Case Study - Victor

1. VICTOR YIP
PREDICTING CRIME
ON THE STREETS
OF CHICAGO

2. VICTOR YIP
PREDICTING CRIME ON THE STREETS OF CHICAGO.
Can we predict crimes
using data science?
This project investigates the
occurrence of crimes in Chicago in
relation to the spatial and Twitter data
obtained between mid April to mid
May 2016.
Descriptive analysis of crime data is
common but our project pushes it a
step further to demonstrate the
predictive capability of widely
available data by using machine
learning techniques.
Task:
I am part of a team
of three students
from MSc Business
Analytics. We
leveraged techniques
from natural
language processing
(NLP), kernel density
estimate and support
vector machines
using crime data
from the Chicago
Open Data Portal and
Twitter to model and
provide probabilistic
estimation of future
crime occurrence
in Chicago.
Review:
We offer our solution through
an interactive website with the
aim of assisting the Chicago
government and police force
to more strategically mobilize
patrol force to places with a
high probability of crime. The
interactive website also serves
as a tool for the wider public
to understand crime statistics
in the city.
This project is unique in three
ways. It it is a easily accessible
tool despite the complicated
model it is based on. It is a
real-time tool that takes in
live action on Twitter and the
latest crime data to update
its prediction. And finally, it
provides a point estimate
so that no street corner in
Chicago is missed out.

3. Q&A
WE SAT DOWN WITH VICTOR AND ASKED HIM A FEW
QUESTIONS ABOUT HIS PROJECT AND ASK WHAT HE
THINKS THE FUTURE HOLDS FOR HIMSELF.
What makes this project unique?
This project is unique in three
ways. Firstly, it is a easily
accessible tool despite being
based on a complicated model.
Secondly, it is a real-time tool that
takes in live action on Twitter and
the latest crime data. Thirdly, it
provides a point estimate so that
no street corner in Chicago is
ever missed out.
What was the moment you
realised you wanted to do
what you’re doing today?
I spent 4 years in finance in a
leading investment bank in Hong
Kong. It was a great experience
with very dedicated and smart
people. But it was not forward
thinking in terms of technology
innovation. I realised that instead of
relying on someone else to code an
idea, I could go deeper down this
vertical to learn coding by myself.
What’s your biggest
career highlight?
Obviously there is a lot more to
be done. But I was really happy to
deliver on a year-long project at
Asia Pacific to revamp the process
of international function relocation.
What motto do you
live your life by?
It is not the hours you put in but
what you put in the hours. The
purpose of life is to find your gift,
the goal of life is to give it away.
Share one big trend
emerging in engineering
and why it’s important?
Artificial intelligence. I have only
been scratching the surface of
this domain in the past year. I am
curious to see how AI will replace
human productivity and how it will
impact society.
What excites you about the
opportunities with data today
and in the future?
Hidden patterns and trends that
we might have never envisioned.
I am very excited to be alive at the
era of data-enabled proliferation.
////
“It is not the
hours you
put in but
what you put
in the hours”