Virtual Conference
SEPTEMBER 7th - 8th, 2022
ODSC APAC 2023 will be announced soon, register your interest and get early access to exclusive discounts on all ticket options
The Upcoming Conference
Join us at our next conference, ODSC East in Boston, May 9-11th. Can’t make it In-Person? Join us virtually!
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Breakout Sessions
Workshops
Speakers
Hours of Content
Attendees
WELCOME TO ODSC
Learn, connect, and grow with 2,000+ data scientists, speakers, and AI practitioners virtually at ODSC APAC 2023
Over the course of 2 days, ODSC APAC will provide expert-led instruction in machine learning, deep learning, NLP, MLOps, and more through immersive workshops and tutorials, and talks. You’ll also have the chance to share insights and build new connections through networking events like Lightning Talks and Open Spaces.
With 100+ hours of content, ODSC APAC has something for every data scientist from beginner to expert.
EXPLORE TRACKS
ODSC APAC 2022 KEYNOTES
Previous Speakers & Instructors
Akira Shibata, PhD
Akira is a renowned data scientist in Japan who led the growth of DataRobot Japan as CEO until June 2021. His background in entrepreneurship (Shiroyagi Corporation), strategy consulting (BCG), experimental particle physicist (LHC, CERN) gives him a unique edge to develop business potential of AI and data technologies. He has worked with over a hundred companies in deploying advanced analytics and digital transformation projects. His active podcast and blog can be found through the links.
MLOps for Musicians(Talk)
Mária Kieferová, PhD
Maria Kieferova (Marika) is a Sydney Quantum Academy fellow, a Lecturer at the University of Technology Sydney (UTS) and a member of Google Quantum AI. She has over ten years of experience working on quantum algorithms, starting from her undergraduate studies at Comenius University in Slovakia. She obtained her PhD from The Institute for Quantum Computing, University of Waterloo, and Macquarie University. Her thesis was awarded the Person medal and IQC Achievement Award. Throughout her studies, she undertook internships at Microsoft Research and Zapata Computing. At UTS, Marika is exploring the boundary between quantum and classical algorithms for machine learning. She is also affiliated with the ARC Centre of Excellence for Quantum Computation and Communication Technology and serves on the editorial board of the IOP journal Quantum Science and Technology.
Dr. Shailesh Kumar
Dr. Shailesh Kumar is currently the Chief Data Scientist at the Centre of Excellence in AI/ML, Reliance Jio. Prior to this he worked as a Distinguished Scientist at Ola cabs, Chief Scientist and Co-founder of Third Leap, an EdTech startup, Researcher in the Google Brain team, Sr. Scientist at Yahoo! Labs, and Principal Scientist at Fair Isaac Research.
Dr. Kumar has 18 years of experience in building AI solutions in a variety of domains including Web, Retail, Finance, Remote Sensing, Fleet Management, Computer Vision, Knowledge Graph, and Conversational computing. He has published over 20 international papers and book chapters and holds more than 20 patents in AI/ML. He was recognized as one of the top 10 data scientists in India in 2015 by Analytics India Magazine. Dr. Kumar holds a Masters and Ph.D. in AI from UT-Austin and B.Tech. in Computer Science from IIT-Varanasi.
Bujuanes Livermore
Bujuanes Livermore is the Head of Research and Design in Data, Intelligence, and Design in Commercial Software Engineering (CSE) at Microsoft and she leads the Worldwide Community for Design & Experience. CSE is a global engineering organization that works directly with the largest companies and not-for-profits in the world to tackle their most significant technical challenges. Bringing human-centered design to the forefront and creating a more harmonious balance between the technical and the human drives her work. She is keenly interested in the influences and effects of digital and augmented environments, the human experience of service and product design, and challenging traditional business models and service offerings.
