Here is (finally) the full schedule of AI on Pi Day, with the main time zones. Under the table, you will find the details of each talk and the bio of each speaker, ordered alphabetically by the full name of the speaker.

Summary table

London / GMTTitleSpeakerNew YorkSan FranciscoBarcelona / ParisNew DelhiTaipei /PerthTokyoSydney
Thu 12:00 midnightWelcomeJean-Georges Perrin, Ralf RoeberWed 8:00 pm *Wed 5:00 pm *Thu 1:00 amThu 5:30 amThu 8:00 amThu 9:00 amThu 11:00 am *
Thu 12:30 amUnlock The Secrets to Delivering Captivating Presentations!Gary LaffertyWed 8:30 pm *Wed 5:30 pm *Thu 1:30 amThu 6:00 amThu 8:30 amThu 9:30 amThu 11:30 am *
Thu 1:00 amElevate Your Analytics Game: Power BI vs. Cognos Analytics, Unraveling the DifferencesMichael BernaicheWed 9:00 pm *Wed 6:00 pm *Thu 2:00 amThu 6:30 amThu 9:00 amThu 10:00 amThu 12:00 noon *
Thu 1:30 amData Testing: Moving towards being proactivePeter FlookWed 9:30 pm *Wed 6:30 pm *Thu 2:30 amThu 7:00 amThu 9:30 amThu 10:30 amThu 12:30 pm *
Thu 2:00 amBuilding LLM apps with LLama CPP in 15 minutesNicholas RenotteWed 10:00 pm *Wed 7:00 pm *Thu 3:00 amThu 7:30 amThu 10:00 amThu 11:00 amThu 1:00 pm *
Thu 2:30 amPrompt Engineering for TestersRahul ParwalWed 10:30 pm *Wed 7:30 pm *Thu 3:30 amThu 8:00 amThu 10:30 amThu 11:30 amThu 1:30 pm *
Thu 3:00 amAI-Generated Creativity: Pushing the Boundaries of Artistic Expression with Generative Adversarial Networks (GANs)Sahaj VaidyaWed 11:00 pm *Wed 8:00 pm *Thu 4:00 amThu 8:30 amThu 11:00 amThu 12:00 noonThu 2:00 pm *
Thu 3:30 amWhy Data is critical to being a successful AI/ML Product ManagerAmritha Arun Babu MysoreWed 11:30 pm *Wed 8:30 pm *Thu 4:30 amThu 9:00 amThu 11:30 amThu 12:30 pmThu 2:30 pm *
Thu 4:00 amA Data Scientist’s Journey from Zero to Data “Hero”Edwin Ricardo Chuy QuanThu 12:00 midnight *Wed 9:00 pm *Thu 5:00 amThu 9:30 amThu 12:00 noonThu 1:00 pmThu 3:00 pm *
Thu 4:30 amHiDeNN (Hierarchical Deep Learning Neural Network): A computational science and engineering in AI architectureAbhishek TripathiThu 12:30 am *Wed 9:30 pm *Thu 5:30 amThu 10:00 amThu 12:30 pmThu 1:30 pmThu 3:30 pm *
Thu 5:00 amConceptual model of Data Quality of Service as CodeJarkko MoilanenThu 1:00 am *Wed 10:00 pm *Thu 6:00 amThu 10:30 amThu 1:00 pmThu 2:00 pmThu 4:00 pm *
Thu 5:30 amTechnology Innovation ExpertOr PelachThu 1:30 am *Wed 10:30 pm *Thu 6:30 amThu 11:00 amThu 1:30 pmThu 2:30 pmThu 4:30 pm *
Thu 6:00 amHow to get help from the AI assistant and Watson Exploration in Cognos with Customer succes storiesRikke JacobsenThu 2:00 am *Wed 11:00 pm *Thu 7:00 amThu 11:30 amThu 2:00 pmThu 3:00 pmThu 5:00 pm *
Thu 6:30 amUsing CognosPaul MendelsonThu 2:30 am *Wed 11:30 pm *Thu 7:30 amThu 12:00 noonThu 2:30 pmThu 3:30 pmThu 5:30 pm *
Thu 7:00 amTransactional gravity is pulling AI towards the mainframeErik WeylerThu 3:00 am *Thu 12:00 midnight *Thu 8:00 amThu 12:30 pmThu 3:00 pmThu 4:00 pmThu 6:00 pm *
Thu 7:30 amDysrationalia in AIAtanas IlievThu 3:30 am *Thu 12:30 am *Thu 8:30 amThu 1:00 pmThu 3:30 pmThu 4:30 pmThu 6:30 pm *
Thu 8:00 amAI for better AI – Authentic Intelligence for Better Approximated IntelligenceLalitkumar BhamareThu 4:00 am *Thu 1:00 am *Thu 9:00 amThu 1:30 pmThu 4:00 pmThu 5:00 pmThu 7:00 pm *
Thu 8:30 amCan we stop that BS about Data Observability?Andy PetrellaThu 4:30 am *Thu 1:30 am *Thu 9:30 amThu 2:00 pmThu 4:30 pmThu 5:30 pmThu 7:30 pm *
Thu 9:00 amOptimizing Lakehouse Strategies with the Modern Data StackVincent HeuschlingThu 5:00 am *Thu 2:00 am *Thu 10:00 amThu 2:30 pmThu 5:00 pmThu 6:00 pmThu 8:00 pm *
Thu 9:30 amFerretDB from scratch – a truly open-source alternative for MongoDBMarcin GwozdzThu 5:30 am *Thu 2:30 am *Thu 10:30 amThu 3:00 pmThu 5:30 pmThu 6:30 pmThu 8:30 pm *
Thu 10:00 amData quality: prevention is better than the cureAndrew JonesThu 6:00 am *Thu 3:00 am *Thu 11:00 amThu 3:30 pmThu 6:00 pmThu 7:00 pmThu 9:00 pm *
Thu 10:30 amFrom slums of Mumbai to Germany, my story in TechSantosh YadavThu 6:30 am *Thu 3:30 am *Thu 11:30 amThu 4:00 pmThu 6:30 pmThu 7:30 pmThu 9:30 pm *
Thu 11:00 amIBM Maximo Application Suite & Cognos Analytics, already a happy marriage since 2012!Jan-Willem SteurThu 7:00 am *Thu 4:00 am *Thu 12:00 noonThu 4:30 pmThu 7:00 pmThu 8:00 pmThu 10:00 pm *
Thu 11:30 amThe Intersection of Graphs and Language ModelsAnthony AlcarazThu 7:30 am *Thu 4:30 am *Thu 12:30 pmThu 5:00 pmThu 7:30 pmThu 8:30 pmThu 10:30 pm *
Thu 12:00 noonBusiness Intelligence and Data Science – Merging both approaches and breaking the silos in consumption, processes and governanceMaximililan BurkardtThu 8:00 am *Thu 5:00 am *Thu 1:00 pmThu 5:30 pmThu 8:00 pmThu 9:00 pmThu 11:00 pm *
Thu 1:00 pmYour ChatBot Pal is Useful and Fun, but Are They Trustworthy?Apostol VassilevThu 9:00 am *Thu 6:00 am *Thu 2:00 pmThu 6:30 pmThu 9:00 pmThu 10:00 pmFri 12:00 midnight *
Thu 1:30 pmHuman AI for StrategyChristophe BissonThu 9:30 am *Thu 6:30 am *Thu 2:30 pmThu 7:00 pmThu 9:30 pmThu 10:30 pmFri 12:30 am *
Thu 2:00 pmAI Alliance and Open Source AI: IBM’s strategy for staying the AI leaderBill HigginsThu 10:00 am *Thu 7:00 am *Thu 3:00 pmThu 7:30 pmThu 10:00 pmThu 11:00 pmFri 1:00 am *
Thu 2:30 pmThu 10:30 am *Thu 7:30 am *Thu 3:30 pmThu 8:00 pmThu 10:30 pmThu 11:30 pmFri 1:30 am *
Thu 3:00 pmYin and Yang – How to balance data access with data securityBart vandekerckhoveThu 11:00 am *Thu 8:00 am *Thu 4:00 pmThu 8:30 pmThu 11:00 pmFri 12:00 midnightFri 2:00 am *
Thu 3:30 pmFrom prototype to value-generating AI model: How to ensure AI governance at financial service providers through MLOps practicesFabian ForthmannThu 11:30 am *Thu 8:30 am *Thu 4:30 pmThu 9:00 pmThu 11:30 pmFri 12:30 amFri 2:30 am *
Thu 4:00 pmData contracts are good for AIJean-Georges PerrinThu 12:00 noon *Thu 9:00 am *Thu 5:00 pmThu 9:30 pmFri 12:00 midnightFri 1:00 amFri 3:00 am *
Thu 4:30 pmBring order to chaosKarl-Oskar BrännströmThu 12:30 pm *Thu 9:30 am *Thu 5:30 pmThu 10:00 pmFri 12:30 amFri 1:30 amFri 3:30 am *
Thu 5:00 pmLessons Learned on a Generative-AI JourneyEric BrodaThu 1:00 pm *Thu 10:00 am *Thu 6:00 pmThu 10:30 pmFri 1:00 amFri 2:00 amFri 4:00 am *
Thu 5:30 pmGetting Data ROI Right: Tech and Business CollideKim ThiesThu 1:30 pm *Thu 10:30 am *Thu 6:30 pmThu 11:00 pmFri 1:30 amFri 2:30 amFri 4:30 am *
Thu 6:00 pmPreparing for the De-Peopling of the White Collar WorkforceKaren KilroyThu 2:00 pm *Thu 11:00 am *Thu 7:00 pmThu 11:30 pmFri 2:00 amFri 3:00 amFri 5:00 am *
Thu 6:30 pmData Contracts Bring Us Together: Improving Access and Understanding Through InterfacesChris FoyerThu 2:30 pm *Thu 11:30 am *Thu 7:30 pmFri 12:00 midnightFri 2:30 amFri 3:30 amFri 5:30 am *
Thu 7:00 pmBoosting Similarity Search With Real-time Stream Processing and MLFawaz GhaliThu 3:00 pm *Thu 12:00 noon *Thu 8:00 pmFri 12:30 amFri 3:00 amFri 4:00 amFri 6:00 am *
Thu 7:30 pmBI in the Age of AIRyan DolleyThu 3:30 pm *Thu 12:30 pm *Thu 8:30 pmFri 1:00 amFri 3:30 amFri 4:30 amFri 6:30 am *
Thu 8:00 pmThe Fraud Hunter’s Playbook: Real-Time Detection Challenges and TacticsFawaz GhaliThu 4:00 pm *Thu 1:00 pm *Thu 9:00 pmFri 1:30 amFri 4:00 amFri 5:00 amFri 7:00 am *
Thu 8:30 pmElevating Your Voice: Strategies for Analytics Professionals to Command Executive AttentionHeather L. ColeThu 4:30 pm *Thu 1:30 pm *Thu 9:30 pmFri 2:00 amFri 4:30 amFri 5:30 amFri 7:30 am *
Thu 9:00 pmFireside chat with Zhamak Dehghani & Jean-Georges PerrinZhamak Dehghani, Jean-Georges PerrinThu 5:00 pm *Thu 2:00 pm *Thu 10:00 pmFri 2:30 amFri 5:00 amFri 6:00 amFri 8:00 am *
Thu 9:30 pmAI for large scale crop classificationEduardo MoyaThu 5:30 pm *Thu 2:30 pm *Thu 10:30 pmFri 3:00 amFri 5:30 amFri 6:30 amFri 8:30 am *
Thu 10:00 pmIBM Cognos Analytics REST API gives Super Power: Building Fast, and Visually Impressive DashboardsRalf RoeberThu 6:00 pm *Thu 3:00 pm *Thu 11:00 pmFri 3:30 amFri 6:00 amFri 7:00 amFri 9:00 am *
Thu 10:30 pmChat as a growth opportunity, challenges and opportunitiesPaul CortellesiThu 6:30 pm *Thu 3:30 pm *Thu 11:30 pmFri 4:00 amFri 6:30 amFri 7:30 amFri 9:30 am *
Thu 11:00 pmIgnore Previous Instructions: Prompt Injection in the Real WorldEric AllenThu 7:00 pm *Thu 4:00 pm *Fri 12:00 midnightFri 4:30 amFri 7:00 amFri 8:00 amFri 10:00 am *
Thu 11:30 pmKnowledge Graph Powered RAGEric BrodaThu 7:30 pm *Thu 4:30 pm *Fri 12:30 amFri 5:00 amFri 7:30 amFri 8:30 amFri 10:30 am *

