“All of the lecturers did a fantastic job in teaching their respective courses.
They had clearly all put a lot of thought into how they were going to present
the content in a way that was accessible to the audience in such a short period of time.”

Jacob Priddle, Queensland University of Technology

Timetable

AMSI Winter School 2024 will focus on the theme ‘Decision Making Under Uncertainty’ through the delivery of a series of short courses throughout the two-week timetable. Each short course consists of a mix of lectures and tutorials.

In addition, a number of program extras are included in the program to maximise your experience and provide opportunities for networking.

Attendance is expected at all scheduled lectures and events over the two-week program.

Key

Course 1: Financial Data Analytics

Professor Phillip Yam
The Chinese University of Hong Kong

Course 2: Decision-making under Uncertainty in Robotics

Professor Hanna Kurniawati
Australian National University

Course 3: Mimicking: Martingales with Matching Marginals

Dr Jie Yen Fan
Monash University

Course 4: Reinforcement Learning – Theory, Algorithms and Applications

Dr Nan Ye
The Queensland University of Technology

Event Extras
TimeTable Week 1
WA SA & NT AEST Monday 24 June Tuesday 25 June Wednesday 26 June Thursday 27 June Friday 28 June
7.30 am 9.00 am 9.30 am Registration
(Science Learning Centre)
Participant Talks
(Forgan Smith 01 – Room: TBA)
HANNA KURNIAWATI
Decision-Making under Uncertainty in Robotics
lecture 1
(Forgan Smith 01-E109)
HANNA KURNIAWATI
Decision-Making under Uncertainty in Robotics
lecture 4
(Forgan Smith 01-E109)
HANNA KURNIAWATI
Decision-Making under Uncertainty in Robotics
lecture 5
(Forgan Smith 01-E109)
8.00 am 9.30 am 10.00 am Official Opening & APR.Intern Presentation
(Science Learning Centre)
8.30 am 10.00 am 10.30 am Morning Tea
(Forgan Smith 01-E109)
Break Morning Tea
(Forgan Smith 01-E109)
Break
9.00 am 10.30 am 11.00 am Morning Tea
(Science Learning Centre)
Participant Talks
(Forgan Smith 01 – Room TBA)
HANNA KURNIAWATI
Decision-Making under Uncertainty in Robotics
lecture 2
(Forgan Smith 01-E109)
Decision-Making under Uncertainty in Robotics
Tutorial 1
(Forgan Smith 01-E109)
Decision-Making under Uncertainty in Robotics
Tutorial 2
(Forgan Smith 01-E109)
9.30 am 11.00 am 11.30 am CAMPUS TOUR
10.00 am 11.30 am 12.00 pm Break

Welcome Lunch 12.30pm – 1.30pm (Science Learning Centre)

Lunch
12pm – 1pm
(Forgan Smith 01-E109)
10.30 am 12.00 pm 12.30 pm Break Break Break
11.00 am 12.30 pm 1.00 pm
11.30 am 1.00 pm 1.30 pm PHILLIP YAM
Financial Data Analytics
Lecture 1
(Forgan Smith 01-E109)
PHILLIP YAM
Financial Data Analytics
Lecture 2
(Forgan Smith 01-E109)
PHILLIP YAM
Financial Data Analytics
Lecture 3
(Forgan Smith 01-E109)
Financial Data Analytics
Tutorial 1
(Forgan Smith 01-E109)
Financial Data Analytics
Tutorial 2
(Forgan Smith 01-E109)
12.00 pm 1.30 pm 2.00 pm
12.30 pm 2.00 pm 2.30 pm Break Break Break PHILLIP YAM
Financial Data Analytics
Lecture 4
(Forgan Smith 01-E109)
MAITHILI MEHTA
Special Lecture
(Forgan Smith 01-E109)
1.00 pm 2.30 pm 3.00 pm QCIF Presentation
(Forgan Smith 01 – E109)
KONSTANTIN BOROVKOV
Special Lecture
(Forgan Smith 01-E109)
HANNA KURNIAWATI
Decision-Making under Uncertainty in Robotics
lecture 3
(Forgan Smith 01-E109)
1.30 pm 3.00 pm 3.30 pm PHILLIP YAM
Financial Data Analytics
Lecture 5
(Forgan Smith 01-E109)
Careers Session
(Science Learning Centre)Afternoon tea provided
2.00 pm 3.30 pm 4.00 pm MATTHEW MASON
Special Lecture
(Forgan Smith 01-E109)
2.30 pm 4.00 pm 4.30 pm
3.00 pm 4.30 pm 5.00 pm Public Lecture Reception
(GCI Atrium)
3.30 pm 5.00 pm 5.30 pm
4.00 pm 5.30 pm 6.00 pm KERRIE MENGERSEN
Public Lecture
(Steele 03-206)
Friday night social
Saint Lucy’s Caffe e Cucina

