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Thrive in an AI-driven world.
We’ve reached an inflection point in both the AI industry and society at large, and the APAC region at the epicenter of this change. To ensure you’re at the forefront of this change, ODSC APAC is gathering leading experts from across the globe to share their knowledge through 100+ hours of hands-on training sessions, workshops, talks and more.
Join us for a deep dive into the latest data science and AI trends, tools and techniques: from LLMs to data analytics and from machine learning to responsible AI.
What to Expect
EXPLORE TRACKS
ODSC APAC PAST KEYNOTES
PAST ODSC APAC KEYNOTES
Previous Speakers & Instructors
Dominic Bohan
A TEDx speaker, Dom brings a wealth of data storytelling experience to StoryIQ from his career at QBE, one of Australia’s largest insurance companies. At QBE, he was a senior leader in data analytics and business improvement, presenting data-driven strategy recommendations to the company’s senior executives and producing reports for the Group Board of Directors.
Kerrie Mengersen, PhD
Kerrie Mengersen is a Distinguished Professor of Statistics and Director of the Centre for Data Science at QUT. Her career in statistical consulting and academic research has taken her across three states of Australia, the USA and France. Kerrie is a Fellow of the Australian Academy of Science, the Australian Academy of Social Sciences, and the Queensland Academy of the Arts and Sciences. Her overall ambition is to ‘use data better’, particularly in the fields of health, environment and industry. To this end, she has led over 30 major projects such as the current Long-term Benefits and Impacts Study with Queens Wharf Brisbane, the online interactive Australian Cancer Atlas and the Virtual Reef Diver program.
Making Private Data Open and Enhancing Decision-Making through Digital Atlases(Talk)
Dipanjan (DJ) Sarkar
Dipanjan (DJ) Sarkar is an acknowledged Data Scientist, published Author and Consultant with over nine years of industry experience in all things data. He was recognized as a Google Developer Expert in Machine Learning by Google in 2019, and a Champion Innovator in Cloud AI\ML by Google in 2022. He currently works as a Lead Data Scientist at Constructor Learning (formerly Schaffhausen Institute of Technology (SIT) Learning), 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. Find more about him at https://djsarkar.com
Karin Verspoor, PhD
Professor Karin Verspoor is Dean of the School of Computing Technologies at RMIT University. She was previously a Professor in the School of Computing and Information Systems and Deputy Director of the Health and Biomedical Informatics Centre at the University of Melbourne.
Trained as a computational linguist, Karin’s research primarily focuses on extracting information from clinical texts and the biomedical literature using machine learning methods to enable biological discovery and clinical decision support. Karin held previous posts as the Scientific Director of Health and Life Sciences at NICTA Victoria Research Laboratory, at the University of Colorado School of Medicine, and Los Alamos National Laboratory. She also spent 5 years in start-ups during the US Tech bubble, where she helped design an early artificial intelligence system.
Large Language Models Are Not (Necessarily) Generative Ai(Talk)
Ville Tuulos
Ville has been developing infrastructure for machine learning for over two decades. He has worked as an ML researcher in academia and as a leader at a number of companies, including Netflix where he led the ML infrastructure team that created Metaflow, a popular open-source framework for data science infrastructure. He is a co-founder and CEO of Outerbounds, a company developing modern human-centric ML. He is also the author of the book Effective Data Science Infrastructure, published by Manning.
Human-Friendly, Production-Ready Data Science with Metaflow(Talk)
Hugo Bowne-Anderson, PhD
Hugo Bowne-Anderson is a data scientist, writer, educator & podcaster. His interests include promoting data & AI literacy/fluency, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. He does many of these at DataCamp, a data science training company educating over 3 million learners worldwide through interactive courses on the use of Python, R, SQL, Git, Bash and Spreadsheets in a data science context. He has spearheaded the development of over 25 courses in DataCamp’s Python curriculum, impacting over 170,000 learners worldwide through my own courses. He hosts and produce the data science podcast DataFramed, in which he uses long-format interviews with working data scientists to delve into what actually happens in the space and what impact it can and does have. He earned PhD in Mathematics from the University of New South Wales, Australia and has conducted biomedical research at the Max Planck Institute in Germany and Yale University, New Haven.