Details of talks and bio of speakers

Here are the details of each talk and the biography of each speaker, ordered alphabetically by the speaker’s full name.

HiDeNN (Hierarchical Deep Learning Neural Network): A computational science and engineering in AI architecture

Target audience: Individuals with a background in computational science and engineering who are interested in AI architecture.

Prerequisites: Basic knowledge of neural networks and computational science.

What people will learn:
– Understanding the concept of hierarchical deep learning neural networks (HiDeNN)
– Architecture and design principles of HiDeNN
– Applications of HiDeNN in computational science and engineering
– Techniques for training and optimizing HiDeNN models
– Evaluating the performance and accuracy of HiDeNN
– Current trends and future directions in HiDeNN research and development.

Speaker: Abhishek Tripathi

As a seasoned Director of Engineering, I am passionate about driving innovation, fostering collaboration, and leading high-performing teams to deliver cutting-edge solutions. With a proven track record of success in steering complex engineering projects from concept to completion, I thrive in dynamic environments where creativity meets technical excellence.

Why Data is critical to being a successful AI/ML Product Manager

Data is the Brainpower: AI/ML products learn and grow from data, just like our brains. Without high-quality data, your product won’t reach its full potential – think of it as building a powerful engine without any fuel. This talk will unveil the different types of data needed and how to use them effectively.

Data Fuels Success: Imagine personalizing experiences, optimizing performance, and even predicting trends – all thanks to the power of data! This talk will equip you with the knowledge to unlock these benefits and transform your AI/ML product into an intelligent powerhouse.

Speaker: Amritha Arun Babu Mysore

Amritha is an accomplished technology leader with over 12 years of experience spearheading product innovation and strategic initiatives at both large enterprises and rapid-growth startups.

Leveraging her background in engineering, supply chain, and business, Amritha has led high-performing teams to deliver transformative solutions solving complex challenges. She has driven product road mapping, requirements analysis, system design, and launch execution for advanced platforms in domains like machine learning, logistics, and ecommerce.

Throughout her career, Amritha has been relied upon to envision the future, mobilize resources, and achieve business success through technology. She has been instrumental in helping shape product strategy across diverse sectors, including retail, software, semiconductor manufacturing, and cloud services.

Amritha excels at understanding diverse customer needs and leading data-driven efforts that maximize value delivery. Her passion and talents have led to her spearheading many greenfield projects taking concepts from ideation to national scale within aggressive timeframes.

