This document provides information about an upcoming conference on Machine Learning in Mining to be held on November 10-11, 2021 in Perth, Western Australia. The conference will showcase how major mining companies like BHP, Rio Tinto, Fortescue, and CITIC Pacific are using machine learning to optimize operations. It will also feature presentations from researchers and experts on topics like overcoming data challenges, integrating machine learning solutions, and applying machine learning across the mining value chain. The agenda outlines presentations on various machine learning applications in mining, lessons learned from implementations, and opportunities to network and collaborate.

1. 10-11 NOVEMBER 2021 / WESTIN PERTH
www.mininginnovationnetwork.com
Event Partner:
LIVE STREAMING
AVAILABLE
Exhibitors:
Associate Sponsor: Premier Industry Partner: Supporting Partners:
Community Partner: Association Partner:
Organised by:

2. www.machinelearningmining.com symon.rubens@energyconferencenetwork.com +61 412 342 501
ABOUT THE CONFERENCE
ENHANCE DECISION-
MAKING, IMPROVE SAFETY,
OPTIMISE OPERATIONS
The first annual Machine Learning in Mining conference
will showcase how companies are deploying Machine Learning
and AI models at scale, increasing productivity and enabling more
efficient and environmentally sustainable outcomes. This is a rare
opportunity to discover how exciting new technologies can be
applied - with a focus on implementation and lessons learned.
1.
Hear how BHP, Rio Tinto, Fortescue, Roy Hill and CITIC Pacific are utilising machine
learning to achieve optimal performance at their mining operations
2.
Discover the latest cutting edge machine learning research from the University of
Western Australia and Curtin University
3. Overcome the data skills challenges and future proof your company for future growth
4.
Collaborate with METS companies to optimally integrate internal and external
hardware and software to maximum efficiencies
5.
Understand how machine learning can benefit operations across the whole mining
value chain
REASONS
TO REGISTER

3. www.machinelearningmining.com symon.rubens@energyconferencenetwork.com +61 412 342 501
INDUSTRY EXPERTS
Chris Aldrich
Professor
Curtin University
Tamryn Barker
Co-Founder CORE Skills Lead
CORE Innovation Hub
Alex Bertram
Manager Digital Operations
Manager Digital
Operations
Fred Blaine
Senior Scientist
Imdex
Holly Bridgwater
Principal Industry Engagement
Unearthed Solutions
Dr. Rachna Dhand
Principal – Data Science
PACE – APAC(W)
Rio Tinto WA
Coert du Plessis
CEO
Maxmine
Chelsea Gray
Group Manager
Client Solutions
WesTrac Cat
Mitin Hirani
Principal Data Scientist
Roy Hill
Eun-Jung Holden
Director – Institute of Data
University of Western
Australia (UWA)
Alex Jenkins
Director
WA Data Science
Innovation Hub
Rob Johnston
Manager Solutions Delivery
Citic Pacific Mining
Kylah Morrison
General Manager - Western
Australia South Australia
METS Ignited
Nadia Rom
Manager Data and
Advanced Analytics
Fortescue
Greg Stagbouer
General Manager
Cortex Intelligence
Systems
Justin Strharsky
Managing Director
Unearthed
Steve Sullivan
Senior Technical
Sales Specialist
Maptek
Dr. Satyam Priyadarshy
Managing Director – India
Center, Technology Fellow and
Chief Data Scientist
Halliburton
Edin Mustajbegovic
Founder
Action | Twelve

