Agenda

Time Main Conference Agenda
09:00 Welcoming Speech, Opening Remarks & Thank You Sponsor Speech by Conference Producer
JAKE-SAUNDERS-rounded Day One Chairman:

JAKE SAUNDERS
Vice President, Asia-Pacific & Advisory Services
ABI Research

ABI research logo horizontal HR
09:15

Opening Address: The AI-First Enterprise: How Automated Machine Learning is Used To Transform the Enterprise

Today, companies now have the ability to use machine learning & AI as a competitive advantage in their market, reduce operational costs, create new revenue streams, and drive higher customer satisfaction and loyalty. How then do you scale AI across your enterprise to deliver top & bottom line-benefits…create truly an “AI-Driven Enterprise”.
Sebastian-Wedeniwski-rounded SEBASTIAN WEDENIWSKI
Chief Technology Strategist
Standard Chartered Bank
Standard Chartered
09:45 The Intersect of Artificial Intelligence with Robotics: Latest Advances
If you get into a car accident in China in the near future, you’ll be able to pull out your smartphone, take a photo, and file an insurance claim with an AI system. That system, from Alibaba, will automatically decide how serious the ding was and process the claim accordingly with an insurer. It shows how the company aims to upend many business areas using machine learning and AI.
Nadia-Magnenat-Thalmann-rounded PROF NADIA MAGNENAT THALMANN
Director, Institute for Media Innovation
Nanyang Technological University
Nanyang Technological University
10:15 Morning Refreshments & Networking Session
10:30 Advanced AI Experience from abroad, with many case studies and latest AI innovations:
  1. USA & Canada
  2. UK, Germany, France, Europe, Russia
  3. China, Korea, Japan, Taiwan
  4. Israel, India
  5. Australia/New Zealand, Southeast Asia
LIAN-JYE-SU-rounded LIAN JYE SU
Principal Analyst
ABI Research
ABI Research
11:30 KEYNOTE TOPIC: Grab’s Transformational AI Lab in Singapore: How Grab is Using AI to Build its Future Business Platform
Ride-hailing company Grab has teamed up with the National University of Singapore (NUS) to launch an artificial intelligence (AI) laboratory to solve urban transportation issues. The laboratory, which is aptly called the Grab-NUS AI Lab, has been set up with a joint initial investment of S$6 million).
Jagan-Varadarajan-rounded Keynote Speaker:
DR JAGAN VARADARAJAN
Head of Data Science (Machine Learning and Maps)
Grab
Grab_logo-01
12:00 Global CEO – CTO – Chief Data Scientist Forum: What Top Fortune 100 Companies are Doing with AI + Industry 4.0 today and What We Can Learn From Them – Success in the Age of AI
Are Industry 4.0 and IIoT just hype, or do these technologies provide a measurable ROI or benefit? An in-depth discussion of what forward-thinking companies are doing today, and the ROI and value of each: Real-time data analytics and control of high technology “lights out” production lines; Cloud technology automatically tracking and replenishing raw material levels at workstations; Global factory and supply chain (remote) visibility; Real time visibility of KPI’s, and real-time alerts for WIP, yield, throughput on hundreds of production lines worldwide; How equipment connectivity automates quality records and “forces” day to day regulatory compliance management. What can CEOs, CTOs of corporation in this region do to fast-forward AI adoption?
12:30 Networking Lunch
13:30 Roundtable: How Deep Learning and Machine Learning is Transforming Different Vertical Industries
In this session we will share how a platform based approach will drive adoption and enable our business team to innovate.  The challenges & enablers to make the RPA / AI platforms scale to enterprise grade will be detailed.