Dipanjan (DJ) Sarkar
Dipanjan (DJ) Sarkar is a data science consultant and published author, and was recognized as a Google Developer Expert in Machine Learning by Google in 2019. He currently works as a lead data science consultant at Schaffhausen Institute of Technology Academy, Zurich. Dipanjan has led advanced analytics initiatives working with Fortune 500 companies like Intel, Applied Materials, Red Hat / IBM. He works on leveraging data science, machine learning and deep learning to build large- scale intelligent systems. Dipanjan also works as an independent consultant, mentor and AI advisor in his spare time collaborating with multiple universities, organizations and startups across the globe. His passion includes solving challenging data problems as well as educating and helping people upskill in all things data. Dipanjan has also been recognized as one of the top ten Data Scientists in India in 2020, 40 under 40 Data Scientists, 2021 and Top 50 AI Thought Leaders by Global AI Hub, Switzerland. In his spare time he loves reading, gaming, watching interesting documentaries, football. He is also a strong supporter of open-source and publishes his code and analyses from his books, articles and experience on GitHub at https://github.com/dipanjanS and LinkedIn at https://www.linkedin.com/in/dipanzan
Advanced NLP: Deep Learning and Transfer Learning for Natural Language Processing(Workshop)
Dr. Jey Han Lau
Dr Lau is a lecturer in the School of Computing and Information Systems at the University of Melbourne. His research is in Natural Language Processing — a sub-field of Artificial Intelligence — where the goal is to develop computational models to understand human languages. A common theme of Dr Lau’s research is that it involves building computational models in an unsupervised or semi-supervised setting, i.e. a learning scenario where the supervision signal for model training is not available or scarce, and is characterised by a diverse flavour of applications, e.g. topic models, lexical semantics, text generation and misinformation detection. Some of his research in text generation and state-sponsored influence operations has been covered by popular science magazines (New Scientist) and mainstream news media (BBC and Guardian).
Generating Product Descriptions and Answers for Customer Queries on E-commerce Platforms(Talk)
Dr. Fatemeh Vafaee
Dr Fatemeh Vafaee is the Deputy Director of the Data Science Centre at the University of New South Wales (UNSW Sydney) and leads the ‘Health Data Science’ priority area. She launched and leads Artificial Intelligence in Biomedicine Laboratory (VafaeeLab.com) at UNSW and is the founder of OmniOmics.ai proprietary limited company (OmniOmics.ai) with the mission to develop and deploy AI technologies to enhance disease diagnosis and accelerate drug development. Dr Vafaee received her PhD in Artificial Intelligence from the School of Computer Science at the University of Illinois at Chicago, USA (2011) followed by 2 multidisciplinary postdoctoral fellowships at the University of Toronto, Canada, and the University of Sydney, Australia (2012 – 2017) on computational biomedicine. Dr Vafaee has a strong track record of multidisciplinary research leadership and industrial engagement. Her research has attracted over $10.5M across >12 research and industry-based project grants and has been published in top-tier journals in the field.
Big Data and Artificial Intelligence – Driving Personalised Medicine of the Future(Talk)
Juan Intan Kanggrawan
Juan Kanggrawan is the current Head of Data Analytics at Jakarta Smart City. His key role is to fully utilize data to formulate public policy and to improve the quality of public services. Juan is currently working on several city-scale strategic analytics initiatives. He is actively analyzing complex, diverse and exciting urban data on a daily basis: citizen complaint/aspiration, transportation/mobility, health (COVID-19), CCTV, Open Data, weather-flood-river bank, subsidy utilization, food commodities price elasticity, etc. He is also developing and aligning a strategic partnership framework between Jakarta Smart City with other government agencies, business enterprises, research agencies, and universities.
Dr. Lau Cher Han
Dr. Lau Cher Han is a chief data scientist and keynote speaker in data science and A.I for major companies, organisations, and government agencies across Australia, Malaysia, Taiwan and other ASEAN countries.