4. www.machinelearningmining.com symon.rubens@energyconferencenetwork.com +61 412 342 501
AGENDA DAY 1: WEDNESDAY, 10 NOVEMBER 2021
09:00 Introduction by Chairperson
09:10
Why companies should share their data more, not less
It seems like every week, we hear about a new data
breach during which some company has been hacked
and their data stolen. Breaches like this result in
severe costs to both reputation and the bottom line.
It seems clear that companies should do everything
in their power to prevent their data from falling into
the wrong hands.
And yet, companies should be sharing their data more,
not less. Justin will discuss the surprising reasons why.
Justin Strharsky, Unearthed
09:40 Machine Learning for Leaders
Dr. Rachna Dhand, Rio Tinto WA
10:10 Morning break
10:40
How to unearth the gold of machine learning in
mining in 2022
The incredible benefits of Machine Learning and
modern MLOps across a plethora of non-mining
industries are already evident. However, astute mining
industry leaders and investors want an accelerated
pathway to tangibly harness these benefits to
best utilise their data, in turn achieving optimal
performance at their mining operations.
With new unprecedented precision in measurement
and large-scale data collection possible today, Mining
Leaders want to move beyond stale PoCs to data
impact at scale.
In this energetic presentation, Coert will cover;
•
The state of ML across the mining value chain,
focusing on critical areas to outline how miners can
uncover the gold hidden in the mountain of data
•
How to navigate the operational uncertainty that starts
in-ground and permeates the mining value chain to the
customer, which requires a vastly different approach to
ML than most other industries where their inputs are
stable and known
Coert du Plessis, Maxmine
11:10
Lessons learned from keeping a machine learning
solution alive for two years
In early 2019, Roy Hill started using machine learning
to forecast our process plant yield / recovery. This
solution started off as a simple MVP (minimum viable
product) and has grown into a MLOps implementation
•
This session is about sharing this journey and the
learnings from this journey
Mitin Hirani, Roy Hill
11:40 Lunch and networking
12:40
Learnings from scale: experiences implementing
data science platforms
Alex Jenkins, WA Data Science Innovation Hub
13:10
Enhancing orebody knowledge using
machine learning
•
Value of Information – Value of having the right
information at the right time
•
Orebody Knowledge (OBK) and the role of
geoscientific data across the mining lifecycle
•
Unique requirements and challenges for successful
application of ML to OBK
•
OBK in Action – Using high-density spatial data with
ML to increase efficiencies in mining operations
Fred Blaine, Imdex
13:40
Machine learning to classify oil samples:
Implementation and change management lessons
from WesTrac
•
Machine Learning models outperforming rules-based
analysis to predict sample outcomes
•
Analysing the change management and operational
involvement required for successful implementation
Chelsea Gray, WesTrac Cat
14:10 Afternoon Break
14:40
The impact of deep machine learning on the
development of sensors and diagnostic systems in
the mineral processing industries
Exponential growth in big data and recent
breakthroughs in deep learning continue to drive the
widespread adoption of machine learning in industry.
In this presentation, the impact of deep learning in the
process industries will be reviewed, focusing on sensor
data analytics and process monitoring.
This will include examples of the monitoring of
bulk particulates on conveyor belts, the underflow
of hydrocyclones, froth image analysis and signal
processing in general, and a brief look at the emerging
application in modelling and control.
Chris Aldrich, Curtin University
15:10
Geological knowledge discovery using machine
augmented intelligence
•
Data-driven decisions in geoscience may be achieved
through a machine augmented and human-driven
approach
•
Machine learning can be used to produce efficient,
consistent and repeatable outcomes, but its
deployment in industry practice is challenging
•
Deployable machine learning (or data science
in general) needs to address transparency, their
seamless integration into human interpretation
workflow, and generating solutions that are
acceptable by domain experts
•
Machine learning is used not only used for structured
data but also unstructured data towards building AI
for geological knowledge discovery
Eun-Jung Holden, University of Western Australia (UWA)
15:40 Special Presentation – BHP
Alex Bertram, BHP
16:10 Close of Day 1

5. AGENDA DAY 2: THURSDAY, 11 NOVEMBER 2021
www.machinelearningmining.com symon.rubens@energyconferencenetwork.com +61 412 342 501
09:00 Introduction by Chairperson
09:10
Rewarding innovators by investing in technology
that enables the resources and energy sector
Kylah Morrison, METS Ignited
09:40 Investing in data
•
Exploring a Data Value Framework that shows how to
design data investments focused on value
•
How a critical learning approach is not going to
achieve the breakthrough results
•
Ensuring you do not neglect complex data investments
to the detriment of your investments and value
•
Managing your data investment portfolio and
understanding the entire data solution lifecycle
Edin Mustajbegovic, Action | Twelve
10:10 Morning break
10:40 Guideline for Sharing Open Data Sets in Mining
As technology advances, data can provide
opportunities to solve problems in various
areas, including accelerated research, increased
transparency, and the identification of novel solutions
to problems. Unfortunately, the appropriate data
are not always readily available. The Global Mining
Guidelines Group (GMG) has produced a Guideline
for Sharing Open Data Sets in Mining to assist in this
area. The purpose of this guideline is to provide best
practices for data sharing for those within the mining
industry based on existing initiatives so they can
benefit from open data.
Rob Johnston, Citic Pacific Mining
11:10
The Data Fit Organisation - insights on the
framework and examples of how it is changing the
roles of workers across mining organisations
Realising value through data is hard and outcomes can
be inconsistent. The technology is getting better but
process and capability are still developing. A successful
data workflow, one that is embedded in the business,
invokes all roles to consistently realise value. It follows
then, that all roles need to be data capable and
demonstrate an understanding of the data workflow.
Having an industry framework or shared way to
build data capability in support of all roles across an
organisation is therefore critical.
Tamryn Barker, CORE Innovation Hub
11:40
The use of open data sets to help advance machine
learning applications in Mining
Machine learning and cloud computing hold the
immense promise of adding value to mining
operations. A new domain modelling solution delivers
significant improvements in processing speed, ease
of setup and use, alongside the ability to use all your
data and in a secure manner. This paper will outline
how access to cutting-edge machine learning has
never been easier and how it delivers confidence in
domaining and modelling decisions.
Steve Sullivan, Maptek
12:10 Lunch and networking
13:00 Special Presentation – Fortescue
Nadia Rom, Fortescue
13:40
Data Projects Spotlight
Holly Bridgwater, Unearthed Solutions
14:20
Using machine learning and data analytics to
improve drilling technologies and real-time
geological modelling
Greg Stagbouer, Cortex Intelligence Systems
15:00 End of Day
ON DEMAND SESSION
Innovation in Mining-Role of Data, AI, Data Science
and Platforms: Lessons from Hydrocarbon industry
for Collaborative Success
Dr. Satyam Priyadarshy, Halliburton

