Personal Information
Organization / Workplace
Washington D.C. Metro Area, MD United States
Occupation
Applied Quantitative Researcher
Industry
Government / Military
Website
github.com/stephenhky
About
Kwan-Yuet (Stephen) Ho, Ph.D. is an applied quantitative researcher with 8-year experience in machine learning, text mining, and other related data science and quantitative fields. He possesses exceptional mathematical abilities, and experience with software development. He is seeking to advance his careers in machine learning, data science and quantitative analytics.
Tags
physics
machine learning
theoretical physics
helimagnets
technology
sunday school
numbers
priest
moses
bible
pentateuch
traffic flow
text analytics
data mining
statistical physics
optimization
a phase
nematics
skyrmion
liquid crystal
choletorics
columnar phase
non-fermi liquid
chiral magnets
goldstone modes
condensed matter
helimagnons
gartner hype cycle
investment
finance
market
quantum information
quantum computing
python
quantum physics
tensor network
artificial intelligence
story-telling
production
gradient descent
prototype
science
monitoring
software testing
software development
data science
#dataanalysis
#dataengineering
#it
#machinelearning
#bigdata
#datascience
balaam
nfl
See more
Presentations
(7)Likes
(15)Python tools to deploy your machine learning models faster
Jeff Hale
•
3 years ago
Detecting Lateral Movement with a Compute-Intense Graph Kernel
Data Works MD
•
6 years ago
Natural Language Processing with Graph Databases and Neo4j
William Lyon
•
9 years ago
Machine Learning Powered by Graphs - Alessandro Negro
GraphAware
•
7 years ago
Graph-Powered Machine Learning
GraphAware
•
7 years ago
Nova Data Science Meetup 9-20-2017 Introduction
NOVA DATASCIENCE
•
7 years ago
Nova Data Science Meetup 9-20-2017 Presentation How AI Powers the Comcast X1 Voice Interface
NOVA DATASCIENCE
•
7 years ago
TENSOR DECOMPOSITION WITH PYTHON
André Panisson
•
8 years ago
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
9 years ago
Using Topological Data Analysis on your BigData
AnalyticsWeek
•
11 years ago
Piotr Mirowski - Review Autoencoders (Deep Learning) - CIUUK14
Daniel Lewis
•
10 years ago
Apache Spark Overview
Vadim Y. Bichutskiy
•
10 years ago
Representation Learning of Vectors of Words and Phrases
Felipe Moraes
•
10 years ago
Personal Information
Organization / Workplace
Washington D.C. Metro Area, MD United States
Occupation
Applied Quantitative Researcher
Industry
Government / Military
Website
github.com/stephenhky
About
Kwan-Yuet (Stephen) Ho, Ph.D. is an applied quantitative researcher with 8-year experience in machine learning, text mining, and other related data science and quantitative fields. He possesses exceptional mathematical abilities, and experience with software development. He is seeking to advance his careers in machine learning, data science and quantitative analytics.
Tags
physics
machine learning
theoretical physics
helimagnets
technology
sunday school
numbers
priest
moses
bible
pentateuch
traffic flow
text analytics
data mining
statistical physics
optimization
a phase
nematics
skyrmion
liquid crystal
choletorics
columnar phase
non-fermi liquid
chiral magnets
goldstone modes
condensed matter
helimagnons
gartner hype cycle
investment
finance
market
quantum information
quantum computing
python
quantum physics
tensor network
artificial intelligence
story-telling
production
gradient descent
prototype
science
monitoring
software testing
software development
data science
#dataanalysis
#dataengineering
#it
#machinelearning
#bigdata
#datascience
balaam
nfl
See more