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Previous presentation at Goto 10 in Stockholm

Streaming and Deep Anomaly Detection

11 Apr 2019, 18:00–20:00 | Organizer: Foo Café

The event has passed.

Two new talks at Foo Café organised by the HopsML group. Join us at Goto 10.

Deep Anomaly Detection

Mehrdad Mamaghani, Principal Data Scientist at Swedbank

Davit Bzhalava, Principal Data Scientist at Swedbank

Anomaly detection has numerous applications in a wide variety of fields. In banking, with ever growing heterogeneity and complexity, it is difficult to discover deviating cases using traditional investigation techniques and pre-defined scenario searches. In this talk we’ll have a walk-through on how Swedbank’s deep learning models run on a state-of-the-art platform can help to detect unseen anomalies and deviations utilizing a large spectrum of features.

Mehrdad Mamaghani and Davit Bzhalava hold PhD degrees in applied mathematical statistics and bioinformatics, respectively. Previously, they have worked within biological research, pharmaceutical and communication industries. At Swedbank, along with rest of the Analytics & AI group, the speakers and their colleagues conduct extensive work and research to better leverage the data within the bank as well as creating frameworks for more efficient and customer-oriented banking processes using deep learning techniques and advanced hardware platforms.

Streaming at King

Anis Nasir, King

King is one of the major mobile gaming companies in the world with numerous mobile games running in production, e.g., candy crush, bubble witch, farm heroes and many others. These games produce billions of events on daily basis, which require to be processed in real-time with latencies within seconds. At King, we have developed an in-house streaming platform called RBEA (rule-based event aggregator), which allows scientists and engineers across King to write streaming application and extract information from the enormous amount of data. The talk will cover various aspects on running streaming platform in production environment at King.

Anis Nasir is a backend engineer at King, working for the streaming platform team for more than a year. Prior to work, he finished his PhD at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology. His supervisors were Sarunas Girdzijauskas and Seif Haridi.

 

Agenda

17:45 Doors Open

18:10 - 18:40: Deep Anomaly Detection

18:40 - 19:10: Pizza and Drinks

19:10 - 19:40: Streaming at King

19:40 - 20:00: Networking

Welcome!

Goto 10 är en arena där individer och organisationer kan dela kunskap, idéer och perspektiv. Detta event speglar arrangörens åsikter och delas inte nödvändigtvis av oss på Goto 10 och Internetstiftelsen. På Goto 10 får idéer och kunskap testas, diskuteras och utvecklas så länge de följer våra riktlinjer.