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Sicong Huang

Research Intern, Vector Institute and Borealis AI

Founder, Former President, and Scientific Advisor, UTMIST

Undergrad, U of T

Google Scholar

About Me

I recently finished my third year of undergrad at University of Toronto and currently on a year of machine learning research internship at Vector Institute and Borealis AI where I am extremely fortunate to work with Roger Grosse, Sageev Oore, Alireza Makhzani and Yanshuai Cao. I spent my first two years at U of T in Engineering Science and after that I switched to study computer science, cognitive science, statistics and mathematics and started to work on machine learning research projects with Vector and Borealis. I'm interested in anything related to machine leanring, but currently mainly dabbling in information theory, generative models, network compression, reinforcement learning, optimization and cognitive science. In my free time, I'm excited about sharing my thoughts and knowledge and discussing interesting ideas. I started a machine learning student organization called UTMIST and I'm involved with, and I also TA'ed undergrad calculus and linear algebra where I tried to explain backprop in my tutorial to first year students. If you want to chat about anything with me, feel free to shoot me an email through the contact me section.

Publications and Preprints

Unsupervised Cipher Cracking Using Discrete GANs

Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser

This work details CipherGAN, an architecture for inferring the underlying cipher mapping given banks of unpaired ciphertext and plaintext. We demonstrate that CipherGAN is capable of cracking language data enciphered using shift and Vigenere ciphers and we prove that the technique used in CipherGAN avoids the common problem of uninformative discrimination associated with GANs applied to discrete data.

Published as a conference paper in ICLR2018

TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer

Sicong Huang, Qiyang Li, Cem Anil, Xuchan Bao, Sageev Oore, Roger B. Grosse

We introduce TimbreTron, a method for high quality musical timbre transfer, where the goal is to manipulate the timbre of a sound sample from one instrument to match another instrument while preserving other musical content.

Published as a conference paper in ICLR2019
Project Page , Preprint

News & Media

UofT News: Cracking the code: This group of U of T computer science researchers are decoding ciphers with AI

"Today, a group of University of Toronto undergraduate computer science students are decoding encrypted text using a neural network, a framework for machine learning algorithms inspired by the brain...." Read more

Work Experience Chronologically

Borealis AI(RBC Institute for Research)

Research Intern (part time)

Working with Yanshuai Cao on machine learning research projects.

Professor Roger Grosse, Vector Institute/Machine Leaerning Group, U of T.

Research Intern

Working with Roger Grosse, Sageev Oore and Alireza Makhzani.

Department of Mathematics, U of T

Teaching Assistant

Held a Teaching Assistantship in a course in calculus(MAT135) during the summer of my second year and a teaching assistantship for a course in linear algebra(MAT223) during 2017 fall.

Professor Li Qian, Department of ECE, U of T

Research Intern

Worked with Professor Qian Li and Dr. Yi Liu on a research project of mathematical modelling of Brillouin amplification in elliptical core spun fiber at the Ultrafast Photonics Laboratory at the University of Toronto.


University of Toronto

Sept 2017 - Sept 2020

Bachelor of Science in Computer Science, Cognitive Ccience and Statistics, Year 3&4

Vector Institute and Borealis AI

May 2018 - April 2019

Machine Learning Research Intern, Professional Experience Year(PEY)

University of Toronto

Sept 2015 - Sept 2017

Bachelor of Applied Science in Engineering Science, Year 1&2

Get in Touch vie below or via email: huang_at_cs_toronto_edu