ML Club
Details
#Itinerary
18:00 - 18:30: Networking over drinks and pizza.
18:30 - 18:40: Introduction to ML Club.
18:40 - 19:20: Hello DEA I want to go to Mars, can you help me?
19:20 - 20:00: Introducing GRAKN.AI to Glasgow
20:00 - 20:30: Final thanks and networking over drinks (assuming pizza has been eaten).
#Talk 1: Hello DEA I want to go to Mars, can you help me?
Space missions development takes years and traditionally starts with a feasibility study phase where experts consider several design options mostly relying on lessons learned from past studies. We propose to develop a Design Engineering Assistant (DEA), an expert system that will enhance and ease the work of the experts in the design of space missions. The tool will rely on the use Grakn, ML and NLP techniques.
The project is led by two PhD students of the Intelligent Computational Engineering (ICE) Lab of Strathclyde University - http://icelab.uk/.
#Speakers Bio
Francesco Murdaca
Background: BSc in Aerospace Engineering and MSc in Space Engineering from Politecnico di Milano + worked for a space company Deimos Space (Madrid) on design tool development for a satellite subsystem sizing.
Research focus: developing the domain ontology tool of the DEA
The research will leverage techniques in the field of Natural Language Processing (NLP), Deep Learning, Ontology Learning, Knowledge Management, Knowledge Discovery, Fuzzy Rules.
Audrey Berquand
Background: MSc in Aerospace Engineering from KTH (Sweden) + 3 years experience as a space system engineer at the European Space Agency (ESA).
Research focus: developing the querying tool of the DEA
Apply Computational Intelligence, Knowledge Management, ML and NLP methods to develop a natural language interface extracting information from the DEA knowledge base and provide knowledge summaries to experts.
#Talk 2: Introducing GRAKN.AI to Glasgow
Cognitive and AI systems process knowledge that is far too complex for current databases. They require an expressive data model and an intelligent query language to perform knowledge engineering over complex datasets.
Grakn provides the knowledge base foundation for intelligent systems to manage complex data. We will also introduce Graql: Grakn's reasoning (through OLTP) and analytics (through OLAP) query language. Graql provides the tools required to do knowledge engineering: an expressive schema for knowledge modelling, reasoning transactions for real-time inference, distributed algorithms for large-scale analytics, and optimisation of query execution. And finally, we will discuss how Graql’s language serves as unified data representation of data for cognitive systems.
#Speaker bio
Haikal is the Founder and CEO of GRAKN.AI. His interest in the field began at the Monash Intelligent Systems Lab, where he built an open source driver for the Parallax Eddie Robot which was then adopted by NASA. After which, he completed a Master’s degree in AI from the University of Cambridge. Haikal was also the youngest Algorithm Expert behind Quintiq’s Optimisation Technology behind some of the world’s largest supply chain systems in transportation, retail and logistics