Aruna Pattam is a seasoned AI leader with over 22 years of experience in data and analytics. Aruna has completed her master’s in data science, computer science and has an MBA. She has extensive experience in delivering solutions using data analytics, artificial intelligence, and machine learning. Earlier, she has held many technical and executive leadership roles in Commonwealth Bank of Australia, Westpac, AMP financial services, and SAS Australia.
Aruna is a Global AI Thought Leader, and she speaks, mentors, blogs about AI, and vlogs for the purpose of educating and raising awareness in the business and general public. Her most recent awards include “AI Global Ambassador 2022” by Swiss Cognitive World-Leading AI Network, “AI Changemaker Leader 2022″, “Presidents Award 2022” by 3AI a leading AI & Analytics community, “The Most Admired Global Indians 2021” by Passion Vista – Global Magazine. You can follow Aruna’s work on AI in her LinkedIn, YouTube Channel, and Website.
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)
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.
Jeet is an experienced Data Science professional carrying 7+years of applied Industrial experience in Machine Learning, Deep Learning, Computer Vision & Natural Language Processing across multiple domains. He is right now working as Manager – Data Science in Analytics & Innovation (Ai) team at United Airlines, one of the major American airlines to solve Aviation analytics problems. Within his ~4 years at United he has worked on designing and architecting Computer Vision & NLP powered capabilities to save thousands of repetitive man hours & Millions of dollars in savings. In past he has worked with Tata Consultancy Services in its Analytics and insights(A&I) unit to build analytics capabilities across multiple domains. He follows various MOOCs and research communities, and his curiosity keeps pushing him to learn and explore more. A firm believer in giving back to the community and gives webinars/career coaching and 1-1 mentorship sessions on his journey to data science, the latest trends in the industry, and general advice to beginners and aspirants to help propel their journey into data science.
Hui Xiang Chua is Senior Data Scientist at Dataiku, helping enterprises with data democratization and enabling them to build their own path to AI. Dataiku is a 2x Gartner Magic Quadrant Leader for Data Science and Machine-Learning Platforms (as of 2021).
She has both public and private experiences solving problems using data, namely over six years in the public service and two years in the media industry. She was also previously an instructor with General Assembly.
In 2017, she was accepted to the Data Science for Social Good Fellowship and was mentored by Rayid Ghani, Chief Scientist of the Obama for America campaign in 2012. For bringing data science into a high school’s curriculum, Hui Xiang was a recipient of the KDD Impact Program award by SIGKDD, the Association for Computing Machinery’s special interest group on knowledge discovery and data mining. She also runs a data science blog called Data Double Confirm that was recognised as 2018/2019 Top 100 Data Science Resources on MastersInDataScience.com.
Hui Xiang holds a B.Sc.(Sons) in Statistics and M.Sc. in Business Analytics from National University of Singapore.
Aditya Bhattacharya is an Explainable AI Researcher at KU Leuven with an overall experience of 7 years in Data Science, Machine Learning, IoT & Software Engineering. Prior to his current role, Aditya has worked in various roles in organizations like West Pharma, Microsoft & Intel to democratize AI adoption for industrial solutions. As the AI Lead at West Pharma, he had contributed to forming the AI Centre of Excellence, managing & leading a global team of 10+ members focused on building AI products. He also holds a Master’s degree from Georgia Tech in Computer Science with ML and a Bachelor’s degree from VIT University in ECE. Aditya is passionate about bringing AI closer to end- users through his various initiatives for the AI community. He has also authored a book “Applied Machine Learning Explainability Techniques”
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.
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