With her balance of technical depth, business acumen, and bold leadership, Amritha is an invaluable asset ready to tackle dynamic challenges and capitalize on new opportunities. She is a principled, solutions-focused leader committed to empowering people, organizations, and ideas.

Data quality: prevention is better than the cure

Many of us spend a lot of our time dealing with poor quality data, and any solution we put in place tends to be reactive or yet another workaround implemented in an increasingly complex data pipeline. But this is proving ineffective and expensive, and preventing organisations from realising the value of their data, when that’s becoming more important than ever.

What if we could prevent data quality issues at source, where it is cheapest and most effective?

We can, and in this talk, I’ll show you how.

Speaker: Andrew Jones

Andrew Jones is a Principal Engineer at GoCardless and author of the recently published and well received book “Driving Data Quality with Data Contracts”. He is a regular speaker and writer, and passionate about helping organisations get the most value from their data.

Can we stop that BS about Data Observability?

In this talk, Andy will dissect the misconceptions surrounding data observability perpetuated by misaligned marketing content from vendors and overzealous promises from well-funded startups hungry for rapid growth.

Explore why the concept of data observability is sinking into the “valley of disillusion” as data teams struggle to meet inflated expectations while grappling with the pressure to reduce costs and deliver on lofty promises.

Andy will provide a candid assessment of the current landscape, offering practical insights and actionable strategies to help recalibrate expectations and navigate the complexities of data observability.

Join us for a candid and insightful discussion that aims to demystify data observability and empower the people first and foremost!

Speaker: Andy Joseph Albert Petrella III, Lord of Slins, Vice Master of the House, Son of Archibaldo Armando Peppino Petrella II

Andy Petrella’s journey in the tech industry began in the realm of geospatial data mining and governance, where he conducted large-scale analytics with data sourced from diverse countries.

In 2011, transitioning to the realm of “big data,” Andy became a passionate advocate for Apache Spark, leading to the creation of the Spark Notebook and the establishment of a vibrant community comprising over 20,000 users.

Recognizing the challenges of data pipelines entering production without proper guardrails and devops practices, Andy founded Kensu to address these gaps. This endeavor evolved into the field of “Data Observability,” with Kensu offering a comprehensive Data Observability Platform and pioneering the concept of “Data Observability Officer as a Service.”

Andy is also the author of the O’Reilly title “Fundamentals of Data Observability” (FODO), released in 2023.

The Intersection of Graphs and Language Models

Large language models (LLMs) have rapidly advanced, displaying impressive abilities in comprehending and producing natural language text. These models can interpret semantic nuances, reason about scenarios, and generate remarkably coherent writing.

Simultaneously, across scientific domains and real-world systems, graph-structured data has become pervasive. Graphs naturally capture the intricacy found in networks — complex interdependencies, relationships, and interactions. Examples span social networks, protein interactions, public transport routes, and more.

This begs a fascinating question — how exactly can the capabilities of graphs and large language models intersect to create even more powerful AI systems? We examine three primary perspectives on this:

  1. Graphs as Context Providers
    Knowledge graphs contain factual information encoded as networks of interrelated entities and relationships. Techniques like Knowledge Graph Prompting improve LLMs by retrieving and appending relevant graph context to questions or prompts. This enhances answers with verified external knowledge, reducing the chances of hallucination or unsupported logical leaps. It cementively grounds LLMs in factual data.
  2. Graphs as Explicit Reasoning Topologies
    An emerging technique is employing graph pathways to deliberately guide and structure the LLM’s internal reasoning process. Examples include Tree/Graph/Chain-of-Thought, which model sequences of thoughts and refinements to solve problems. The topology itself shapes the analysis trajectory. This goes beyond merely using graphs as inputs — it directly influences the reasoning architecture.
  3. Using LLMs for Graph Tasks
    Finally, LLMs can be adapted to harness their vast knowledge for tackling graph problems using natural language formulations. This involves pre-training transformer architectures on massive graph data or framing analysis tasks as text prompts tailored for graph inputs and outputs.

The Synergistic Potential
This three-pronged approach underscores a collaborative synergy between graphs and LLMs. Graphs ground language models in complex factual data while providing an architectural framework for reasoning chains. Language models lend their expansive neural networks to unlock insights within structured data.

Speaker: Anthony Alcaraz

“But logic is not all; one needs one’s heart to follow an idea.” (Richard P. Feynman)

Passionate Data Science & AI Professional

Your ChatBot Pal is Useful and Fun, but Are They Trustworthy?

Attacks and mitigations for LLMs and Generative AI

Speaker: Apostol Vassilev

Research Manager, NIST.

Apostol Vassilev is a research manager in the Computer Security Division at NIST. His group’s research agenda covers a range of topics in Trustworthy and Responsible AI and Cybersecurity, with a focus on Adversarial Machine Learning (AML), Robust AI for Autonomous Vehicles, AI bias, meta-learning with large language models (LLMs), Multi-Party Threshold Cryptography, novel approaches to cybersecurity testing and measurement through automated machine-based methodologies.

Vassilev works closely with academia, industry, and government agencies on the development and adoption of standards in artificial intelligence and cybersecurity and contributes to national and international standards groups. Vassilev holds a Ph.D. in mathematics from Texas A&M University. He has authored over fifty scientific papers and holds five U.S. patents. His work has been profiled in the NIST Taking Measure Blog, VentureBeat, StateScoop, Fortune, Forbes, the Register, FedScoop, podcasts, webinars, and others. Apostol frequently speaks at conferences and contributes to research as a guest editor in scientific journals.

Dysrationalia in AI

Dysrationalia in Machine Learning Models

Speaker: Atanas Iliev

Atanas Iliev is passionate about exploring innovative platforms for AI and data. He is also passionate about prompt engineering. His latest work has brought him into the fields of AI ethics, data engineering, and data governance. In 2023, he joined the AIDA User Group and began providing weekly updates. He was elected as a member of the Board of Directors in 2024.

Before moving to Data and AI, Atanas had over 10 years of experience in the telecommunications industry, having worked for some of the largest companies in Europe and worldwide. He loves walking around lakes near Berlin, Germany, with his wife and kids. They enjoy spending time together outdoors.

Yin and Yang – How to balance data access with data security

Access Management is the most annoying part of data engineering. Who hasn’t heard this before? In a world that’s getting increasingly data hungry, data security workflows act like a waiter on barbiturates. Because data security technology isn’t made for how we work with data today, it creates slow access management processes that kill productivity and dreams.

In this session we will show what you can do to streamline data security to unlock more than 70% of your data for BI and GenAI.

Let’s slay the dreamkiller that is data security today.

Speaker: Bart vandekerckhove

As one of the co-founders of Raito, Bart is on a mission to balance data access with data security. I believe that data workers can get access to data in a faster and more secure way.
Before co-founding Raito, Bart was the senior product manager of privacy at Collibra.

AI Alliance and Open Source AI: IBM’s strategy for staying the AI leader


Speaker: Bill Higgins

VP, IBM watsonx Platform Engineering and Open Innovation

Data Contracts Bring Us Together: Improving Access and Understanding Through Interfaces

I will explain how I have used data contracts in my work to foster better understanding with the team that works on the application from which I am pulling data. I will also discuss how I am benefiting from the work that AIDAUG is doing for data contracts.

Speaker: Chris Foyer

Chris is a Data Engineer with Systematic in Denmark. He is working on solutions to use existing data from existing hospital workflow solutions to improve oversight and collaboration among staff. He also works on custom web-based visualizations that focus on portability to a wide array of devices.

