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Speaker Profile

X Topic Abstract

In the session i will explain practical examples of how we do it in our organisation.

Speaker Profile

I am an Associate Director with more than 9 years’ experience in data and analytics. I am part of Deloitte Analytics, a cross-functional team with a focus on embedding data and analytics and AI in organisations across Africa. I am also responsible for the Digital Transformation team in Risk Advisory with a focus on exponential technologies, AI, Digitisation and rapid prototyping. I am passionate to help people on their journey to enable their company to become a data driven organisation, and have a passion for moving Africa into the fourth industrial revolution and enabling the true potential.

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Key takeaways from your session: Applications of data science methods to modern financial crimes and fraud.

Speaker Profile

Currently a lead data scientist heading a data science department which deals mostly with financial crimes and compliance analytics on a day to day basis.

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As more and more AI/ML models being developed, it becomes a critical topic on how to manage and governance your models. Our solution is to provide a centralized platform with one simple user inteface for data exploration, automated ML, model deployment, and drfit tracking; democrotize the access to data and enable the company to quickly operationalize the data projects.

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Hiring, developing and retaining a highly talented team of data scientists and machine learning engineers requires both employees and leaders to bring their best technical, business and communication skills. When leaders and data scientists stay current on the latest technology trends and are open to explore unpaved pathways, opportunities for innovation arise. Diversity and inclusion are keys to innovation, success, and digital transformation

Speaker Profile

Working directly with the Chief Data Officer for IBM’s Cloud and Cognitive businesses,
Serena is currently driving IBM’s ongoing internal transformation and helping the business to succeed, with the use of data science, machine learning, and AI.

As part of her commitment to forwarding data science as a profession, she is guiding a team of Data Science Apprentices who joined the program with no previous coding, educational, nor professional background in analytics. She is contributing to upskill other IBMers interested in transitioning to a career in data science, machine learning, and AI. Serena is also advising professors and instructors in the NYC area on ways to incorporate data science in their curricula, while her team is mentoring college students, with the goal of improving technical skills overall, and reducing the data science skills gap.

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Key takeaways from my session:
how to use data in Manufacturing

Speaker Profile

Avery Smith is an innovative data science who loves to help make smart decisions with the power of data.

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In a fast-growing company like HRS, knowing how to use Data Analytics, Data Science and Machine-Learning is not only about hiring the right data people and work on the right problem but also how to setup the function and spread best knowledge and practices related to data and associated technology across the organization.

In this talk I will use concrete examples of problems faced in setting up and growing a data function and how we are solving it at HRS, in particular in times like during the COVID-19 crisis.

Speaker Profile

Sébastien is the CDO of the HRS Group, the leading global Business Travel company. A former Professor in Astrophysics and a Data Scientist, he has headed several Data departments, focusing on creating a measurable business impact leveraging data related technology and machine learning

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Speaker Profile

X Topic Abstract

In the session i will explain practical examples of how we do it in our organisation.

Speaker Profile

I am an Associate Director with more than 9 years’ experience in data and analytics. I am part of Deloitte Analytics, a cross-functional team with a focus on embedding data and analytics and AI in organisations across Africa. I am also responsible for the Digital Transformation team in Risk Advisory with a focus on exponential technologies, AI, Digitisation and rapid prototyping. I am passionate to help people on their journey to enable their company to become a data driven organisation, and have a passion for moving Africa into the fourth industrial revolution and enabling the true potential.

X Speaker Profile

I am also CompTIA National AI Council Advisory Member

My specialities : Familiar with C/C++, Unix, Java, Python, Django, SQL, Storm, Spark, Hadoop

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Understanding the challenges in applying AI at scale for online decision making, and the opportunities for improved products and architectures that lie in solving them.

There is a ton of resources available on how to train machine-learned models, but how do you make use of them in real solutions once they are trained? If you need to evaluate models over big data sets and scale to thousands or millions of evaluations per second, such as in online recommender and ad systems, this is a very hard challenge. A few of the few biggest internet companies in the world has proprietary solutions for solving this problem, but until recently it has been out of reach for anybody else.