Helen Thompson
Helen Thompson is an Associate Professor of Statistics in the School of Mathematical Sciences and the Centre for Data Science at QUT. She specialises in statistical modeling and machine learning. With expertise in high-dimensional data analysis, space-time modeling, and optimum experimental design, she has made significant contributions to various fields including health, environment, and social sciences. She has published extensively in leading journals and her work provides valuable insights into complex datasets, uncovering hidden patterns and informing optimal decision-making processes in projects including Optimal Resource Extraction with BHP, Emergency Department Demand Modelling with Queensland Metro South Health and Hospital Services, Great Barrier Reef monitoring programs, and the Australian Cancer Atals.
Making Private Data Open and Enhancing Decision-Making through Digital Atlases(Talk)
Raghav Bali
Raghav is a seasoned Data Science professional with over a decade’s experience of research & development of large-scale solutions in Finance, Digital Experience, IT Infrastructure and Healthcare for giants such as Intel, American Express, United HealthGroup and DeliverHero. He is an innovator with 10+ patents, a published author of multiple well received books & peer-reviewed papers and a regular speaker in leading conferences on topics in the areas of Generative AI, Recommendation Systems, Computer Vision, NLP, Deep Learning, Machine Learning and Augmented Reality.
Building Robust and Scalable Recommendation Engines for Online Food Delivery(Talk)
Seema Chokshi
Seema Chokshi is the founder of Brainbox Solutions, guiding small and medium size firms in adopting AI to improve productivity. Seema is an established thought leader and expert with over two decades of experience in the field of Data Science. Seema learned about the power of data driven decisioning during the 2008 global financial crisis, as a part of the New York based niche credit risk management team, in the global financial services firm, American Express. Her love for inspiring the younger generation with her passion for the field, made her join Singapore Management University in 2013 as the Faculty and Founding Director of the university-wide Analytics Program. Over the years she has taught various graduate courses covering multiple aspects of Data Science. Seema has advised multiple organizations globally to set up productive Data Science teams. Seema is the author of multiple cases studies, available for purchase in the Harvard Business store, with focus on uncovering challenges that hamper trust in AI. Her research aims to uncover how Responsible AI can help companies inch closer to reaping full benefits of AI by minimising unintended consequences and instilling trust in the technology at the same time. Seema is a women’s empowerment champion, guiding and mentoring women in navigating the challenges of their unique career journeys through women empowerment sessions and meetups.
State of AI in Human Resource Functions: Unique Opportunities and Challenges (Talk)
A M Aditya
Aditya is a tech enthusiast with more than 7 years of experience across various technologies in data science, machine learning, deep learning and computer vision. He has completed his Masters in Data Science from the National University of Singapore. He has worked across various domains including automotive, banking, retail among others consulting various clients around the globe. He is a true believer of ‘You got to see it work to know it works’ and sets goals towards achieving the same in any of the endeavours he undertakes. Being highly inclined towards technology, he founded Xaltius Pte. Ltd in Singapore which has a major focus on building solutions in Data Science and AI and educating students and professionals in the same areas. He also founded Code for India which specializes in delivering top notch skills in Data Science and AI as required in the industry today. Apart from work, he loves to engage with kids and get involved in social work.
Jayachandran Ramachandran
Jayachandran Ramachandran is the Senior Vice President and Head of Artificial Intelligence Labs at Course5 Intelligence. He is responsible for Applied AI research, Innovation and IP development. He is a highly experienced Analytics and Artificial Intelligence (AI) thought leader, design thinker, inventor with extensive expertise across a wide variety of industry verticals like Retail, CPG, Technology, Telecom, Financial Services, Pharma, Manufacturing, Energy, Utilities etc.
Jason Tan
Jason Tan is the Founder of Engage AI, a Conversation Copilot that remembers conversations across multiple channels to augment conversations in virtual and real-life. Since its release in Jan 2023, over 30,000 users worldwide have been using it to break the ice and engage with their prospects. Taking the learnings from implementing Engage AI, he also assists and shares the learnt lessons with enterprises to embrace and incorporate Generative AI and Large Language Models into their business.
