Full CV (Last updated in Aug 2020) [PDF
New York University - September 2020 – Present
Doctor of Philosophy of Data Science
- Full Scholar
- Data Science Supplementary Fellowship Grant (2020)
University of Guelph - September 2013 – May 2015
Masters of Science in Engineering
- Research: Deep Learning, Unsupervised Learning, Statistical Machine Learning
- Under the advisory of Dr. Graham W. Taylor
University of Toronto - September 2008 – May 2012
Graduated with Distinction, Honors BSc
- Specialist: Computer Science Artificial Intelligence
- 3rd & 4th year GPA: 3.8
- Neural Networks for Machine Learning at University of Toronto in 2012
Geoffrey .E. Hinton
- Machine Learning at Standford University in 2012 Andrew Ng
AIFounded - June 2016 – July 2020
Founder & Chief Executive Officer
- Connecting artificial intelligence and business, creating industry leading AI powered by a search engine.
Licensing search engine to AI industry — providing commercial search engine API allowing users to customize AI agents that retrieve information. Top machine learning labs have conducted research and published papers using AIFounded search engine — with academic research successfully transferred over to development.
- Top machine learning lab partnerships include: New York University, University of Montreal (MILA), and York University.
- Participating in M&A process and leading due diligence efforts for clients.
- Sold AIFounded IP
- Major AI clients include: Chatter Research, Clearview AI, and SecondLifeBook.
Janelia Research Campus, Branson Lab - March 2016 – July 2020
- Researcher under the advisory of Dr. Kristin Branson — a world-renowned expert in computational biology, focused on the application of machine vision and learning to the problems of automatic animal tracking, supervised behavior detection, and unsupervised behavior mining.
- Neuroscience Research: collaborating on animal social behaviors and their neural activities with top neuroscientists in the world.
- Machine Rearning Research: Interactive & Active Metric Learning, Stochastic Optimization Methods
Coinscious - Jan 2018 – October 2019
Co-Founder & Chief Technology Officer
- Conscious Network publically listed in Biki Exchange (IEO).
- Created Conscious Terminal which is known as Bloomberg terminal for cryptocurrency market.
- Developed all product and services, such as alert, report, and backtesting systems. Performed data analysis, technical analysis, and machine learning solutions for crypto market. Lead the customized solutions to major hedge funds like 3iQ
- Provided operational planning, legal, and administrative support. Put together the advisory board teams.
University of Montreal, MILA machine learning institute - April 2015 – March 2016
- Under the advisory of Dr. Roland Memisevic
- Primary research: deep generative models — including auto-encoders, variational auto-encoders, and GANs
University of Guelph, School of Engineering - Sept. 2012 – June 2015
- Worked with Dr. Graham Taylor on the Hyperspectral image classification via semi-supervised learning
- Primary research: dynamic system based deep learning algorithms, such as theoretical results on gated auto-encoder under the gradient field, and persistent minimum probability learning for Restricted Boltzmann Machines.
- Secondary research: distance metric learning that optimizes the soft form of Naïve Bayes Nearest Neighbor selection.
- Application project: semi-supervised neural network on hyper-spectral image.
Sightline Innovation Inc. - Nov. 2012 – Aug. 2013
Research and Development Specialist
- Designed and implemented the backend component of VtiS System
- Job match scoring sytem using Hadoop
University of Toronto, Dept. of Computer Science - Sept. 2012 – Nov. 2012
- Researched on computational and constructional approaches to the semi-productivity of light verb construction (LVC) formation
- Representing meaningful representation of multi-words expression in feature vectors
- Using various machin elearning methods to experimento nclassifying LVCs and examine which
features play an essential role on defining LVC
Air Canada Business Intelligence - May 2009 – Sept. 2009
Data Analyst (Intern)
- Designed and built automated reports for the Airports Branches
- Utilized Business Intelligence tools, such as Microsoft Reporting Services(SSRS),OLAP
cube(SSAS), and ETL (SSIS) using SQL server database, to perform data mining and to recognize trends
- Solved various T-SQL and oracle based process
- Data extraction for complex XML structures
NeurIPS workshop, TNNLS 2019
Neural Computation, TNNLS 2018
NECO 2017, TNNLS 2017
NIPS 2016, GRSL 2016
- PRO: Designing and Developing Windows-based Applications by using the
Microsoft .NET Framework - 2009
- Python, MATLAB, C++, Java, Bash, C, HTML, CSS, SQL, Prolog, LATEX
- VIM, Eclipse, Xcode, Git, gdb, make, Linux system administration