Undergraduate Research Opportunities Conference

October 2-4, 2015

Experience the Life of a Graduate Student in 3 Days

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Are you curious about Computer Science research, but not sure where to start?

UROC is a 3-Day, invitation-only, fully funded research workshop at University of Waterloo for top undergraduate students in Canada.


Mini Projects

Groups of students will work with a professor to tackle a mini-research problem, from brainstorming ideas, prototyping, running experiments and presenting results.

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Mixers & Panels

Q&A sessions and social events where current graduate students will answer questions about life as junior researchers, their experience applying to graduate school, etc.

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Research Samplers

Not sure what you are interested in? Explore new research topics by attending presentations from each of the 17 research groups at University of Waterloo.

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Share Your Passion

Are you already involved in an undergraduate research project? Do you have secret side projects? There will be sessions to showcase your current work.

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Preliminary Schedule

Here is a sneak peak at our exciting program

Day 1

08:00-09:00am | Registration and Breakfast

10:00-11:00am | Mini-Project Session I

11:00-12:30pm | Faculty & Industry Panel

12:30-01:30pm | Lunch

01:30-03:00pm | Lab Tours

01:00-02:00pm | Mini-Project Session II

05:00-07:00pm | Dinner + Social

Day 2

08:00-09:00am | Registration and Breakfast

09:00-11:00am | Mini-Project Session III

11:00-12:30am | Graduate Student Panel

12:30-02:00pm | Lunch

02:00-07:00pm | Mini-Project Session IV and V

07:00-08:00pm | Dinner + Social

Day 3

08:00-09:00am | Registration and Breakfast

09:00-12:30pm | Project Presentations

12:30pm | Depart

Faculty Panel

Verna Friesen
Engineering Manager

Link to personal website:   Verna Friesen

University of Waterloo
MMath, Computer Science
University of Saskatchewan
BSc, Computational Science

Michael Terry
Associate Professor
University of Waterloo

Link to personal website:   Michael Terry

Georgia Institute of Technology
Doctoral of Science
Florida Institute of Technology
Master of Science
Cornell University
Bachelor of Science

Kate Larson
Associate Professor
University of Waterloo

Link to personal website:   Kate Larson

Carnegie Mellon University
PhD, Computer Science
Memorial University of Newfoundland
BMath, Mathematics

Student Panel

Jeff Avery
PhD, Computer Science

Research Group

Human Computer Interaction (HCI)

Xu Chu
PhD, Computer Science

Research Group

Database Group

Anatasia Kuziminykh
MMath, Computer Science

Research Group

Human Computer Interaction (HCI)
Computer-Assisted Language Learning

Cecylia Bocovich
PhD, Computer Science

Research Group

Cryptography, Security, and Privacy (CrySP)
Centre for Applied Cryptographic Research

Irish Medina
MMath, Computer Science

Research Group

Machine Learning

Mini Projects

Incentive Mechanisms in Crowdsourcing
Project Leader: Prof. Edith Law

Human Computation (a.k.a. crowdsourcing) is the idea of combining human and machine intelligence on the Web to help tackle difficult problems that algorithms cannot yet solved. Examples of crowdsourcing includes ReCaptcha which helps digitize books, commercial crowdsourcing platforms such as Amazon Mechanical Turk, and systems for solving scientific puzzles such as FoldIt and Zooniverse.

A major problem in crowdsourcing is incentives -- how can we design user interfaces and reward systems to incentivize participation, especially when people are volunteers, participating out of their own intrinsic motivation? X-with-a-Purpose systems engage participants to perform tasks as a by-product of another activity they are intrinsically motivated to do. Games with a Purpose is a prime example, where game players generate useful annotations as a by-product of playing a casual game. Research goes into making these games both fun and spammer-prove - two important but often conflicitng objectives. In this mini-research project, we will design, prototype and test a variety of incentive mechanisms for volunteer-based crowdsourcing.

The Wonders of Biology
Project Leader: Prof. Bin Ma

DNA and proteins are important molecules that determine or affect many things about an organism. These include properties that are easy to observe, such as the gender and color; and properties that are harder to observe, such as the strength, IQ, and health. The new abilities to measure the hard-to-observe properties, such as an underdeveloped disease, have much greater impacts to improve the living conditions of the mankind. Modern biology and health research rely on advanced instruments to measure the DNA and proteins molecules in a biological system, and produce huge amount of data. Bioinformatics tries to manage, visualize and analyze these large datasets, and computes the answer to the biologists questions. In this mini-research project, a particular measurement, the mass spectrometry, is examined. Mass spectrometry measures the mass (molecular weights) of the peptides in a carefully prepared biological sample. A visualization software tool will be developed to visualize the signals in the data, and associate the signal in the data to peptides in a protein database.