Framework and Lessons Learned from Building a Generative AI Application(Talk)
Jayeeta Putatunda
Jayeeta is a Senior Data Scientist with several years of industry experience in Natural Language Processing (NLP), Statistical Modeling, Product Analytics and implementing ML solutions for specialized use cases in B2C as well as B2B domains. Currently, Jayeeta works at Fitch Ratings, a global leader in financial information services. She is an avid LP researcher and gets to explore a lot of state-of-the-art open-source models to build impactful products and firmly believes that data, of all forms, is the best storyteller. Jayeeta also led multiple NLP workshops in association with Women Who Code, and GitNation among others. Jayeeta has also been invited to speak at International Conference on Machine Learning (IML 2022), ODSC East, MLConf EU, WomenTech Global Conference, Data Science Salon, The Al Summit, and Data Summit Connect, to name a few. Jayeeta is also an ambassador for Women in Data Science, at Stanford University, and a Data Science Mentor at Girl Up, United Nations Foundation, and WomenTech Network where she aims to inspire more women to take up STEM. Jayeeta has been nominated for the WomenTech Global Awards 2020 and has been spotlighted in the List of Top 100 Women Who Break the Bias 2022. More information here – https://linktr.ee/JayeetaP
Building the Future of LLM Applications – with LangChain and Vector Databases(Talk)
Kevin Noel
Kevin Noel is currently Lead of Machine Learning Ads at Mapbox Japan and has more than 10 years experience in Japan. Previously, he held principal ML role at the largest Big Data, E-commerce in Japan (Rakuten), working with large scale multi-modal data (Tabular, Time series, Japanese NLP, image) through numerous machine learning projects in real time Ads/Recommendations, also provided internal training on Deep Learning and external talks on applied ML (New York, 2019, Kobe(Japan)… )… Prior to this, Kevin, with a background in applied Stochastic Modeling and Data Mining from Ecole Centrale (France), held various quantitative roles a BNP Paribas, Bank of America, and ING in Asia/Japan.
Applied Reinforcement Learning for Online Ads/Recommender(Talk)
Kuldeep Jiwani
Kuldeep Jiwani is Head of Data Science for HiLabs, a US Healthcare MNC. He has been driving research and innovation in the Healthcare sector using state of the art AI technologies like LLMs, Medical Ontologies, NLP, Predictive Analytics in multiple areas, Bayesian modeling, Statistical modeling, Time series forecasting, etc. Built 6 products in a year with a team of 50+ data scientists, where each product gathered multi-million dollars for the company.
Prior to this he was building machine learning applications at massive scale for the telecom sector. Discovering telecom subscribers behavioural patterns via mining and modelling billions of daily records, for various use cases like Churn prediction, Network congestion, Service experience, etc. He has been a Performance architect designing high scalable Big Data solutions over distributed systems. Then designing ultra-low latency trading solutions for the Financial trading tools industry. He has been a researcher all along, publishing papers and practically finding new ways to solve real world problems. He has also been an Entrepreneur and founding member of a startup that was successfully acquired by Oracle.
LLMs and Ontologies for Precision NERC(Tutorial)
Some of our confirmed sessions
TALK: Building a Data-Driven Workforce
TALK: Making Private Data Open and Enhancing Decision-Making through Digital Atlases
TALK: Human-Friendly, Production-Ready Data Science with Metaflow
TALK: Responsible AI In Practice
TUTORIAL: LLMs and Ontologies for Precision NERC (Named Entity Recognition & Classification)
KEYNOTE: Infuse Generative AI in your Apps Using Azure OpenAI Service
TALK: Exploring the Generative AI Landscape: From Basics to Hands-on Applications
TALK: Framework and Lessons Learned from Building a Generative AI Application
TUTORIAL: Troubleshooting Retrieval-Augmented Generation
Workshop: Big Data Analysis with PySpark
For more sessions please check the schedule page here
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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
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