Event Program
October 20, 2023 ∙ FEUP
| When | What | Where |
|---|---|---|
| 9:00 (30′) | Registration | Entrance Hall |
| 9:30 (15′) | Welcome Session | Auditorium |
| 9:45 (45′) | Keynote 1: Rayid Ghani Using AI/ML/Data Science for Social Good: Fairly and Equitably Powered by Fraunhofer Portugal | Auditorium |
| 10:30 (30′) | Coffee Break | Showroom |
| 11:00 (45′) | Keynote 2: Pedro Saleiro Innovating from within: AI Research at Feedzai | Auditorium |
| 11:45 (135′) | Lunch Break | Showroom |
| 14:00 (45′) | Keynote 3: Jodie Burchell How to sell a data science project (without selling your soul) | Auditorium |
| 14:45 (75′) | 1 on 1 talks Coffee Break | Classrooms (B024 + B025) Showroom |
| 16:00 (45′) | Keynote 4: Arlindo Oliveira Artificial Intelligence: Applications, Implications and Speculations | Auditorium |
| 16:45 (30′) | Goodbye | Auditorium |
| Sunset Cocktail Sponsored by CIB |
Find more details below
Keynote 1:
Rayid Ghani
Using AI/ML/Data Science for Social Good: Fairly and Equitably
Can AI, ML and Data Science help reduce infant and maternal mortality? Can it reduce the impact of mental and behavioral health crisis? Can it help cities better target limited resources to improve the lives of citizens and achieve equity? We’re all aware of the potential of ML and AI but turning this potential into tangible and equitable social impact involves dealing with both technical and ethical challenges.
In this talk, I will discuss lessons learned from working on numerous projects over the past few years with non-profits and governments on high-impact public policy and social challenges in criminal justice, public health, education, economic development, public safety, workforce training, and urban infrastructure. I will highlight opportunities as well as challenges around ethics, bias, and fairness that need to be tackled in order to have social and policy impact in a fair and equitable manner.
Keynote 2:
Pedro Saleiro
Innovating from within: AI Research at Feedzai
Fraud and money laundering continue to pose significant challenges to the stability of the global financial system. In the United States, the reported financial loss due to fraud reached approximately $8.8 billion in 2022, a 30% increase from the previous year. The adversarial dynamics and varied nature of financial crime, encompassing scams, social engineering, mule accounts, or sophisticated malware attacks further complicates its mitigation.
The AI Research group at Feedzai focuses on developing state-of-the-art AI innovations to address issues of fraud detection, behavioral biometrics and anti-money laundering while adhering to Responsible AI principles. This talk will present an overview of its current research initiatives in four main areas: algorithmic risk assessment, MLOps, fairness, and generative AI. The objective is to provide a nuanced understanding of the role of AI and its ethical considerations in financial crime prevention, thereby contributing to broader dialogue between industry and academic research.
Keynote 3:
Jodie Burchell
How to sell a data science project (without selling your soul)
Have you been keeping track of the amazing data science work being done at companies like Google, Meta and Microsoft, and dreamed of doing something similar in your own company? Don’t worry, getting your manager on board might not be as tough as it seems!
In this talk, we’ll explore the role of research-oriented data scientists within profit-driven enterprises, and discover how to craft and present projects that not only ignite your scientific curiosity but also capture your company’s interest. We will delve into the delicate balance between innovation and the fear of failure that businesses must navigate, and you’ll learn how to negotiate this while developing your projects. By the end of this talk, you’ll leave with knowledge and strategies to seamlessly merge your scientific passion with your company’s objectives.
Keynote 4:
Arlindo Oliveira
Artificial Intelligence: Applications, Implications and Speculations
Recent advances in the fields of Artificial Intelligence (AI) and Machine Learning are revolutionizing our economy and our society.
In the near future, AI-based systems may replace a significant fraction of human workers in many jobs and functions. AI research may even open the door to Artificial General Intelligence (AGI), enabling us to create digital minds, systems as intelligent, powerful, and conscious as humans. These digital minds would exhibit intelligent behavior, either by direct emulation of brain processes or by synthetic, approach. If they come into existence, what will be the social, legal, and ethical implications?