Socialisation, learning and entertainment
On October 17, dScience welcomes you to an evening of socialisation, learning and entertainment.
The event starts with a short session of mingling and food. Then we will be hearing exciting talks from invited speakers. After the talks, we regather in the Science Library foyer for mingling and refreshments.
Continuing the success from previous years, we have invited a wide range of relevant companies to set up stands where they can present themselves to our guests. Our goal is to bring all parts of the data science community together for unique networking opportunities.
Open to All
The event is free and open for all audiences, whether you are familiar with data science practices, or you are curious about data science. Food, snacks and soft drinks will be served.
Program
- 17:00 – Doors open, company stands, food and soft drinks
- 18:00 – Welcome and presentations
- "Data-Driven Rides: Tackling Mobility Challenges with Data Science at Voi" by Rahman Amandius, Head of Machine Learning & Data Science at Voi Technology
- "Fairness by Design - Considering Fairness in Algorithmic Decision Making" by Anne-Marie George, Postdoctoral Fellow at the Department of Informatics, UiO
- "From Hypothesis to Reality: Designing a Superhuman Racing AI Agent using Deep Reinforcement Learning" by Alisa Devlic, Senior Research Scientist at Sony AI
- 20:00 – Socializing, company stands, food and soft drinks
Abstracts
Data-Driven Rides: Tackling Mobility Challenges with Data Science at Voi, Rahman Amandius, Voi Technology
Voi is a micro-mobility company operating in 100 cities across Europe, specializing in short-term rentals of e-bikes and e-scooters. At the heart of our product is data, with a strong emphasis on Machine Learning and Data Science. This presentation will explore key user-facing challenges where Data Science plays a crucial role in the provided solutions: (1) Availability: Maximizing the probability that a vehicle is available when and where a customer needs it. (2) Compliance: Ensuring that customers adhere to city regulations.
Fairness by Design - Considering Fairness in Algorithmic Decision Making, Anne-Marie George, University of Oslo
While we may associate fairness with social sciences, fairness is an increasingly relevant notion in data science. Designers of algorithms and automated decision making may introduce (un)fairness in their systems, in particular for applications that involve decisions for humans. In this talk Anne-Marie will exemplify such (un)fair decisions, but also tell us how different notions of fairness can be enforced algorithmically.
From Hypothesis to Reality: Designing a Superhuman Racing AI Agent using Deep Reinforcement Learning, Alisa Devlic, Sony AI
This work started out as a grand challenge to create an AI agent that could beat the world’s best Gran Turismo (GT) drivers. In order to develop an agent capable of competing against the world’s best drivers, GT Sophy was trained to master the following driving skills: race car control, racing tactics, and racing etiquette. This talk will tell you a story about the technical evolution of GT Sophy from a research outcome to an in-game feature that could be introduced as part of the Gran Turismo 7 (GT7) PlayStation racing game. Sony AI, in collaboration with Polyphony Digital and Sony Interactive Entertainment, designed novel deep reinforcement learning approaches with unique training and evaluation methods on a modern cloud computing platform to accommodate this project. In less than two years since GT Sophy appeared on the cover of Nature, the breakthrough AI agent has now become a permanent in-game feature of GT7.
Company stands
There will be sizable number of company stands, showcasing their work and innovations to participants both before and after the talks. Currently, the following companies have confirmed their participation (please note that this list is continuously being updated):
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ABB AS Marine & Ports
- Bane NOR
- Chronos AS
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DNV
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Factiverse
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Gjensidige
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Hance
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Kongsberg Digital
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Microsoft Norway
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Norsk Regnesentral
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SINTEF Digital
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SLB (Schlumberger)
- Soundsensing
- SSB (Statistisk sentralbyr?)
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Telenor
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Tet Digital