He has trained and advised many of the organisations including Intel, Standard Chartered, and IBM. He is also keynote speaker in data science conferences for Microsoft, Facebook and Google. As the CEO of LEAD, Dr. Lau’s current focus is on helping clients to grow their data science teams and to gain insights by combining structured and unstructured data. He helps the clients on implementing data analytics and big data strategies, and preparing for the future big data economy.
Dr. Huong Ha
Dr. Huong Ha is currently a Lecturer at the Artificial Intelligence Discipline, School of Computing Technologies, RMIT University, Melbourne, Australia. Her research is in the areas of Artificial Intelligence and Software Engineering, particularly trustworthy machine learning, automated machine learning, and data-driven software engineering. She regularly publishes her works in the leading international research venues in these areas including NeurIPS, ICML, AAAI, AISTATS, ICSE, and ICSME. In addition to her current role in academia, Huong has previous working experience in the industry as a data scientist and a product development engineer.
Data-efficient Active Testing of Machine Learning Models(Talk)
Raymond Reed
Ray is a Customer Success Data Scientist at WhyLabs, the AI Observability company. He has a long held passion for machine learning and loves helping customers save time and money by monitoring their ML systems at scale. Ray was formerly a Senior Success Engineer at Datorama, a Salesforce Company, where he drove success for large enterprise customers with a focus on improving query performance across the company. With his spare time, Ray enjoys hiking, music, and more hiking.
Monitoring CV Systems: A Unique Solution to a Unique Problem(Talk)
Sunny Kim
Sunny is a seasoned professional data scientist, with over 15 years of relevant experience, and successful completion of significant company-onsite projects for many respected companies in South Korea and the US. Significant experience and dynamic practitioner in various domains, including NLP project lead, credit risk modeling, financial distress modeling, customer marketing prediction, and ML service provider consultation. She is passionate about creating and building AI solutions applying a variety of NLP technologies including sentiment analysis, conversational computing, topic modeling, etc. to support AI real-world usages for SME businesses. She is currently putting her efforts into her own AI start-up company – ReviewMind Inc. In 2020, her company was identified as an excellent start-up case by Korea Women in Science and Technology Support Center. Sunny and her team also won the best award in the 2021 Start-up Demo Day from the Korea Institute of Startup & Entrepreneurship Development. Sunny holds both a Masters in Data Science (Information Systems) and an MBA from the US and South Korea respectively.
Ian Hansel
Ian Hansel is a Director of Verge Labs, a company empowering businesses through Machine Learning and Artificial Intelligence. Verge Labs bridges the gap between business and cutting-edge research applications. Ian has lead data teams in corporates and believes in taking away the complexity of machine learning to show people how to use amazing technology on their own.
Building Machine Learning Apps(Tutorial)
Deepak NagarajeGowda
Bio Coming Soon!
Using Augmented Reality, Machine Vision & Deep Learning for Solving Supply Chain Problems(Talk)
Ravi Ranjan
Ravi Ranjan is a full-stack Data Scientist working as Manager Data Science at Publicis Sapient. He holds a Bachelor’s degree in Computer Science & Engineering with a proficiency course in Reinforcement Learning from IISc Bangalore. He has professional experience of 8+ years in AI and ML at scale with expertise in building enterprise data solutions and ML Engineering. He is part of the Centre of Excellence and is responsible for building ML products from inception to production. He has worked on multiple engagements with clients mainly from the Automobile, Banking, Retail, and Insurance industries. He is a Google Certified Professional Cloud Architect, blogger, speaker, and mentor.
Route Optimization using Reinforcement Learning and Metaheuristics(Workshop)
Thilaksha Silva, PhD
Thilaksha Silva has obtained a Doctor of Philosophy (PhD) in Statistics from Monash University, Australia. Thilaksha is skilled in data science for electricity distribution, statistics, time series forecasting, predictive modelling and big data analytics. She is adept at advanced data analytics with 10+ years of experience and has mastered in communicating the business value across the business and engaging audience with data science on a deeper level.
Jonathan Neo
Jonathan is an Analytics Engineer at Canva where he is building data platforms to empower product teams to unlock insights from millions of users.
