6111. This is an open ended project in the sense that more animations can be added to this site over time.

**Required background:** General prerequisites

**Recommended background:** EECS 3101


====== Automated Reasoning System for Quantified Propositional Logic ======


**Supervisor:** Zbigniew Stachniak

Quantified Propositional Logics (QPL) plays an important role in a number of computer science disciplines from the theoretical computer science to knowledge representation and verification. There are also a number of open problems concerning this logic, and formulated more than 70 years ago, that can be finally solved (or at least approached) using automated reasoning techniques. The first step in such investigations has to be the design and implementation of a theorem prover, or automated reasoning system, for QPL. Such a system should, in principle, be able to determine whether or not a given formula of QPL is a theorem (or a tautology) in this logic.

The theorem prover for QPL is to be designed, implemented, and fully tested.

Background: Various variants of QPL have been formally formulated for the first time in the 1920s by a number of logicians and mathematicians. In modern computer science, QPL plays a significant role in theoretical computer science (proof complexity, satisfiability) as well as in verification and AI.

**Required background:** General prerequisites

**Recommended background:** Passion for programming and experimentation; Some knowledge of propositional and predicate logic

====== NABU Network Emulator ======

**Supervisor:** Zbigniew Stachniak

Have you ever considered writing your own emulator of an interesting system? There has been a substantial activity in building software emulators of historically significant computers, game consoles, and, recently, smart communication devices. As a result, there is at least one emulator of almost every significant system. This activity contributes, in the first place, to the preservation and dissemination of significant hardware and software technologies. It also allows for cost-effective development of contemporary software and hardware. The project's objective is to design and implement an emulator of the NABU Network – one of the earliest “proto-Internet” networks. The emulator is to be implemented in Java.

Background : The NABU Network was designed and implemented by a Canadian company NABU Manufacturing between 1981 and 1983. The underlying idea behind the network was to link home personal computers to cable television networks which would supply a continuous, high speed stream of computer programs and information (at the rate of 6.5 Mbits per second) to almost an unlimited number of users. Cable television was a uniquely ideal technology for NABU to deliver software and data to home computers because of its high bandwidth and networking capabilities. After the official launch on Ottawa Cablevision in October of 1983, the NABU Network was introduced by Ottawa's Skyline Cablevision in 1984 and a year later in Sowa, Japan, via a collaboration between NABU and ASCII Corp. NABU Network subscribers could rent or buy a NABU PC and dedicated network adaptor, and use an ordinary television set as a display monitor. Once connected to the network, a user could choose from various application programs and services in categories including entertainment, information and guides, education, and professional programs. Dedicated NABU magazines, newsletters, programming guides, and user groups provided subscribers with supplementary information and support. To learn more, visit here.

**Required background:** General prerequisites

**Recommended background:** Java (including 2D graphics); Some knowledge of PC hardware architecture; Some knowledge of (any) assembler language is an asset.

*/