Human AI for Strategy

Big data and noise are becoming a nuisance for companies, with devastating consequences that traditional decision Systems can not cope with. Thus, in the context of fiercer competition and growing uncertainties, Christophe will present decision intelligence systems to control its strategic environment better and help to anticipate and dig into Big data by intertwining human and machine intelligence.

Speaker: Christophe Bisson

Christophe BISSON, Ph.D is Scientific Director of the Msc “”International Strategy & Influence”” at SKEMA. He explores and develops innovative competitive intelligence and anticipatory systems augmented by machine learning. He received international and national awards for his work and won research funds from the American NSF, EU, etc. He lectures in Paris, Raleigh and Suzhou in graduate programs and provided trainings to top executives in the US, EU, ME and Asia.

Large Language Models in practice

  • Pros and Cons of LLMs.
  • Energy consumption and latency.
  • Interpretability or the lack thereof.
  • Transformer architecture (decoder-only) and attention mechanism.
  • Writing unit tests for LLMs.
  • Prompt design with LLMs.
  • Description of possible use cases, such as the transformation of unstructured data to structured data.
    -Sharing project experience with the GPT-3-5 model.

Speaker: Dr. Alessandro Brillante

Alessandro Brillante, PhD is a Managing Consultant with adesso SE. Alessandro obtained a PhD in theoretical astrophysics where he implemented numerical simulations of compact stars using Fortran. His main interests center around software architecture, data processing, statistics, and finance. With his team he has developed applications leveraging optical character recognition and language models. He advises banks, insurers and corporates with the maintenance and development of data driven applications.

AI for large-scale crop classification

We are going to talk about our models to make crop classification here in Jalisco.

Speaker: Eduardo Moya

Ulises Moya is a pioneering director in the AI field within the public administration in Mexico. Ulises’s expertise and commitment to responsible and ethical design have gained international recognition. Some of his projects were selected by GPAI(2020), Global UNESCO IRCAI Top 100 ( selected in Top-10) 2023, and GPAI scale-up solutions 2023, reflecting their contributions in the field of responsible AI, and ethics in real world problems.

Prior to his current role, Ulises contributed to the HPC and deep learning research at the Barcelona Supercomputing Center’s high-performance artificial intelligence group. His research achievements (more than 30 research papers) have led to his inclusion as a member of the National System of Researchers of CONACYT, holding level 1. Additionally, Ulises has successfully participated in robotics competitions as a mentor, with his teams winning several national (TMR) championships and achieving first and second place in Robocup Junior Superteam competitions.

Finally, Ulises was honored with the Juan Manuel Lozano Diploma by the Institute of Physics UNAM and with the Fulbright García-Robles grant, providing him with the opportunity to collaborate with the Quantitative Bioimaging Laboratory at the University of Texas in Dallas and the University of Texas Southwestern Medical Center.

A Data Scientist’s Journey from Zero to Data “Hero”

I am going to talk about my personal journey that took me from basic knowledge of data to taking to the Microsoft Certified: Fabric Analytics Engineer Associate certification exam in beta as well as my participation in the Hack Together: The Microsoft Fabric Global AI Hack hackathon that it will have finished a week and a half before Pi Day. I will share some of my experiences in the process and valuable resources as well as provide tips for anybody who is considering a career shift to deal with data.

Speaker: Edwin Ricardo Chuy Quan

A Data Scientist with six years of experience in a small retail business. Started learning with basic knowledge of Excel (no pivot tables) and have gradually learned about analytics and business intelligence to produce reports and dashboards using Microsoft Power BI. Presently, learning about Microsoft Fabric by already taking the Microsoft Certified: Fabric Analytics Engineer Associate certification exam in beta and now participating in the Hack Together: The Microsoft Fabric Global AI Hack hackathon.

Ignore Previous Instructions: Prompt Injection in the Real World

Prompt injection is more than just a buzzword. According to the Open Worldwide Application Security Project (OWASP), it’s the top vulnerability for Large Language Model (LLM) applications.

These attacks can have real-world consequences beyond just having a model say something it normally wouldn’t; they could enable unauthorized access to sensitive information or manipulate LLM behavior in unexpected ways.

In this talk we’ll dig into data from one of the most extensive LLM red-teaming efforts to date, and go over the taxonomy of prompt injection techniques that we discovered with our Gandalf and Mosscap prompt injection games, as well as some internal hackathon red teaming that lead to fun discoveries like an invisibility cloak for visual LLMs.

We’ll also explore some practical applications of these prompt injections against real production systems and discuss some steps you can take to mitigate the impact of prompt injections in your own LLM applications.

Speaker: Eric Allen

Eric Allen is a Developer Advocate for Lakera AI and currently calls Boston home. He’s spent time as a consultant, adjunct professor, VP, and individual contributor at companies ranging from a boutique design house to a Fortune 50 financial institution.

Other than software, he’s also developed a passion for Artificial Intelligence, User Experience, and Developer Experience.

When he’s not experimenting with Large Language Models, he’s probably playing with his doggo, Judge; cooking up something vegetarian; enjoying a craft beer; or traveling the world with his fianceé, Priyanka, and pretending that he’s a photographer.

Knowledge Graph Powered RAG

How to supercharge your Generative-AI RAG capabilities using Knowledge Graphs

Speaker: Eric Broda

Eric Broda is the president of Broda Group Software. Broda Group Software is a boutique consulting firm that helps firms accelerate their Data Mesh and Generative AI journey. Mr. Broda has designed/implemented Data Mesh, Generative AI, API, and Event Streaming solutions at global financial firms, international retailers, and climate change specialists, leading directly to radical improvements in time-to-market, customer engagement, and better/faster insights.

Lessons Learned on a Generative AI Journey

There are many obstacles on the road to a successful Generative-AI implementation. What are the lessons learned that will help you avoid those obstacles.

Speaker: Eric Broda

Eric Broda is the president of Broda Group Software. Broda Group Software is a boutique consulting firm that helps firms accelerate their Data Mesh and Generative AI journey. Mr. Broda has designed/implemented Data Mesh, Generative AI, API, and Event Streaming solutions at global financial firms, international retailers, and climate change specialists, leading directly to radical improvements in time-to-market, customer engagement, and better/faster insights.

Transactional gravity is pulling AI towards the mainframe

The Swedish bank SEB has done an MVP with IBM, successfully integrating low-latency ML scoring models into pre-existing transactional business flows on the mainframe.

Speaker: Erik Weyler

COBOL-Erik is a well-known advocate for Mainframe and COBOL. Always thinking of ways to make mainframe developers as productive as possible and always seeking to use new technology, together with the old, for no-fuss solutions.

From prototype to value-generating AI model: How to ensure AI governance at financial service providers through MLOps practices

In this presentation, Fabian Forthmann talks about the relevance of background processes in AI applications, which ensure the traceability and reproducibility of AI models. This is particularly relevant in the banking market because financial service providers are required to have particularly strong governance, which they can achieve through the technical implementation of MLOps practices.

Speaker: Fabian Forthmann

Fabian Forthmann is a senior consultant in the Data and Analytics department at MSG for Banking. He advises banks and financial service providers on the design and introduction of data-driven systems in their technical and functional environments. In current projects, he is particularly concerned with the efficient realization of cost potential through profitable use cases of Artificial Intelligence. Therefore, he specialises in the background processes of AI applications that ensure the secure and sustainable operation of AI models for financial service providers.