This talk will explain why this is a hard problem, show some of the things that become possible once a solution is available, and describe how we use the open source Vespa.ai platform to solve this problem in some real use cases including the world's third largest ad network.

Speaker Profile

Jon Bratseth is a VP architect in the Big Data and AI group of Verizon Media, and the architect and one of the main contributors to Vespa.ai, the open big data serving engine. Jon has 20 years experience as architect and programmer on large distributed systems, and a frequent public speaker. He has a master in computer science from the Norwegian University of Science and Technology.

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Key takeaways from my session:
In this session, we will walk through the process of succeeding in the analytics journey. We will examine the best approach to building a corporate analytics function and a high performing analytics team. We will describe and discuss the Artisanal and Modular approaches to hiring and building a team. We will also examine how to evolve from the Artisanal and/or Modular model to a Hybrid model. We will examine how to manage a high performing analytics team to deliver analytical models and applications that are implemented and used in daily operations to improve organizational efficiency and effectiveness. Be ready to ask questions, this will be an interactive and open discussion.
Format can be any of the below:
· 45 minutes Presentation with real life examples

Speaker Profile

John is an international technology executive with over 30 years of experience in the business intelligence and advanced analytics fields. Currently, John is responsible for the global Advanced Analytics & Artificial Intelligence team and efforts at CSL.
Prior to CSL, John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics. Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.
John is the author of the new book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement. The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams. The book outlines how to engage with executives and senior managers. How to select and undertake analytics projects that change and improve how a business operates.
John is co-author of the bestselling book – Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017. Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives and driving change in business operations through data and applied analytical applications.
Mr. Thompson’s technology expertise includes all aspects of advanced analytics and information management including – descriptive, predictive and prescriptive analytics, artificial intelligence, analytical applications, deep learning, cognitive computing, big data, data warehousing, business intelligence systems, and high performance computing.
One of John’s primary areas of focus and interest has been to create innovative technologies to increase the value derived by organizations around the world.
John has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run - sales, marketing, consulting, support and product development organizations.
He is a technology leader with expertise and experience spanning all operational areas with a focus on strategy, product innovation, growth and efficient execution.
Thompson holds a Bachelor of Science degree in Computer Science from Ferris State University and a MBA in Marketing from DePaul University.

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I am interested in presenting a brief technical summary of machine learning methods for inferring causality. Specifically machine learning methods for time series and dynamical systems causality.

Speaker Profile

Experienced Data Scientist with a demonstrated history of working in the information technology and services industry. Strong research professional with dual Bachelor's degrees in Cognitive and Computer Science from UC Berkeley, and with a Master's degree in Statistics from Stanford University. Skilled in distributed programming via Apache Spark, Bayesian modelling, deep learning, convex optimization, and stochastic differential equations.

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The inevitable set-backs of being a machine learning practitioner and how to over-come them

Speaker Profile

Mkhuseli is an seasoned data scientist that has worked in the fields of Robotics & AI, Law and Actuarial Science. With a back-ground in Law, he is a self-taught machine learning practitioner with a wealth of experience in the adoption of data science in many fields. Throughout the years he has had a hand in innovative break-through's in all these fields, most notably creating one of the first applications of AI for South African Case Law. He has taught at Data Science workshops, consulted for some of the leading Actuaries in the country and created the first front-end interface environment for R Packages. Mkhuseli is currently Vice President of Data Science at the ABSA Group's Internal Audit.

X Topic Abstract

Speaker Profile

X Topic Abstract

In the session i will explain practical examples of how we do it in our organisation.