He has previously worked at EY, Telstra Purple, and Mantel Group, where he has led data engineering teams, built data engineering platforms for ASX-100 customers, and developed new products and businesses. Since 2020, Jonathan has trained over 100 students through data analytics bootcamps and courses. In 2022, he founded Data Engineer Camp, a 14-week data engineering bootcamp that empowers professionals to become data engineers with the modern data stack.
He also hosts the Perth Data Engineering monthly meetup group with over 300 members.
Key Design Principles of Modern Data Platforms (feat. Airbyte, dbt, Snowflake and Dagster)(Workshop)
Urvesh Devani
Urvesh, currently Head of Data Science at Portcast.io (real time predictive visibility and demand forecasting to optimize supply-chain), has more than 8 years of hands-on and 4 years of leadership experience overall across Machine Learning, Software product development, management, and cross-functional collaboration. Urvesh started his career as a software engineer at Cisco, writing and fixing protocols for firewalls and exploring use of machine learning in malware classification. He later joined noodle.ai as a Data Scientist and worked on numerous ML projects involving government, manufacturing industry, and airlines. He has spent some time mentoring Data Science Students at SpringBoard and is currently a fellow at On Deck Data Science (ODDS).
ODSC APAC IN-PERSON MEETUPS
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APAC 2022 Registration
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ODSC APAC Virtual Conference
I can’t possibly explain how much I enjoyed the ODSC East Virtual conference. Many of the talks and workshops exceeded my expectations. Thank you very much and well done!
Batool A. | Research Fellow | Liverpool, UK
ODSC East 2020 is the 3rd ODSC event that I have attended. The staff and speakers did a tremendous job approaching the challenge of moving the conference online. The speakers were engaging, the staff attentive, and my team had a wonderful experience this week. Well done! I look forward to attending my next event.
Leslie Walcott | Data Scientist | Chicago
It’s just wonderful to attend this virtual event with so many people over here. Wonderful Initiative by ODSC. Brilliant Content.
Harshit P. | Software Engineering | Accenture
I just want to say a huge thanks to the organizers! I was skeptical about the remote format at first. However, it is an introvert’s dream! It is so much easier to ask questions in chat/slack than it is to raise my hand in a crowded lecture hall
Andras Z.| Lead Data Scientist | Brown University.
ODSC is the best community data science events on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it’s the conference to engage, to build, to develop, and to learn from the whole data science community.
Kirk Borne | Principal Data Scientist and Executive Advisor at Booz Allen Hamilton
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Accelerate your data science knowledge and network. All in one event.
ODSC APAC Virtual Conference 2022 is one of the largest applied data science conferences. Our speakers include core contributors to many open source libraries and languages. Attend ODSC APAC Virtual Conference 2022 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.
Focus Areas
Deep Learning
Machine Learning
Data Engineering/MLOps
Natural Language Processing
Big Data & Data Analytics
Topics
Recommendation Systems
Transfer Learning
Machine Vision
Autonomous Machines
Conversational AI
Artificial Intelligence
Speech Recognition
Unsupervised Learning
Image Classification
Machine Translation
Tools
Tensorflow, Keras, PyTorch, Caffe, MXNet
Scikit-learn, Theano, Shogun, Pylearn2
Python, Jupyter Notebooks
R programming, Julia, Scala, Stan
Apache Spark, MLlib, Streaming
Azure ML, Amazon ML,H20.ai, Cloud ML
Neo4J, D3.js, R-Shiny
Hadoop, Apache Storm, Apache Flink, Kafka, Druid
The Leading Conference for
MACHINE LEARNING
DATA SCIENCE
DEEP LEARNING
DATA ANALYTICS
DATA ENGINEERING
NLP & NLU
RESPONSIBLE AI
CYBERSECURITY
MLOPS
COMPUTER VISION
Companies Represented at ODSC Conferences
We’re Proud to Have Their Best and Brightest in Attendance
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