6. TERMS CONDITIONS
COMPANY DETAILS
Payment Terms
Payment is due in full by credit card upon completion of this registration form.
By completing this registration form you agree to Energy Conference Network
charging your credit card for the amount stated above and you agree to pay
Energy Conference Network the price to secure your conference ticket. Your
registration will not be confirmed until payment has been made by credit card
and cleared funds are received in full. Admission to the conference will be
refused if payment has not been received.
Cancellation and Substitution Policy
Cancellations must be received in writing and we do not offer refunds
once payment has been made. If the cancellation is received more than 14
days before the conference, attendees will receive a full credit to a future
conference. Cancellations received 14 days or less (including the fourteenth
day) prior to the conference will be liable for the full fee. A substitution from
the same organisation can be made at any time in writing at no extra charge.
If Energy Conference Network cancels a conference, payments received at the
cancellation date will be credited towards attendance at a future conference
or in the event of postponement by Energy Conference Network, towards the
rescheduled date. Credit notes remain valid for twelve months.
Changes to Conference and Agenda
Energy Conference Network reserves the right to postpone or cancel an event,
to change the location or alter the advertised speakers for an event. Energy
Conference Network is not responsible for any loss or damage as a result of
substitution, alteration, postponement or cancellation of an event due to causes
beyond its control including without limitation, acts of God, natural disasters,
sabotage, accident, trade or industrial disputes, terrorism or hostilities. In the
event that a conference is cancelled, Energy Conference Network is not liable
for any costs incurred by delegates in connection with their attendance.
Occasionally it is necessary for reasons beyond our control to alter the content
and timing of the program, venue or the identity of the speakers without any
liability to the delegates. Changes to the agenda will be updated on our website
as soon as possible.
Payment by invoice will incur a AU$50 administration fee
Mr Mrs Ms Other
Company Name:
Address:
City:
Postal Code:
Country:
PAYMENT DETAILS
Please select your method of payment
Visa Mastercard American Express
Cardholder Name:
Card Number:
Start Date / Expiry Date:
Issue Number:
(if applicable)
Security Code:
Signature:
Date:
Card billing address:
(if different from
the above)
DELEGATE DETAILS
First Name:
Last Name:
Job Title:
Email:
Tel:
Mobile:
Category 1 / Registration for Mine Operator or Company
Registration to attend Machine Learning in Mining for mine operators and mining companies. Registration fee covers
access to the event for two days, all associated networking functions, morning/afternoon teas and lunches and
access to approved presentations post event.
Category 2 / Non-Mine Operator or Company
Registration to attend Machine Learning in Mining for mining equipment, technology and services providers, consultants,
research bodies, government. Registration fee covers access to the event for two days, all associated networking functions,
morning/afternoon teas and lunches and access to approved presentations post event.
Category 3 / Enhanced Delegate
Registration fee covers access to the event for two days, all associated networking functions, morning/afternoon teas
and lunches, access to approved presentations post event AND corporate branding at Machine Learning in Mining.
Category 4 / Student
Registration to attend Machine Learning in Mining as a student. You must be a FULL-TIME student, you will need to
register with your school email and bring your student ID when you check in at the registration desk. Registration fee
covers access to the event for two days, all associated networking functions, morning/afternoon teas and lunches
and access to approved presentations post event.
Live Streaming Registration
This registration is to view the event via Live Streaming. No in person attendance is included.
Early Bird Pricing
Ends 15 October
AU$895
AU$1,295
AU$1,295
Regular Price
Beginning 16 October
AU$995
AU$1,395
AU$1,995
REGISTER ONLINE AT: www.machinelearningmining.com
AU$395 AU$395
AU$95 AU$95