Please note: Timetable may be subject to change

TimeTable Week 2
WA SA & NT AEST Monday 1 July Tuesday 2 July Wednesday 3 July Thursday 4 July Friday 5 July
7.30 am 9.00 am 9.30 am NAN YE
Reinforcement Learning
lecture 1
(Forgan Smith 01-E109)
NAN YE
Reinforcement Learning
lecture 2
(Forgan Smith 01-E109)
NAN YE
Reinforcement Learning
lecture 3
(Forgan Smith 01-E109)
NAN YE
Reinforcement Learning
lecture 4
(Forgan Smith 01-E109)
NAN YE
Reinforcement Learning
lecture 5
(Forgan Smith 01-E109)
8.00 am 9.30 am 10.00 am
8.30 am 10.00 am 10.30 am Morning Tea
(Forgan Smith 01-E109)
Morning Tea
(Forgan Smith 01-E109)
Break Morning Tea
(Forgan Smith 01-E109)
Break
9.00 am 10.30 am 11.00 am JIE YEN FAN
Mimicking: Martingales with Matching Marginals
Lecture 1
(Forgan Smith 01-E109)
JIE YEN FAN
Mimicking: Martingales with Matching Marginals
Lecture 2
(Forgan Smith 01-E109)
JIE YEN FAN
Mimicking: Martingales with Matching Marginals
Lecture 3
(Forgan Smith 01-E109)
JIE YEN FAN
Mimicking: Martingales with Matching Marginals
Lecture 4
(Forgan Smith 01-E109)
JIE YEN FAN
Mimicking: Martingales with Matching Marginals
Lecture 5
(Forgan Smith 01-E109)
9.30 am 11.00 am 11.30 am
10.00 am 11.30 am 12.00 pm Break Break Lunch
(Forgan Smith 01-E109)
12pm-1pm
Break Farewell Lunch
(Science Learning Centre)
10.30 am 12.00 pm 12.30 pm
11.00 am 12.30 pm 1.00 pm Queensland brain Institute Lecture
(Forgan Smith 01-E109)
Reinforcement Learning
Tutorial 1
(Forgan Smith 01-E109)
Optiver Trade-a-thon
(Forgan Smith 01-E109)
Reinforcement Learning
Tutorial 2
(Forgan Smith 01-E109)
11.30 am 1.00 pm 1.30 pm
12.00 pm 1.30 pm 2.00 pm Boeing Presentation
(Boeing Centre)
12.30 pm 2.00 pm 2.30 pm Break Break Break
1.00 pm 2.30 pm 3.00 pm Mimicking: Martingales with Matching Marginals
Tutorial 1
(Forgan Smith 01-E109)
Participant Talks (Final)
(Forgan Smith 01-E109)
Mimicking: Martingales with Matching Marginals
Tutorial 2
(Forgan Smith 01-E109)
1.30 pm 3.00 pm 3.30 pm
2.00 pm 3.30 pm 4.00 pm
2.30 pm 4.00 pm 4.30 pm Diversity in STEM
(Science Learning Centre)
3.00 pm 4.30 pm 5.00 pm

Please note: Timetable may be subject to change

Program Extras

Included in the program are a range of extra activities designed to share ideas, help you see your research in a new light, build your networks and get the most out of your experience in Brisbane