Education

Name: Soon Chee Loong

Email: cheeloong.soonatmaildotutorontodotca

Undergraduate: Bachelor of Applied Science (BASc) Computer Engineering 2017

Graduate: Masters of Applied Science (MASc) Industrial Engineering 2019

About

I enjoy working with applied math and code.

My career focuses on Applied Machine Learning and Distributed Systems.

Graduate (Masters)

I was a MASc (Masters of Applied Science, research-based) student at the University of Toronto.

I was a member of the Data Driven Decision Making Laboratory.

My research focused on Deep Graph Embeddings in Recommender Systems.

Undergraduate

During my undergraduate, I have done Software Engineering Internships at Google, Salesforce, Intel.

Published a paper under the supervision of Professor Christopher Beck.

Final year research group capstone project under the supervision of Professor Raquel Urtasun.

More information on my projects in undergraduate here

Research Interest

• Statement Of Purpose Fall 2016

I am curious about our intelligent ability to learn.

Artificial Intelligence Branches:

• Machine Learning: How do machines learn?
• Natural Language Processing: How do machines read?
• Computer Vision: How do machines see? (2D -> Computer Vision -> 3D)
• Computer Graphics: How do machines imagine? Inverse of Computer Vision (opposite of seeing) (3D -> Computer Graphics -> 2D)
• Speech Processing: How do machines hear?
• Robotics: How do machines move? How do machines localize itself to know where it is in the world?
• Evolutionary Intelligence: Natural Selection of machines
• Swarm Intelligence: How do machines learn as a society of groups?
• Constraint Satisfaction Problem: How do machines plan? (Assuming it already learns everything from the world, how does it intelligently reasons and makes decisions)
• Knowledge Representation: How do machines represent knowledge and logically reason from it?

Conferences

Full Papers

• Noise Contrastive Estimation for One-Class Collaborative Filtering. Wu, G.; Volkovs, M.; Soon, C. L.; Sanner, S.; and Rai, H. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-19), Paris, France, 2019 [pdf] (84/426, 20% acceptance, ORAL)

Journals

• Loong, S.C., Ku, W.Y. and Beck, J.C., 2016. ℚ-bounds consistency for the spread constraint with variable mean. Constraints, 21(4), pp.646-652. [pdf]

Thesis

• Deep Graph Embeddings in Recommender Systems. [pdf]

Talks

• UTMIST Academic Talk Series 2018: Recommender Systems: Motivations, Challenges and Seminal Works
• MASc Thesis Defense Presentation: Deep Graph Embeddings in Recommender Systems

Teaching Assistant

Awarded $500 for MIE Teaching Assistant Award for the 2017-2018 academic year.

Median Rating: 5.0/5.0 (60 anonymous student surveys) => Mode Rating = 5.0

• CSC418 Winter 2019: Computer Graphics
• CSC258 Fall 2018: Computer Organization
• CSC263 Summer 2018: Data Structures and Analysis
• CSC207 Fall 2017 - Winter 2018: Software Design
• MIE250 Fall 2017: Fundamentals of Object Oriented Programming

Software Engineer

• Amazon Web Services
  • Distributed Systems (Java)

Associate Researcher

• Huawei
  • Computer Vision (C++, Python, Java)

Teaching Assistant

• University of Toronto
  • Computer Graphics (C++)
  • Computer Organization (Verilog)
  • Data Structures and Analysis (Math)
  • Software Design and Object Oriented Programming (Java)

Software Engineering Intern

• Google
  • Concurrency (C++)
• Salesforce
  • Distributed Systems (Java)
• Intel
  • Web Programming (Python)

• Curriculum Vitae

• Resume