| Department of
The Department of Computer
Science is located at The Centre for Computing and Engineering - 245
Church Street. Moriyama & Teshima designed the new Centre for Computing
and Engineering on the urban campus of Ryerson University in the heart
of downtown Toronto, Canada. The building features a sculptural treatment
of the Church Street facade that dramatically changes throughout the
day as the sun and ambient light varies. At times reflective and at
time transparent, the building is a distinctive symbol of Ryerson.
The facility brings together a number of departments including Aerospace,
Civil Engineering, Computing Science and Electrical and Computing Engineering.
Design started in February 2002 and the facility opened to students
in the fall term of 2004.
Science News & Announcements
Intercollegiate Programming Competition (ICPC) team placed 26th out of 130 Team
Thu, 05 Nov 2015
Talk: Compact Discrete Representations for Scalable Similarity Search
Our Intercollegiate Programming Competition (ICPC) team placed 26th out of 130 teams in Windsor on Saturday, October 31, 2015!
Dr. Woungang drove our ICPC team (RyersO(n): Dante Camarena, Zachary Harris and Matthew Stewart) to Windsor for the East Central North American Regional competition. Matthew, Zach and Dante together solved 3 of 9 problems, placing 26th overall. You can see the scores for all the teams
at the following link: https://ecna15.kattis.com/standings
Notably, among Canadian schools, RyersO(n) placed ahead of teams from McMaster U. (all 4 teams),
York U. (both teams), and
Brock U. (both teams),
while behind teams from
U. of Waterloo (all 4 teams), U. of Toronto (2 of the 3 teams), and
Western U. (1 of its 2 teams).
This is an excellent result, considering the many universities competing from East Central Canada and United States. Congratulations to Zach, Dante and Matthew! Thanks to Isaac for his time and support of the team!
Thu, 05 Nov 2015
Talk: Efficient 3D Molecular Structure Estimation with Electron Cryomicroscopy
Speaker: Mohammad Norouzi (University of Toronto)
Date: November 19th, 2015.
Abstract: Scalable similarity search on images, documents, and user activities benefits generic search, data visualization, and recommendation systems. This talk concerns the design of algorithms and machine learning tools for faster and more accurate similarity search. The proposed techniques advocate the use of discrete codes for representing the similarity structure of data in a compact way. In particular, I will discuss how one can learn to map high-dimensional data onto binary codes with a metric learning approach. Then, I will describe a simple algorithm for fast exact nearest neighbor search in Hamming distance, which exhibits sub-linear query time performance. Going beyond binary codes, I will highlight a compositional generalization of k-means clustering which maps data points onto integer codes with storage and search costs that grow sub-linearly in the number of cluster centers. This representation improves upon binary codes, and provides an even more precise approximation of Euclidean distance. Experimental results are reported on multiple datasets including a dataset of SIFT descriptors with 1B entries.
Biography: Mohammad Norouzi is a PhD candidate in computer science at the University of Toronto. His research lies at the intersection of machine learning and computer vision. He is a recipient of a Google US/Canada PhD fellowship in machine learning. He is going to join Google as a research scientist in January 2016.
Thu, 05 Nov 2015
Ready, willing and able to work thanks to co-op experience
Speaker: Marcus Brubaker, Ph.D. (University of Toronto)
Date: November 12th, 2015.
Abstract: Discovering the 3D structure of molecules such as proteins and viruses is a fundamental research problem in biology and medicine. Electron Cryomicroscopy (Cryo-EM) is a promising vision-based technique for structure estimation which attempts to reconstruct 3D structures from 2D images. This talk reviews the computational problems in Cryo-EM which are closely related to classical vision problems such as object detection, multiview reconstruction and computed tomography. Finally, a framework is introduced for reconstruction of 3D molecular structure which exploits modern methods for stochastic optimization and importance sampling. The result is a method which is efficient, robust to initialization and flexible.
Biography: Marcus Brubaker received his Ph.D. in Computer Science from the University of Toronto in 2011. After that he worked with Raquel Urtasun as a postdoctoral researcher at Toyota Technological Institute at Chicago and is currently a postdoc at University of Toronto, Scarborough. He also consults with Cadre Research Labs on machine learning and computer vision related projects and teaches at the University of Toronto. He was won a number of fellowships and awards, including OGS and NSERC graduate fellowships as well as an NSERC Postdoctoral Fellowship.
His most recent work on autonomous vehicle localization ("Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization," CVPR 2013) and the estimation of the 3D structure of proteins and viruses ("Building Proteins in a Day," CVPR 2015) have won awards and attention in the lay press. His interests span computer vision, machine learning and statistics and he works on a range of problems including video-based human motion estimation, physical models of human motion, Bayesian inference, Markov Chain Monte Carlo methods, ballistic forensics, electron cryo-microscopy and autonomous vehicle localization.