Boosting Similarity Search With Real-time Stream Processing and ML

Both similarity search and stream processing offer valuable capabilities for handling data-intensive tasks but require careful consideration of their respective trade-offs and challenges in implementation. While similarity search offers efficient retrieval of similar items across diverse data types, it can suffer from sensitivity to data representation and a trade-off between speed and accuracy. Stream processing, on the other hand, enables real-time analytics with scalability and fault tolerance but introduces complexity in design and operation.

Speaker: Fawaz Ghali

Fawaz Ghali is the Principal Data Science Architect and the Head of Developer Relations at Hazelcast with +22 years of experience in DevRel, cloud, enterprise software development and deployment, ML/AI and real-time intelligent applications, management, and leadership. He holds a Ph.D. in Computer Science and has worked in the private sector as well as in academia and research. He has published +45 scientific peer-reviewed papers in the fields of ML/AI, data science, and cloud computing on Google Scholar. Fawaz is a renowned expert who has +200 talks and presentations at global events and conferences.

The Fraud Hunter’s Playbook: Real-Time Detection Challenges and Tactics

Fraud can be considerably reduced via speed, scalability, and stability. Investigating fraudulent activities using fraud detection machine learning is crucial, as decisions need to be made in microseconds, not seconds or even milliseconds. This becomes more challenging when things get demanding and scaling real-time fraud detection becomes a bottleneck. The talk will address these challenges and provide solutions using a combination of real-time storage and computing that provides a unique synergy for real-time use cases at any scale.

Speaker: Fawaz Ghali

Fawaz Ghali is the Principal Data Science Architect and the Head of Developer Relations at Hazelcast with +22 years of experience in DevRel, cloud, enterprise software development and deployment, ML/AI and real-time intelligent applications, management, and leadership. He holds a Ph.D. in Computer Science and has worked in the private sector as well as in academia and research. He has published +45 scientific peer-reviewed papers in the fields of ML/AI, data science, and cloud computing on Google Scholar. Fawaz is a renowned expert who has +200 talks and presentations at global events and conferences.

Unlock The Secrets to Delivering Captivating Presentations!

Learn the 3-Step formula to designing and delivering powerful and engaging presentations every time…even if you hate speaking in public!

Speaker: Gary Lafferty

Gary is a leading expert in the art of Presenting…both live and online. With a proven track record of transforming ordinary webinars into extraordinary experiences, Gary is renowned for his ability to captivate audiences and drive impactful results.

As the founder of The Webinar Academy, and a 2 time #1 international best selling author, he has become synonymous with excellence in presentation delivery and webinar strategy, equipping countless professionals with the tools they need to captivate audiences and drive results.

Elevating Your Voice: Strategies for Analytics Professionals to Command Executive Attention

Analytic Professionals who Want their Ideas Heard by Executives

Speaker: Heather L. Cole

Heather L. Cole is an esteemed expert in data analytics and executive influence, specializing in equipping analytics professionals with the strategies to command executive attention. With a rich background that blends finance, computer science, and law, Heather excels in the art of negotiation and persuasion, which are key skills she imparts through her executive coaching. As the visionary behind Lodestar Solutions and Heatherized, Inc., she empowers professionals to elevate their voices, ensuring their insights drive decision-making at the highest levels. Heather’s approach not only transforms organizations but also positions data analytics as a pivotal force in executive strategy.

IBM Maximo Application Suite & Cognos Analytics have already been a happy marriage since 2012!

My talk is about the strength of using Cognos Analytics as a Data Analytics tool for IBM Maximo, especially for AI-driven reports regarding Asset Health & Anomaly prediction using the strength of both products (Maximo Manage, Monitor, IoT platform and Health & Predict and IBM Cognos Analytics infused with

Speaker: Jan-Willem Steur

Jan-Willem is a passionate Asset Management subject matter expert on all aspects, from asset condition to asset performance and asset life cycle management. He has a strong background in several domains of Asset Management, such as reliability engineering, maintenance management, and system engineering. His personal experience in his early years as a field technician at the Royal Dutch Navy helped him to better understand the day-to-day challenges in the field and how EAM systems can optimally support technicians by recording their critical data. From an asset- and maintenance-management perspective, he is experienced in managing complex assets, dealing with challenging asset and maintenance strategies, and translating them to process-supporting and user-friendly solutions using the best-in-class EAM system IBM Maximo Application Suite products.

Conceptual Model of Data Quality of Service as Code

Data QoS as Code represents a groundbreaking shift in data management, merging the principles of Data Quality and Service-Level Agreements into an integrated framework. This approach leverages the concepts of network Quality of Service (QoS) for monitoring data service performance metrics such as packet loss, throughput, and availability. By adopting the Everything as Code philosophy, Data QoS as Code introduces a method for automating, scaling, and securing data monitoring and management. It utilizes a vendor-neutral, YAML-based specification to facilitate this, offering a streamlined and efficient solution for handling complex data quality and service-level requirements.

In the presentation I will discuss the concept model and initial specification for it with some practical examples on how it would work in practice. Participants will learn how Everything as Code can be applied to Data Quality as Service covering both data quality and service quality aspects.

Speaker: Jarkko Moilanen

Experienced Data Economy professional with strong expertise in data monetization, platform, and API economy. He is Head of Data Products in the Abu Dhabi Emirate-wide data platform. Jarkko is the igniter and maintainer of Open Data Product Specification. He was MIT CDOIQ Country CDO Ambassador for Finland for two years. Jarkko has written business-focused books on API economy (“API Economy 101”) and Data Economy (“Deliver Value in the Data Economy” and “AI-Powered Data Products”).

Data Contracts are good for AI

Data contracts are here to stay, and it is a good thing. In this talk, Jean-Georges (aka jgp) will explain the genesis of data contracts and why they are bringing incredible value to AI.

Speaker: Jean-Georges Perrin

Jean-Georges “jgp” Perrin is the chief innovation officer at AbeaData, focusing on building innovative and modern data tooling. He is also chair of the Open Data Contract Standard (ODCS) at the Linux Foundation project Bitol, co-founder of AIDA User Group, and author of multiple books, including Implementing Data Mesh (O’Reilly) and Spark in Action, 2nd edition (Manning). He is passionate about software engineering and all things data. His latest endeavors bring him to more and more data engineering, data governance, industrialization of data science, and his favorite theme, Data Mesh. He is proud to have been recognized as a Lifetime IBM Champion, a PayPal Champion, and a Data Mesh MVP. Jean-Georges shares over 25 years of experience in the IT industry as a presenter and participant at conferences and publishing articles in print and online media. His blog is visible at He enjoys exploring Upstate New York and New England with his wife and kids when not immersed in tech, which he loves.

Preparing for the De-Peopling of the White Collar Workforce

Preparing for the oncoming massive loss of white collar jobs caused by automation by figuring out new ways for people to be paid. We propose helping people to make trackable, trackable content and paying people for their content.

Speaker: Karen Kilroy and Orson Weems

Karen Kilroy is the author of several O’Reilly publications, including Blockchain Tethered AI (2023), AI and the Law (2021), and Blockchain-as-a-Service (2019). She is a full-stack developer focused on AI, blockchain, and e-commerce. Karen is the Co-Founder of Friends of Justin, a non-profit organization created to ease the interactions between humans and AI. Karen is also the CEO of File Baby, a forever home for your files that lets you claim them using Content Authenticity Initiative (CAI) methodologies. Kilroy Blockchain, of which Karen is also CEO, won the IBM Watson Build Challenge for North America in 2017 for their app RILEY, and that was the point where Karen’s journey into the intersection of blockchain and AI began.

