Shaping the future of commercial shipping

An open lecture by:

Konstantinos Chatzimichalis & Polykarpos Meladianos

When: Wednesday, 26 February, 18:30-19:30
Where: Pierce Amphitheater

Organized by: The Graduate Master Class Series, School of Graduate and Professional Education

To reserve your place please contact Ms Maria Kritikou via email: [email protected] or telephone: 210 6009800 ext. 1210


Lecture Description

Maritime Transport is the backbone of the global economy as 90% of globally traded goods have been on a ship at some point of their logistical trail. Signal Ocean is a technology company that develops solutions to enhance commercial shipping performance. The company invests a lot on developing novel algorithms and machine learning models to gather and fuse information from various sources and to predict vessel movements. We will give an overview of the problems we aim to solve and then focus more on the Natural Language Processing (NLP) side of the business.

Konstantinos Chatzimichalis

Konstantinos Chatzimichalis is a VP of Data Science Engineering at Signal Ocean where he has worked at for the last 5 years. He previously worked at the asset management part of Barclays Capital and at GLI. He is a graduate of the Applied Mathematics and Physical Sciences school of NTUA and holds an MSc in Mathematical and Computational Finance from the University of Oxford. His experience and interests lie in the areas of Data Science, Software Engineering, Financial Mathematics and Product Management.

Polykarpos Meladianos

Polykarpos Meladianos is currently a data scientist at Signal Ocean where he works on data ingestion pipelines and models. Previously he worked on OpenPaaS speech to text summarization project and the National Library of Greece Web Archive. He has obtained a Ph.D. from Athens University of Economics and Business(AUEB) in 2018, a Master on Data Sciences from Ecole Polytechnique, Paris in 2016 and his engineering diploma from the Electrical and Computer Engineering (ECE) department of the Aristotle University of Thessaloniki (AUTH), Greece in 2013. His interests include the areas of machine learning, data mining, neural networks focusing on text mining and natural language processing.”