Speaker Profile

I am an Associate Director with more than 9 years’ experience in data and analytics. I am part of Deloitte Analytics, a cross-functional team with a focus on embedding data and analytics and AI in organisations across Africa. I am also responsible for the Digital Transformation team in Risk Advisory with a focus on exponential technologies, AI, Digitisation and rapid prototyping. I am passionate to help people on their journey to enable their company to become a data driven organisation, and have a passion for moving Africa into the fourth industrial revolution and enabling the true potential.

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The space race was a EEUU – Soviet Union competition to conquer the space. This competence helped to develop space technology in an incredible manner, developing other derivative technologies as a side effect.
This race was full of success in both sides, achieving goals that seemed impossible in record time.
From this space race we can learn some lessons that we can apply to our Machine Learning projects to have a bigger success rate in a limited amount of time.

Speaker Profile

Diego is the Machine Learning Manager at RavenPack, in Marbella, (Málaga, Spain). He is a teacher in the Big Data & Analytics master for ESESA IMF, an Antonio de Nebrija University title. He also collaborated teaching in the Big Data Executive Program at Escuela de Organización Industrial (EOI), a Spanish business school where he has been also a Big Data mentor. He is passionate about Machine Learning & Artificial Intelligence, and he loves to share this passion speaking in international congresses & seminars, being the opening or closing keynoter in some important ones.

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- Business Analytics nature is typicaly complex and often expensive. Business Owners needs to rely either on analytical department or on their "gut feeling" while running the business.

With 20 years of anayltics experience, we will be presenting (still beta version) an user-friendly Advanced Analytics solution serving Business Owners as their personal assistant.

Get clear info on blind-spots of your business in One Click. Stop money leakage & boost business perfromance where needed.

Stop overpaying underperfroming salesmans. Stop producing or ordering certain products and put money on "growing stars".

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Presentation on rise of computer vision applications in various industries and a code walk through of image classification example. Challenges in Time series analysis.

Speaker Profile

Niharika Karia is a Data Scientist at Aspen Technologies based in Boston. She has a master's degree in Data Science. She is passionate about environmental sustainability. She uses machine learning for building predictive models to detect anomalies and failures in industrial operation.

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Bert and other deep learning technologies need to be adapted to work for long document classification

Speaker Profile

Irina Matveeva is Chief of Data Science and AI at Reveal Data, an eDiscovery company based in Chicago. She is also Adjunct Professor at the Illinois Institute of Technology where she teaches Data Mining. Matveeva earned her PhD in Computer Science from the University of Chicago and her professional expertise includes Natural Language and Machine Learning technologies. Matveeva frequently presents on the subject of AI and NLP. She has been a volunteer mentor for the Data Science for Social Good fellowship.

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Open Source Software (OSS) is more prevalent than in any other era and continues to grow in the Artificial Intelligence, Machine Learning, and Deep Learning space. In this session, we are going to review the latest status of OSS for Machine Learning (ML) for the different hardware platforms, specifically, mainframe technology who once upon a time was considered old. Today it has become a new, modern, and ideal high-performant platform for ML models and ML applications. Tensorflow, Python, Pytorch, Spark, and many other widely used OSS have become the building blocks of ML applications and are available for all Linux distributions across multiple platforms. This session will also cover how to participate in those open-source projects and how to contribute back to open-source communities.

Speaker Profile

Javier Perez leads the open-source program strategy for the IBM Z and LinuxONE ecosystem at IBM. Javier has been in the open-source, cloud, SaaS, and mobile industries for 20+ years. He has been working directly with Open Source Software (OSS) for over 10 years, more recently leading product strategy of the Software Composition Analysis product line at Veracode. Prior to Veracode, Javier was at Axway leading a successful open source project, Appcelerator, and at Red Hat where he was Director of Product Management driving the OpenShift-based Mobile Application Platform offering for developers and enterprises including containerized applications. Javier has had the opportunity to speak at webinars and conferences all over the world covering open source, AI, security, cloud, and application development topics. Javier has held leadership positions in Product Management and Sales Engineering for different startups, leading successful product exits and product integrations post-acquisition. Javier holds an honors degree in Computer Systems and an MBA.