Orson Weems is the president of File Baby ( and co-founder and executive director of The Music Education Initiative ( Prior to heading these incredible organizations, Orson worked as the chief operating officer with the renowned music and entertainment icon, Al Bell, and his global music, entertainment, and artist development company, Al Bell Presents. Since 2006, Orson has been the president and majority shareholder of Land Improvement Company, a company founded in 1955 that specializes in construction management, civil construction/site preparation, small building demolition, and industrial services for federal, state, and local projects and government contracts.

Orson currently serves on the advisory board of The National Cold War Center ( He has served on numerous boards, including the Razorback Lettermen’s Club Board of Directors, the Arkansas Alumni Association Board of Directors, the Walton College of Business, Diversity & Inclusion Advisory Board, the University of Arkansas Chancellor’s Council on Diversity.

He is a graduate of The University of Arkansas, Fulbright College of Arts and Science, with a Bachelor of Arts in Journalism (Advertising and Public Relations), and a minor in English. He was also a Razorback offensive lineman and three-year letterman (‘81, ‘82, ‘83) under the legendary, Coach Lou Holtz.

An enthusiastic sports fan, Orson also enjoys traveling, cooking, good food, great music, estate sales, and responsible AI. He resides in Northwest Arkansas.

Bring order to chaos

What would you be able to do if all your unstructured data was correctly classified?

30 years. That´s for how long we have been digitizing our organizations. The result is vast amount of data, much of it of no use, but still driving costs and exposing us for risks of non-compliance and breaches.

It is time we bring structure to the unstructured by automating the process of reading, assessing, classifying and manage our data using state of the art large language models and deep transfer learning.

  • Bring additional value to your existing technology, such as data loss prevention and policy enforcement.
  • Support your users by relieving them of the burden of manual classification.
  • Increase your compliance with NIST800-53, NIS2, ISO27001, DORA, CMMC, GDPR, and all other upcoming regulations demanding you to have granular information insight and control.
  • Make it possible for your organisation to use generative AI by controlling both what goes in, and what comes out.

Speaker: Karl-Oskar Brännström

Karl-Oskar has more than two decades of experience in digitalization, combining technology, people, and processes to achieve sustainable compliance and operational efficiency. Starting his career as a pioneer in business process management, he has headed companies surpassing 1 million active and licensed users and is now on a quest to bring order to chaos.

Karl-Oskar holds an LL.M. and a bachelor’s degree in corporate finance from the University of Gothenburg and a Master in Intellectual Capital Management from Chalmers University of Technology. He is today the CEO of Aigine and serves as a board member and senior advisor for numerous companies within anti-corruption, AI and privacy.

Karl-Oskar calls Stockholm, Sweden, home and enjoys sailing, dirt bikes and skiing in his spare time. His summer house in Bordeaux, France has also led to a profound interest in wine and food.

Getting Data ROI Right: Tech and Business Collide

Regardless of how cool your AI solution is, it will fail without executive buy-in – not only in the shiny but also in the data beneath it- to scale and grow over time. How do you make your case for this very technical need to a non-technical audience? Tailored to data and technology leaders, Kim will gather her team of trusty superheroes to guide you through meaningful ways to rapidly achieve ROI that gains attention and meaningfully articulate the technical needs we have for investment without causing executive eyes to glaze over. Together, we will catapult your ability to lead and drive radical transformation to a data-driven company.

Speaker: Kim Thies

Kim’s passion lies in using modern data architecture to establish data-driven enterprises. As CEO of AbeaData, she works with clients across the world to revolutionize the way they access, govern and use data. Prior to joining AbeaData, Kim held a variety of leadership roles in data, technology and business strategy, including her recent role as Director of Intelligence Automation at PayPal. Her career journey spans startups, Fortune 500 leadership and consulting roles, grassroots advocacy, and international nonprofit leadership. Kim is a chronic entrepreneur, travel junky, and loves spending time with her family.

AI for better AI – Authentic Intelligence for Better Approximated Intelligence

This talk delves into the concept of authentic intelligence, how Lalit understands it, and its profound implications for enhancing the quality, ethical framework, and societal impact of AI. It explores the essence of infusing human values, ethical considerations, and cognitive empathy into AI systems to foster better decision-making, ethical reasoning, and empathetic interactions. Leveraging authentic intelligence not only cultivates trust between humans and machines but also paves the way for responsible and beneficial AI applications across diverse domains. Lalit will discuss the significance of integrating Authentic Intelligence as a fundamental paradigm for shaping a future where AI aligns harmoniously with human values, critical thinking, societal needs, and ethical standards.

Speaker: Lalitkumar Bhamare

For the past 15 years, Lalit has been a driving force in the realm of test engineering and software quality leadership. His expertise spans the entire spectrum of quality engineering, from conceptualizing to the post-production phases of software delivery.

Currently serving as a Manager at Accenture Song, Lalit wears multiple hats, simultaneously leading the Innovation and Thought Leadership group for Quality Engineering Services at Accenture DACH. This strategic role encompasses operations across Germany, Austria, and Switzerland.

Lalit excels in leveraging testing as a catalyst for business and digital transformation, a skill that has earned him acclaim in the form of his proprietary delivery framework, Quality Conscious Software Delivery (QCSD). This framework received prestigious recognition at the EuroSTAR 2022 International Conference in Copenhagen.

Lalit is a long-time active contributor and is recognized for his noteworthy contributions to the community. From his non-profit publication, “Tea-time with Testers,” to his role as Director at the Association for Software Testing and his engagements as an international keynote speaker and testing thought leader, Lalit had left an indelible mark.

Throughout the past decade, Lalit has collaborated closely with industry experts and leaders worldwide, actively propelling the craft of software testing forward. Explore more about Lalit’s professional endeavors on his website:

Federated System and Neural Architecture Search

1. What is NAS – Introduction
2. Why is it the need of the hour?
3. It’s relevance to current research in AI
4. How it integrates with Federated Learning
5. a little about my research topic

Speaker: Laveena Kewlani

Laveena holds an MSc. from the Technical University of Munich, Germany, specializing in Data Engineering, Data Science, Computer Vision, and Advanced Mathematics, with over 8 years of experience in data science analytics. Through her education and work experience in both India and Germany, she has gained insight into recent research topics in technology, such as data mesh, federated learning, computer vision, object detection, tracking, and scientific computing.

With significant hands-on experience as a Data Engineer and Architect, Laveena has successfully solved data-related tasks for analytics, machine learning, and deep learning problems, including challenges in computer vision.
Additionally, she is currently pursuing a PhD in Neural Architectural Search at IIT Kharagpur, further advancing her expertise in cutting-edge topics within the field of artificial intelligence and deep learning. This research focus highlights her commitment to advancing the understanding and development of neural architectures.

FerretDB from scratch – a truly open-source alternative for MongoDB

The SSPL license introduced by MongoDB in 2018 makes it difficult to use the most loved by developers NoSQL database, for projects they are working on.

FerretDB allows you to use all tools, drivers, UIs, and the same query language as MongoDB and stay open-source. Our mission is to enable the open-source community and developers to reap the benefits of easy-to-use document databases while avoiding vendor lock-in and faux pen licenses.

The software may use PostgreSQL and SQLite as a backend, and it is designed to work in Kubernetes environments. Everything is to provide developers and operations the flexibility they need to create modern applications and maintain the infrastructure. Because of that, FerretDB becomes a drop-in replacement for MongoDB in many cases.

Speaker: Marcin Gwozdz

Proactive IT solution professional advisor with combined business and technical knowledge: experienced in enterprise software sales for cross sectors, building technical alliances, and supporting channel sales for years. Focused on open-source solutions, always ready to share knowledge.