  • AI in the Courts, in the Legal Community and Law Enforcement/Investigation – Unleashes AI to Automate Legal Work
  • AI in Education – Advances in AI are Giving Teachers a Better Understanding of How Their Students Learn and Personalize Individual Learning
  • AI in Defence & Security/Intelligence Services – Using AI to Predict the Probability of Crime in Location by Detecting Anomalies and Faces
  • Augmenting Drones with AI
Jiin-Joo-Ong-rounded JIIN JOO ONG
Co-Founder & Chief Technology Officer
Garuda Robotics
Garuda Robotics
  • AI in Transportation: Aviation and Airports, Trains, Shipping, Autos & Parking, Last Mile: Case Study of How AI is Deployed in Supply Chains to enable Smart Procurement, Intelligent Indenting and Efficient Demand Forecasting
  • AI for Perception and Tracking. Use-case and Methodology
Eric-Julianni-rounded ERIC JULIANI
Technical Team Lead, Deep Learning
Easy Mile
Easy Mile
  • AI in Engineering Services, Packaging and Manufacturing, Factory of the Future: Robust AI in the production chain
SOMNATH-MUKHERJEE-rounded SOMNATH MUKHERJEE
Senior Computer Vision Engineer, ADAS Camera
Continental AG
Continental AG
  • AI in Construction, Real Estate, Infrastructure Development
  • AI in Medical Research & Surgery: Case Study of How AI is Helping Doctors Diagnose Cancer Faster and More Effectively
Shailendra-Bajpai-rounded DR. SHAILENDRA BAJPAI
Head of Disease Management and Stakeholder Engagement, Sanofi Emerging Markets Diabetes and CV
Sanofi
Sanofi logo
  • AI in Wealth and Fund Management, Derivatives Trading, Banking & Insurance – Case study of Using AI to Carry Out Financial Trading Across the World
  • AI for Power Generation, Transmission, Distribution and Renewables
Praveen-Lala-rounded PRAVEEN LALA
Regional Director
GE Digital
GE ANZ
  • AI for Oil & Gas, Petrochemicals, Refining, Mining, Natural Resources
  • AI for Customer Experience and E-Commerce
  • AI for Water, Waste management, Environmental Services
  • AI for Supply Chain, Demand Forecasting
  • AI for SemiConductor & Electronics Manufacturing
  • AI for Physical and Cyber Security
  • AI for Banking and Financial Services
  • The Use and Implications of AI for Creative Fields Such as Music
AGNES-KAT-rounded KAT AGRES
Research Scientist, Social & Cognitive Computing Department, (IHPC)
A*STAR
A STAR
15:30 Afternoon Refreshments & Networking Session
16:00 Operationalizing Machine Learning: How to Ensure Value-Driven Deployment
Machine learning only delivers value when acted upon – that is, when deployed. Only a carefully designed management process ensures that the analytics’ output is pragmatically viable for operationalization, and that company operations – your internal consumers of analytics – know best how to employ the product they’re consuming. Overcoming the challenges of AI operationalization, providing insights as to how best to execute on the functional deployment of machine learning.
Praveen-Lala-rounded PRAVEEN LALA
Regional Director
GE Digital
GE ANZ
16:30 Development of Machine Pre-Maintenance using Autonomous Learning
Korea Telecom MAN SEOK OH
Head, AI Development
Korea Telecom
Leading development of Sound and Image Deep Learning in KT
17:00 Closing Remarks by Conference Chairman
17:05 Champagne Networking Session
image-3
Enjoy a glass of champagne whilst networking with other like-minded individuals on topics that are of most interest to you and fellow delegates.
Time Main Conference Agenda  
09:00 Welcoming Speech, Opening Remarks & Thank You Sponsor Speech by Conference Producer
09:15

