The Large Scale Machine Learning and Cloud Data Engineering Lab (ML @ Cloud) was established in January 2021 (Government Gazette 153 – 21/01/2021) at the Department of Computer Engineering and Informatics, University of Patras. 

The main purpose of the Laboratory is the high level interdisciplinary research on issues related  to the extraction of knowledge from large volumes of data, using algorithms, machine learning and statistical inference for the extraction of knowledge and predictions, as well as decentralized building techniques for efficient multi-dimensional indexing data stored on distributed cloud computing systems. The main goal is the efficient storage of the above data in NoSQL databases of the cloud network nodes as well as the efficient processing and optimization of queries on these databases, in order to extract new knowledge.

The Laboratory is essentially the merger of two prior Laboratories of the Department. The first is the Pattern Recognition Laboratory and the second is the Graphic and Multimedia Laboratory. By decision of the General Assembly of the Department of Computer Engineering & Informatics, all the technological equipment, the furniture, the books and the spaces of the two Laboratories that were abolished, are transferred to the new Laboratory. Also, all the scientific work produced by the two Laboratories as well as all their research / development projects, will be included in the new Laboratory. 

The courses supported by the Laboratory of Large Scale Machine Learning and Cloud Data Engineering include Decision Theory, Computational Intelligence, Artificial Intelligence (in co-teaching) and at postgraduate level Decentralized Big Data Management, Learning Algorithms and Decision Theory. 

Pattern Recognition, in the 80’s, was an emerging technology and although today it has not been surpassed, it is a small part of the wider scientific area of ​​Machine Learning. Machine Learning explores the study and construction of algorithms / methods for constructing models that can learn from data and make predictions about it. Recently, these Machine Learning techniques have been used to process and extract knowledge from large volumes of data. Graphics, Multimedia and Geographic Systems technology, in the 80’s, was an emerging technology and although today it has not been surpassed, it is a small part of the wider scientific area of ​​Data Engineering and in fact of large volumes of data that is stored on cloud computing infrastructures (Cloud Multimedia Platforms, GPU Cloud Computing). Cloud Data Engineering investigates the design and construction, mainly of decentralized algorithms / methods / techniques, with the ultimate goal of efficient storage, structuring, management, retrieval and processing of cloud data, most often with Machine Learning techniques, to enable the construction of software systems with real response time.

Some distinctions of the ML@Cloud Lab include:

  1. Research Papers Awards and Distinctions:
  • Subject Classification of Learning Resources Using Word Embeddings and Semantic Thesauri, Best paper award, Int. Symposium on Innovations in Intelligent Systems and Applications, (IEEE-INISTA),  2019.
  • IRaaS: A Cloud Implementation of an Interface Relaxation Method for the Solution of PDEs (co-author), Certificate of Merit, 2015 International Conference of Parallel and Distributed Computing (ICPDC’15), part of World Congress on Engineering 2015 (WCE 2015).
  • Predicting Human miRNA Target Genes Using a Novel Evolutionary Methodology Predicting Human miRNA Target Genes Using a Novel Evolutionary Methodology (co-author) – Best Student Paper Award, SETN 2012 – Hellenic Association of Artificial Intelligence.
  • Analyzing Human Proteome: From Protein-Protein Interaction Prediction to Protein Complex Prediction and Function Characterization of Proteins (co-author) – Best Student Paper Award, 5ht Panhellenic Conference on Biomedical Technology, ELEVIT 2012. 
  1. Competitions
  • Imagine Cup 2007 – The World’s Premier Student Technology Competition  ( Software Design) (Advisor) – 2nd Winner, Microsoft – Greece.
  • BioInBook – A Book of Bio-Intelligent Services (project supervisor) – 1st Winner, Hellenic Startup BioMed 2013 – IEEE EMS.
  • InSyBio Ltd (co-founder), 2nd Winner,  MIT Enterprise Forum – Greece Startup Competition, 2016.
  • As part of the Startup BioMed 2013 competition award, in addition to the cash prize, there was mentoring for the founding of Startup InSyBio (Intelligent Systems Biology), of which lab members are founders. The company currently has its headquarters in Patras (in the Science Park) and branches in the UK. (London) and in the USA (Texas).
  1. References in Patents

Results of the below research paper have been used in patents filed by the following large companies:“ ARCHIMIDES: An Intelligent Agent for Adaptive Personalized Navigation within a WEB Server”, HICSS-32 Mini-Track on Software Agents, Maui, Hawaii, V. 5, p. 5020, January 5-8, 1999.  

  1. IBM

https://patents.justia.com/patent/6990494

  1. NEC

https://patents.justia.com/patent/7043685

  1. Google

https://patents.google.com/patent/US6990494B2