My vision is that open source will be as sustainable in terms of product and revenue growth as proprietary solutions as more and more entrepreneurs will work on open source projects.

Business Intelligence and Data Science – Merging both approaches and breaking the silos in consumption, processes, and governance

Business Intelligence and Data Science are often seen as two worlds: both worlds make different contributions for different purposes and thus have their rationale for existence. There are departments in companies using various BI tools for descriptive statistics and charts (Tableau, Cognos, Power BI, etc.). The insights from Machine Learning or Deep Learning processes, e.g., a market basket customer churn analysis or more complex forecasts, are again consumed separately (often Open Source technology). The “Data Family” is dealing with a merging of data sources to create a single point of truth and make data highly available, but at this point, we are again building up renewed silos. Silos in consumption (different tools/front-ends), separate processes for data pipelines, governance, and many more. Maximilian talks about the approach of merging BI and Data Science methodologically, conceptually, and technically.

Speaker: Maximilian Burkardt

Maximilian is a Technical Sales Specialist for AI-based in Germany, and his favorite topic is Artificial Intelligence in combination with Business Intelligence (AI+BI). He has a technical background in Data Science and Business Intelligence as well as 6,5 years of industry experience in the Retail and Supply Chain Industry (Grocery Retailer) before IBM. In the Retail industry, he worked intensively with domain expert business units on various Data Science use cases and developed an MLOps architecture. At IBM, Max is a trusted Technical Sales Specialist for clients, a Speaker about Data Science, Business Intelligence, and Generative AI as well as develops innovative prototypes and demos in the field of AI+BI for a worldwide audience.

Elevate Your Analytics Game: Power BI vs. Cognos Analytics, Unraveling the Differences

Making the right decision on Cognos Analytics vs. Power BI. Why Cognos is more than you know today.

Speaker: Michael Bernaiche

Mike is a seasoned IBM Cognos and Planning Consultant and coach with a wealth of experience in driving actionable insights and strategic decision-making for businesses. They specialize in untangling complex data landscapes and crafting tailored solutions that align with organizational goals. As a coach, Mike empowers teams and individuals to harness the full potential of IBM Cognos and Planning solutions through personalized guidance and mentorship. With expertise in streamlining reporting processes, designing forecasting models, and optimizing budgeting workflows, Mike is a trusted advisor committed to excellence in business intelligence and planning.

Building LLM apps with LLama CPP in 15 minutes

Want to build LLM apps, but all you’ve got is your laptop and a dream? In this session, Nick’s going to walk you through all you need to know to work with Llama CPP for your own desktop applications, from prompting to function calling and multi-modal stuff.

Speaker: Nicholas Renotte

Nicholas, Chief AI Engineer – Client Engineering, is a seasoned Data Science and AI professional. He has honed his expertise through his tenure at IBM and across diverse sectors such as Finance, Government, Wholesale, Retail, and more. In addition to his work at IBM, Nicholas runs a successful YouTube channel on Machine Learning, known for its insightful and practical content. His current focus is on empowering clients to leverage machine learning and generative AI, including the use of watsonx, to solve business challenges. His work is central to driving the adoption and understanding of these advanced technologies, making AI accessible and beneficial for all.

AI in the workplace

How to harness the power of AI tools to streamline work processes and unlock significant productivity gains

Speaker: Or Pelach

Leading change and innovation processes, helping organizations streamline and improve work processes, and increase productivity. Lecturer and facilitator of workshops on large language models such as ChatGPT and other AI tools.

Chat as a growth opportunity, challenges and opportunities

The value that Chat can add when used for your long-term growth. I will present some challenges and societal concerns when chat and similar tools are used with a short-term mindset.

Speaker: Paul Cortellesi

Am no one of consequence, but will update with more info later (or check is bio on the AIDA User Group’s board page).

Using Cognos

Harnessing the Stars: Using Cognos for Astrological Forecasting – a warning on generative AI.

Speaker: Paul Mendelson

Paul is a mystery. He doesn’t know how to write bios, so nobody actually knows anything about him.

Data Testing: Moving towards being proactive

The talk will center around the difficulties of testing. I will explore the current methodologies used and dive into how these processes can be automated using open-source tools available to us. Then, we will finish off with the future direction of testing, where AI-assisted testing and data contracts will play a part.
This talk is intended for data and software engineers, architects, and testers. After the talk, they will understand the shortcomings of current methods, tools, and services that are available to tackle these problems and what the future of testing could look like.

Speaker: Peter Flook

Founder @ Data Catering. Data Engineer who has experience touching a bit of everything in technology. Enjoys watching/playing any sport.

Prompt Engineering for Testers

  • Why is Prompt Engineering the New Buzz Skill?
  • Basics of Prompting
  • Prompting Techniques – Basics to Advanced
  • Live Demonstration & Testing Use Cases
  • AI Prompt Repository for Testers

Speaker: Rahul Parwal

Rahul Parwal is an Expert Software Tester. He is a recipient of the prestigious Jerry Weinberg Testing Excellence Award.

Rahul is an avid reader, blogger, and conference speaker who likes to share his thoughts on various platforms. He is a mind mapping enthusiast and also one of the official Xmind Ambassadors. Recently, he has been inducted as a LambdaTest Spartan, & a Browserstack Champion for his work in the field of testing. He works with ifm engineering.

IBM Cognos Analytics REST API gives Super Power: Building Fast, and Visually Impressive Dashboards

Join us in this interactive technical session, where we’ll steer you through the process of creating a super fast and appealing dashboard leveraging the IBM Analytics REST API. We’ll demonstrate how to invoke the REST API with plain JavaScript and Angular and incorporate numerous IBM Analytics Reports for sub-three-second data visualization. Designed for multi-device compatibility, the dashboard emphasizes speed, design elegance, and user-friendly interactivity. All examples used will be openly sourced, allowing participants to recreate and tailor the dashboard to their requirements. Imagine using the REST API for data delivery anywhere. By the end of the session, you’ll be equipped with the knowledge to create striking, highly responsive dashboards utilizing the IBM Analytics REST API.

Speaker: Ralf Roeber

Meet Ralf, a seasoned IT professional with over 30 years of experience in the industry. With a remarkable ability to comprehend and efficiently solve complex technical challenges, Ralf’s expertise spans OSI Level 2 – 7, granting him a unique advantage in evaluating project proposals and swiftly resolving issues during critical project launches.

Driven by a passion for delivering exceptional service, Ralf places utmost emphasis on achieving 120% customer satisfaction in all his business relationships. For nearly two decades, he has proudly served as a reliable and trusted partner to a prestigious German car manufacturer, consistently providing them with best-in-class solutions.

In 2021, Ralf embarked on a new entrepreneurial journey by founding, a cutting-edge platform that revolutionizes IBM Cognos testing and beyond through a user-friendly no-code approach for QA testers and by embracing developers with low-code and Python solutions.

Beyond his technical prowess, Ralf is an avid speaker, sharing his knowledge and insights with audiences, and he generously mentors students who aspire to carve their paths in the IT industry. When not immersed in the world of machines, Ralf indulges in his love for exploration, wandering the enchanting landscapes and beaches of Barcelona, Catalunya, Spain.

Ralf’s achievements are as impressive as his technical acumen. Notably, he received an honorable mention at the 1997 Prix Ars Electronica, recognizing his contributions to the field. Furthermore, his expertise in Cognos earned him the prestigious Cognos Performance Star in 2006. In recognition of his exceptional skills and knowledge, he was named an IBM Data Analysis and AI Champion from 2021 to 2024, cementing his status as a thought leader in the industry.

