Past Meetup

Decentralized Private Machine Learning, and more...

This Meetup is past

106 people went

Silicon Allee

Chausseestraße 19, 10115 · Berlin

How to find us

Rooftop Meetup Space, take the elevator to the 6th floor

Location image of event venue

Details

Secure and anonymous sharing of data is tedious, and traditional methods have so far failed us. At Ocean, we are interested not only in the emerging technologies which facilitate secure data sharing, but also in the potential of a world where enough high-quality data is available to propel future applications forward.

For this meetup, we are thrilled to welcome Francesco Gadaleta of Fitchain.io, Verv COO Maria McKavanagh, as well as Fang Gong of Ocean Protocol. As always, pizza and beer are on us. Doors open at 6:45pm.

Francesco Gadaleta, PhD., Founder, Fitchain.io
Talk: Fitchain.io: Decentralized Private Machine Learning

Training machine learning models based on private data is usually performed via encryption of data, models or both. The complexity of current encryption schemes and the computational requirements of modern machine learning methods, make encrypted machine learning unfeasible for real world applications. Fitchain allows data providers to open their private data to algorithms created by data scientists without disclosing nor encrypting them. Incentives to all the actors involved in the process (model owners, data owners, computing providers and validators) make the fitchain marketplace sustainable and balanced in game theoretic terms.

Bio:
Francesco Gadaleta, PhD. is the founder of fitchain.io, Techstars alumni, and former member of the Advanced Analytics Team of Johnson&Johnson Pharmaceutical Companies.
His interests range from applied math, machine learning, cryptography, blockchain technology and decentralised systems. He has worked in domains such as healthcare, bioinformatics and personal finance, while creating the most accurate ischemic stroke predictor from real world evidence data (RWE). He has also helped people manage their money by designing an advanced financial chatbot at Abe AI. He is the host of the podcast datascienceathome.com, has a weakness for highly-skilled individuals, long distance running and chocolate-flavoured Italian gelato (not to be confused with ice cream).

Maria McKavanagh, COO, Verv
Talk: Exchanging data for electricity: a new data marketplace for energy with the consumer at its centre

Maria will provide insight into the rich and untapped energy data sets in the home that can be unlocked by high-speed data sampling and advanced AI. Maria will explore the value behind their new business model that will be facilitated by the Ocean platform, and the importance of providing a safe and secure ecosystem whereby consumers are in full control of their data.

Bio:
Maria McKavanagh is the COO of Verv, the company behind the VLUX Token. Verv is creating a new energy marketplace that's powered by data as they look to bring energy bills down to zero. Maria is a global keynote speaker and advocate of women in tech. For the second year running she has been nominated as one of the most influential women in UK tech. Previously she worked for NASDAQ data acquisition specialist National Instruments where she was responsible for a multi-million pound sales territory across a range of industries from Aerospace and Defence to Consumer Electronics. She holds an MEng degree in Electrical Engineering.

Fang Gong, Researcher, Ocean Protocol
Talk: Bringing Privacy to Ocean Protocol

At Ocean Protocol, we unlock data for AI and use Token Curated Registries (TCRs) to maintain a registry of high-quality datasets through voting. Privacy is essential to protecting the confidentiality of voters and prevent potential attacks. Fang will go into detail more details during his talk and explore the ways of bringing privacy to Ocean.

Bio:
Fang is a researcher working at Ocean Protocol. His research interests focus on mechanism design for tokenized ecosystem. Fang received his Ph.D. degree from electrical engineering at University of California, Los Angeles (UCLA) in 2013.