Limited Discount Offer Ends in
Responsible AI and Social Good
The Responsible AI track brings together top data ethicists to provide a practical, ethical framework for technologists to develop machine learning systems.
Using case studies and existing frameworks, we’ll give you the tools to build out your own ethical approach to realize the best outcomes while deploying machine learning in the real world.
You will be able to responsibly design human-in-the-loop review processes, monitor bias, build trust transparency, and develop explainable machine learning systems to ensure data and model security.
ODSC APAC Virtual Conference 2024
Register your InterestWhat You'll Learn
Talks + Workshops + Special Events on these topics:
AI Ethics and Bias
Federated Analytics
Federated Learning for User Privacy
AI for Climate Change, Social Good
Reproducability
Explainable AI: heatmap-based explanations
Explainable AI: human in the loop
Uncertainty in AI
Fairness in Machine Learning
Algorithmic Decision Making
Fairness in Predictive Modeling
and more…
Responsible AI and Social Good
The Responsible AI track brings together top data ethicists to provide a practical, ethical framework for technologists to develop machine learning systems.
Using case studies and existing frameworks, we’ll give you the tools to build out your own ethical approach to realize the best outcomes while deploying machine learning in the real world.
You will be able to responsibly design human-in-the-loop review processes, monitor bias, build trust transparency, and develop explainable machine learning systems to ensure data and model security.
ODSC APAC Virtual Conference 2024
Register your InterestSome of Our Current Responsible AI and Social Good Speakers
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)
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.
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)
Rohit Sroch
Rohit Sroch is a Sr. AI Scientist at Artificial Intelligence Labs at Course5 Intelligence, with over 5 years of experience in the Natural Language Processing and Speech domains. He plays a pivotal role in conceptualizing and developing AI systems for the Course5 Products division. Simultaneously, he maintains an active involvement in his research endeavors, leading to the publication of several research papers in recent years. Also, his fervent interest in the constantly evolving landscape of AI drives him to engage in continuous research and stay abreast of the latest technologies.
Minsoo Thigpen
Minsoo is a Senior Product Manager at Microsoft Azure Machine Learning designing and building out Responsible AI tools for data scientists. She’s worked with OSS tools such as InterpretML, Fairlearn, Responsible AI Toolbox and contributed to the UX of the Responsible AI dashboard now released in Azure Machine Learning. She has bachelor’s degrees in Applied Mathematics and Painting from Brown University and Rhode Island School of Design (RISD). Coming from an interdisciplinary background with experience in building machine learning models and products, analyzing data, and designing UX, she is always finding work at the intersection of AI/ML, design, and social sciences to empower data and ML practitioners to work ethically and responsibly end-to-end.
Mehrnoosh Sameki, PhD
Mehrnoosh Sameki is a principal PM manager at Microsoft, where she leads emerging Responsible AI technology and tools and for the Azure Machine Learning platform. She has cofounded Error Analysis, Fairlearn and Responsible AI Toolbox and has been a contributor to the InterpretML offering. She earned her PhD degree in computer science at Boston University, where she currently serves as an adjunct assistant professor, offering courses in responsible AI. Previously, she was a data scientist in the retail space, incorporating data science and machine learning to enhance customers’ personalized shopping experiences.
Why Attend
Accelerate and broaden your knowledge of key areas in Responsible AI
With numerous introductory level workshops, get hands-on experience to quickly build up your skills
Post-conference, get access to recorded talks online and learn from over 100+ high-quality recording sessions that let you review content at your own pace
Take time out of your busy schedule to accelerate your knowledge of the latest advances in data science
Learn directly from world-class instructors who are the authors and contributors to many of the tools and languages used in data science today
Meet hiring companies, ranging from hot startups to Fortune 500, looking to hire professionals with data science skills at all levels
Get speaker insights and training in AI frameworks such as TensorFlow, MXNet, PyTorch, Spark, Storm, Drill, Keras, and other AI platforms
Connect with peers and top industry professionals at our many networking events to discover your next job, service, product, or startup.
Who should attend
The Responsible AI Track is where industry’s top creative minds gather to discuss and shape the most challenging social problems. Whether you are an expert, or just starting your journey, this is the conference for you.
Data scientists looking to build an understanding of ethical intelligent machines
Data scientists seeking to investigate and define potential adverse biases and effects, mitigation strategies, fairness objectives and validation of fairness
Anyone interested in understanding areas such as fairness, safety, privacy and transparency in artificial intelligence and data
Business professionals and industry experts looking to understand data science ethics in practice
Software engineers and technologists who need to develop algorithms to solve fundamental algorithmic fairness problems
CTO, CDS, and other managerial roles that require a bigger picture view of data science
Technologists in the field of AI Fairness and others looking to learn mitigation strategies, algorithmic advances, fairness objectives, and validation of fairness
Students and academics looking for more practical applied training in data science tools and techniques
ODSC Newsletter
Stay current with the latest news and updates in open source data science. In addition, we’ll inform you about our many upcoming Virtual and in person events in Boston, NYC, Sao Paulo, San Francisco, and London. And keep a lookout for special discount codes, only available to our newsletter subscribers!