Thu, 24 Sep 2015
Ryerson University student Matthew Tesfaldet says a co-op placement as a software designer will put him ahead of the curve when it comes time to find a job. Story
Computer Science Job Postings
JOB POSTING: Student Developers and Designer Needed
Fri, 11 Sept 2015 JOB POSTING: Software Developer, PhD University Graduate
JOB POSTING: SmartSimple: Jr. Analyst
STUDENT DEVELOPERS AND DESIGNER NEEDED: Want to combine your love of audio with dynamic cloud storage and mobile innovation? We need four GTA-area students to help build an innovative audio application here at Ryerson.
iOS Engineer: 1 position (September-April 12-18 hours per week)
Experience with Object Oriented Programming
Experience developing User Interfaces
Experience interacting with Networking APIs
Senior year undergrad or grad students in computer science
Accessible development experience
Solid knowledge of digital audio fundamentals
Team leadership skills
Demonstrable commitment to project execution
Strong communication skills
Bonus: Swift, iOS, Audio DSP
Server Engineer: 2 positions (September-April 12-18 hours per week)
Experience with Object Oriented Programming
Experience in Database Programming
Solid knowledge of networking fundamentals (HTTP, JSON, REST, Scalability, Security)
Ability to work in a team
Bonus: Node.js, MongoDB, Digital Audio Fundamentals
UI Designer: 1 position (September-December 12-18 hours per week)
Adobe Creative Suite
Experience in accessible design
Senior undergrad or graduate student
Ability to work in a team
Ability to interpret feedback and manage deadlines
Apply with resume, samples of previous work and one academic or professional reference to firstname.lastname@example.org. Students must be enrolled in part-time or full-time post-secondary classes in Toronto.
Tue, 31 Mar 2015
Reports to: Small Project Team Lead
Location: Toronto Canada
Employment Type: Full-time Permanent
Hours: 37.5 per week
Job Grade: TBD
Since 2002, SmartSimple has been providing organizations with an innovative, cloud-based software solution that automates a wide range of administrative processes in multiple vertical markets, including grants, research and claims management. Our system is used by tens of thousands of people every month, working in more than 100 countries around the world. Our company is technologically advanced, culturally diverse and continuously growing with offices in Toronto, New York City and Dublin.
The Jr. Analyst will spend three (3) months in the Small Project Team. As a configuration resource for the Small Project Team (SPT), the Jr. Analyst assists in the execution of small-scale project related work. Under the direct guidance of the Small Project Team Lead and with the mentorship of senior technical staff they will be responsible for platform configuration of client systems. After this time, and the successful completion of two projects, you will be assigned to the pre-implementation or post-implementation team upon completion of the training according to your demonstrated strengths and technical ability. This is a non-client facing, highly technical role.
This position is an ideal entry level role for a recent computer science graduate looking to establish a solid career with a proven Cloud Provider.
Specific Job Responsibilities:
- Work with Small Project Team Lead to review and analyse options within SmartSimple software and determine best way to configure and/or modify software for client systems based on the client Statement of Work (SOW) requirements.
- Collaborate and obtain guidance on the design of client systems from the Business Configuration and Implementation Specialists, Project Managers, or Solutions Architects in the course of work. Get approval for system changes/modifications prior to commencing any configuration work.
- Work in close collaboration with the Project Manager to investigate and help solve client issues. This involves detailed troubleshooting of client systems before escalating issues to the Sr. PM or Development team.
- Review and test configured system functions to ensure adherence to client requests and SOW requirements.
- Assist with performing integrated system testing when new features are applied to a client system.
- Flag and report potential problems or out-of-scope requests from clients to the Project Manager.
Specific Job Requirements:
- Ability to grasp concepts quickly with strong analytical and problem solving skills, and attention to detail.
- Clear, concise and effective communication ability.
- Working knowledge of databases, data modelling concepts and best practices. Ability to read a data model and perform data mapping.
- Experience with application configuration within a project environment for example. Configuration of fields, creation of workflows, tweaking, implementation. Full project lifecycle (conception to production).
- Basic knowledge of 'Software as a Service' solutions (SAAS) and experience of Software Development Lifecycle (SDLC). Ability to work independently and within a team environment to achieve project goals.
For more details, please visit: http://wwww.smartsimple.com/
Taking a stroll down O’Keefe Lane
Wed, 25 Nov 2015
Rams player battles back
Ryerson and Covenant House collaborate on refurbishment of underused campus space... more
Mon, 23 Nov 2015
Community honours Trans Day of Remembrance
Ryerson volleyball player keeps her skills up on and off the court... more
Fri, 20 Nov 2015
Ryerson dancers collaborate with James Kudelka
Ryerson marks Trans Awareness Month with events, memorial... more
Wed, 18 Nov 2015
DMZ-based entrepreneur says 'yes I can'
The famed Canadian choreographer teams up with the Theatre School for 75-minute performance... more
Mon, 16 Nov 2015
$8-million gift from Jack Cockwell and Brookfield Partners Foundation supports innovation
Maayan Ziv’s AccessNow offers crowdsourced database of accessibility... more
Fri, 13 Nov 2015
A space for veterans
In recognition, the new Church Street building will be named Daphne Cockwell Health Sciences Complex in honour of Cockwell’s mother... more
Wed, 11 Nov 2015
The neighbourhood beyond the campus
New campus group aims to provide networking opportunities, emotional support... more
Mon, 09 Nov 2015
University says goodbye to Adam B. Kahan
Ryerson Student Affairs’ Your Neighbour project connects students in residence with charitable community organizations... more
Fri, 06 Nov 2015
When the puck drops, his work begins
Ryerson’s top fundraiser retiring after 12 years... more
Wed, 04 Nov 2015
Alum Bob McKenzie receives Elmer Ferguson Memorial Award for hockey journalism ... more