The Complexity of Circuits
Project leader: Prof. Eric Blais

The goal of complexity theory is to determine the fundamental limitations of computers and algorithms or, in other words, to establish the minimal resources (in terms of time, disk space, network communication, etc.) that are required to solve various computational problems. One area in complexity theory that has led to surprising results and baffling open problems is circuit complexity. A circuit is a collection of AND, OR, and NOT gates that take in some Boolean (0 or 1) values and returns a single Boolean value as output. What are the functions that require large circuits to compute? This deceptively simple question has important ramifications---a complete answer to the question could give a proof of the famous P vs. NP problem---but it has also proved to be incredibly elusive. In this mini-project, we will explore some of the open questions in circuit complexity that follow from this central question. We will prove and conjecture, and in the process catch a glimpse of how research in theoretical computer science is conducted.

Dirty Data
Project Leaders: Prof. Ihab Kaldas

Dirty data is everywhere. Entry errors, integration from multiple sources, and imperfection of automatic data acquisition techniques are examples of the causes of low-quality data. In the Big Data era, extracting the value of the massive amounts of collected data is crucial in fuelling meaningful analytics and effective business intelligence. Large body of research is in the area of detecting data anomalies and data inconsistencies, and even more approaches are proposed to automatically repair the data. However, it is unclear how to verify the correctness or soundness of dirty databases without reaching out to the main digital sources where this data was born. In this project, we try to use available corpora from text, social media, news and other external sources (mostly unstructured) to support the facts (or errors) in the collected data sets. The project explores using techniques from information retrieval, natural language processing, statistics and probability theory, with a judicious involvment of users and experts to verify and repair low-quality data sets.

I'm ready to Apply!

UROC is open to all undergraduate students in Canada, and is fully funded (i.e., we pay for travel, lodging and meals). To be eligible, you must be in the third or fourth year of your program, and open to the possibility of pursuing graduate studies in Computer Science. To apply, please submit a pdf containing the following materials to uroc@uwaterloo.ca:

  • resume (2 pages)

  • transcript

  • a personal statement, answering all three of the following questions:

    (a) describe one topic in computer science that you are fascinated by, and explain why (250 words max).

    (b) describe one thing in life, unrelated to computer science, that you are passionate about. Explain why (250 words max).

    (c) if you have the power to turn anything into a computer (i.e., by adding computational or information processing capabilities), what would that be and why? (250 words max)

  • name and email address of at least one reference, preferably a professor or former supervisor from the industry who can comment on your academic achievements, creativity, leadership and personal attributes.

For full consideration, please send your application by July 31, 2015. Academic excellence is important, but we also highly value creativity, leadership, dedication and diversity. A small group of students will be selected based on a mix of criteria that indicate potential in pursuing academic research in Computer Science.

Applications are now closed

Accepted Students

Aaron Lam| University of Toronto
Aaron Peddle| University of Manitoba
Aayush Rajasekaran | University of Waterloo
Adrian Cheung | University of Waterloo
Ahmad Shikib Mehri | University of British Columbia
Albert Cui | University of Toronto
Alexander Purdy | University of Victoria
Amna Liaqat | Simon Fraser University
Athabasca Witschi | University of Victoria
Blaine Lewis | University of Alberta
Brandon Fuller | University of Lethbridge
Brittany Postnikoff | University of Manitoba
Cameron Seth | University of Waterloo
Carl Kwan | University of British Columbia
Clarice Ng | University of Waterloo
Darrell Aucoin | University of Waterloo
Eddie Santos | University of Alberta
Edward Smith | McGill University
Emily Chen | University of British Columbia
Frank (Hexiang) Hu | Simon Fraser University
Irene Chen | University of British Columbia
Jane Henderson | Mount Allison University
Josh Bradshaw | University of Waterloo
Karoliina Oksanen | Memorial University of Newfoundland
Mark Sadowski | University of Manitoba
Marko Ilievski Krysti | University of Lethbridge
Matthew Fritze | University of Alberta
Matthew Teoh | Simon Fraser University
Micah Stairs | Mount Allison University
Michael (Zhucheng) Tu | University of Waterloo
Nik Klassen | University of Waterloo
Paul He | University of Waterloo
Qian Xin | University of Waterloo
Ricky Rong | University of Waterloo
Sally Dong | University of Waterloo
Sarah Yeo | University of British Columbia
Sean Davis | University of Alberta
Sean Harrap | University of Waterloo
Simon (Shun da) Suo | University of Waterloo
Taylor Lloyd | University of Alberta
Theo Belaire | University of Waterloo
Tiasa Mondol | University of Waterloo
Tommy Tran | University of Waterloo
Vaastav Anand | University of British Columbia
Vanessa Reimer | University of Manitoba
Vincent (Wenxuan) Zhao | Acadia University
William Fiset | University of British Columbia