Ralf’s passion for knowledge exchange extends to the community, evident in his role as the founder of AIDAUG, an independent, large-scale, worldwide user group for AI and Data Analytics. Through this initiative, Ralf fosters collaboration and continuous learning, empowering professionals across the globe to excel in their data analytics endeavors.

With a lifelong commitment to innovation, customer satisfaction, and technological excellence, Ralf continues to leave an indelible mark on the IT industry while exploring the realms of possibility in his ever-evolving journey.

How to get help from the AI assistant and Watson Exploration in Cognos with Customer success stories

In the recent versions of IBM Cognos Analytics, a lot has been done to build more AI into the product.
The AI assistant can help you get quick answers about your data, and if you would like to get some help to
To analyze and understand your data, you must learn how to use Watson Exploration in Cognos.
I will show you how to use the AI Assistant and Watson Exploration in Cognos, and then I will show how
some of our customers have used both to gain business success.

Speaker: Rikke Jacobsen

Rikke Jacobsen is the CEO & and Founder of CogniTech A/S. A Danish IBM Business Gold Partner. Keeping her employees happy and motivated and getting more people to use and get the most value out of IBM Analytics is her passion.

Rikke has worked with IBM Cognos Analytics for more than 20 years, and she still gets excited about the prospect of helping her clients make sense of their data. She is the first Dane to be named IBM Analytics Hero, a title that has been earned because of her enthusiasm and dedication to the Cognos community. A lot of people also know her as Mrs. Cognos.

BI in the Age of AI

I will review business intelligence, how we got to where we are, and where AI will take us.

Speaker: Ryan Dolley

Ryan Dolley is Vice President of Product Strategy at GoodData and co-host of the Super Data Brothers show. He has over a decade of experience in the analytics and business intelligence industry.

AI-Generated Creativity: Pushing the Boundaries of Artistic Expression with Generative Adversarial Networks (GANs)

This research proposal seeks to explore novel applications of Generative Adversarial Networks (GANs) in the realm of creative content generation, specifically focusing on art, music, and literature. By harnessing the capabilities of GANs, this project aims to push the boundaries of artistic expression, enabling the creation of unique and original works through collaboration between human artists and AI systems.

The primary objective of this research is to investigate how GANs, a type of artificial intelligence model, can contribute to the creative process by generating artistic content that is not only visually and aesthetically pleasing but also conceptually innovative. The project aims to foster a symbiotic relationship between human creativity and AI, expanding the possibilities of what can be achieved through collaborative endeavors.

Speaker: Sahaj Vaidya

As a doctoral student in Data Science at the New Jersey Institute of Technology (NJIT), Sahaj
Vaidya has undertaken groundbreaking research in Ethical AI Governance, Data-Driven
Decision Making, and effective communication of scientific insights. Her focus on responsible
AI implementation in the public sector demonstrates a commitment to addressing critical issues
in the field.

Open Explainability Protocol (OEXP):
Sahaj’s research project, the Open Explainability Protocol (OEXP), stands as a testament to her
dedication to ethical AI and responsible governance. OEXP aims to establish a universally
accepted standard for conveying the outputs of autonomous systems, a crucial step in enhancing
user interactions with AI-based systems. This initiative reflects Sahaj’s proactive approach in
contributing to industry-wide standards.

Leadership as AI Ethics Officer at ZEN:
Sahaj Vaidya serves as the AI Ethics Officer at ZEN, a role that holds significant prominence
among her achievements. In this capacity, she plays a pivotal role in shaping ethical
considerations in AI. Notably, Sahaj’s role involves curating a curriculum for building AI literacy
among individuals with varied backgrounds, showcasing her commitment to making AI
education accessible and inclusive.

CAIDP Fellow for Spring 2024 Cohort:
Sahaj’s recent accomplishments include being selected as a CAIDP (Center for Applied Artificial
Intelligence for Data Analytics and Policy) fellow for the Spring 2024 cohort. This recognition
reflects her standing as a thought leader and practitioner in the application of AI for data
analytics and policy development.

Researcher and Distinguished Speaker at Artiqode:
Sahaj Vaidya actively contributes as a researcher and distinguished speaker with the Artiqode
community, focusing on Generative AI for training C-suite executives on AI and its impact on
business. Her role in disseminating knowledge to high-level executives underscores her ability to
bridge the gap between technical concepts and practical business implications.

Engagement in AI Education Network:
Within the AI Education Network, Sahaj has been a proactive member, actively working to
provide AI education to K-12 students and promote awareness of AI concepts among young
learners. This commitment aligns with her broader dedication to AI education and public
engagement, reflecting a holistic approach to advancing the field.

From slums of Mumbai to Germany, My story in Tech

I grew up in slums of mumbai and struggled in my life, there were times when I had to sleep on floor, fighting to save my daughters life, but finally I came on top and living a better life with my family in germany, everyone struggles in life, I will share my story of story of grit and determination how I succeeded in tech, How Open Source changed my life ? and became indias first GitHub Star.

Speaker: Santosh Yadav

Santosh is a Senior Software Engineer at Celonis, a GDE for Angular, GitHub Star, Nx Champion and an Auth0 Ambassador. He loves contributing to Angular and its ecosystem. He is a co-founder of This is Learning. He is also the author of the Ngx-Builders package and part of the NestJsAddOns core Team. He is also running This is Tech Talks talk show, where he invites industry experts to discuss different technologies.

Optimizing Lakehouse Strategies with the Modern Data Stack

In this presentation, we’ll guide you through the process of constructing a robust data lake on cloud storage solutions such as Amazon S3. We will demonstrate how to perform in-place data transformations using cutting-edge tools like DuckDB and DBT, enabling semantic SQL transformations directly on your data lake. The discussion will extend to crucial topics such as data lineage and strategies for managing data quality issues, ensuring your data remains accurate and reliable. Furthermore, we will explore innovative methods for hosting APIs and dashboards that interact seamlessly with your data lake, opening up new possibilities for data accessibility and visualization. Throughout the session, we will share practical code samples executed on our proprietary DataTask platform, providing you with hands-on knowledge and tools to enhance your data architecture.

Speaker: Vincent Heuschling

As the enthusiastic founder of DataTask and the host of the French data podcast “”BigDataHebdo””, I dedicate my days to assisting clients in the creation, development, and management of their data platforms. My approach prioritizes both efficiency and simplicity, stemming from a firm belief in the potential for democratizing data usage.

Fireside chat with Jean-Georges Perrin

Let’s talk Data Mesh, Data OS, and more!

Speaker: Zhamak Dehghani with Jean-Georges Perrin

Zhamak Dheghani is a prominent figure in the field of software engineering and technology. Born in Iran, Dheghani’s passion for computer science led her to pursue a Bachelor’s degree in Electrical Engineering. With a strong foundation in engineering, she went on to earn a Ph.D. in Computer Science from the University of Cambridge.

Dheghani has made significant contributions to the industry through her expertise in distributed systems, event-driven architecture, and streaming platforms. She is particularly renowned for her groundbreaking work on data mesh, a paradigm shift in data architecture that emphasizes domain-oriented, self-serve data infrastructure. Her ideas and principles have revolutionized how organizations approach data management and have gained widespread recognition in the technology community. She is the author of the book “Data Mesh – Delivering Data-Driven Value At Scale”. Moreover, she has published numerous articles, given keynote speeches, and conducted workshops, inspiring and guiding organizations worldwide to embrace this innovative approach. She now runs Nextdata.

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