Government-Wide AI Strategy: How AI Increase Efficiency, Reduce Operational Costs, Improve Service Delivery and Increase Citizen Engagement

  • Augmenting policy and resource allocation decisions thereby improving effectiveness of policy with optimized staff and resource allocation and citizen satisfaction from predictive citizen sentiment
  • Optimizing staffing and resource availability with improved efficiency of better staff and infrastructure utilization from service and resource demand forecasting
09:45 AI in Enhancing Government’s Productivity: How AI and Robotic Process Automation Will Slash Paperwork Burdens, Reduce Manual and Repetitive Tasks with Bots
Reducing administrative burden and workload with Robotic Process Automation and Intelligent Automation while improving public service quality with decreased response time and increased accuracy and consistency
10:15 Morning Refreshments
 Attaining Transformational Business Outcomes with AI
10:30 Data-driven Approaches in a Technology Startup
MICHAL-SZCZECINSKI-rounded

MICHAL SZCZECINSKI
Head of Data
GOGOVAN

GOGOVAN
11:00 Moving AI Off Your Product Roadmap and Into Your Products
JULIANA-CHUA-rounded JULIANA CHUA
Head Digital Transformation
NTUC Income
NTUC Income
AI Breakthroughs and Adoptions in World Class Organizations
 11:30 Data Analytics and Data Analytics based  on AI Models
SUDHIR-PANDA-rounded SUDHIR PANDA
Senior Associate Director, Group Digital Commerce, Digital Bank
International Bank
12:00 AI in Action: Case Study of How AI is Helping Doctors Predict Outcomes of Patients Effectively
ANDY-TAN-rounded ANDY TAN KIAN SOON
Principal Medical Informatics Specialist
National University Health System
National University Health System
12:30 Networking Lunch
13:30 How AI Can Be in the Risk and Compliance Domain
Bobby-rounded BOBBY THOMAS
Head – Risk Analytics
Prudential
Prudential Corporation Asia
14:00 Design Thinking in AI: Utilizing data in the newsroom amidst an aggressive digital transformation at a century-old paper
KOREY-LEE-rounded KOREY LEE
Head of Data Analytics
South China Morning Post
South China Morning Post
14:30 Building the AI Systems of the Future: Trends in new AI Systems
One of the biggest challenges in AI is how to translate advances in the lab into large-scale applications. This challenge sits at the intersection of AI and systems engineering and requires an integrated understanding of all of the components that make up a large machine learning-based system, including computation, storage, communications, and algorithms. What are the current trends in new AI systems and how codesigning these components in concert will be critical for building the AI systems of the future.
RAJESH-NANDAKUMAR-rounded RAJESH NANDAKUMAR
Head of Enterprise Architecture Governance Global Consumer Technology Asia & EMEA
CITI Bank
Citi bank
15:00 Afternoon Refreshment & Networking Session
15:30 What We’ve Learned Solving Business Problems with Deep Learning
What if you could QA everything and make your best employees 10–100x more efficient? Engineers and executives want AI to do more than researchers typically consider. Business leaders want AI to consume all of the data that matters (images, audio, video, text, structured, etc.). Businesses also want AI to get smarter “automagically.” What realistically is the state of the art across multiple industries and what is actually being done versus what is still a toy problem. Top reasons why the majority of AI projects fail to ship value and touches on concerns around IP and AI liability.
SIMON-LEE-rounded SIMON LEE
Asia – Regional Chief Operating Officer
AXA
AXA
16:00 AI for Customer Experience and E-Commerce: How ML is Helping NTUC Link Transform a Legacy Loyalty Program into Omni-Channel Personalized Customer Experiences
Kevin-Oh-rounded KEVIN OH
VP, Head of Customer and Digital Analytics
NTUC Link
NTUC Link
16:30 Operationalising AI
VINCE-KARSTEN-rounded VINCE KASTEN
Regional Operations – Robotics and AI
Prudential Corporation Asia
Prudential Corporation Asia
17:00 Closing Remarks by Conference Chairman
MORNING: POST-CONFERENCE SEMINARS
post conference image 1 Seminar 1. How to Build Your Company’s AI Strategy. As a C-level executive, how do you navigate through the 4th industrial revolution, aka AI? This session provides strategy and best practices to affect your company’s bottom-line or top-line positively using AI, as well as how to oversee the whole cognification process.

Seminar 2. Implementing AI & Deep Learning in R, the Well-known Open-source Platform for Data Science and Machine Learning

Seminar 3. How to Train and Execute a Deep Learning Model Able to Re-identify and Extract Attributes from Humans

AFTERNOON: SITE TOUR
post conference image 2 Visits to corporations and institutions which have successfully rolled out AI & IoT programmes. Potential site visits include:

  • OCBC AI Innovation Lab
  • Citi Innovation Lab
  • StanChart Innovation Lab