- Forecasting strategies (recursive, direct, mimo and hybrid)
- Metadata oriented machine learning
- Complex cloud machine learning pipelines
- Serverless active model monitoring
Edgar Bahilo Rodríguez – Lead Data Scientist | Siemens EnergyEdgar Bahilo Rodriguez is the lead data scientist in the industrial applications division of Siemens Energy, his main experience is in applying ML for time series analysis and forecasting but extends to other knowledge areas like anomaly detection and NLP. Edgar is the product owner of SEER, the company’s most notable end to end data scientist platform. He is also the architect of the data science life cycle in industrial applications, and he has strong experience implementing and architecting ML workloads in the cloud (AWS). He co-leads the cross topic of ML Methods and Engineering at Siemens Energy.
Mohamed Ahmed – Senior Data Scientist | Siemens EnergyMohamed Ahmed is a Senior Data Scientist working for Siemens Energy in the industrial applications division. He has worked in many time series forecasting problems and computer vision use cases. Recently he has been involved in the first IoT use cases using machine learning in industrial applications. Experienced with developing end to end ML solutions on cloud infrastructure (AWS), using MLOps best practices. He is also part of the ML Methods and Engineering cross topic at Siemens Energy.
October 15 @ 14:30
14:30 — 14:50 (20′)
Day 2 | M3 | Data Engineering Stage
Edgar Bahilo Rodríguez – Lead Data Scientist & Mohamed Ahmed – Senior Data Scientist | Siemens Energy