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Complexica Expands its Scientific Advisory Board

12 September 2016

Complexica Pty Ltd, a leading provider of Artificial Intelligence software for optimising sales & marketing activities, announced today that it has added three international experts in the field of Artificial Intelligence to its Scientific Advisory Board, namely: Dr. Pablo Moscato from the University of Newcastle; Dr. Vic Ciesielski from RMIT, and Dr. Łukasz Brocki from Primespeech.

“The newly appointed members of our Scientific Advisory Board will contribute to our research activites in the areas of data science, genetic programming, data mining, deep learning, recurrent neural networks, and language modeling” said Dr. Zbigniew Michalewicz, Chief Scientist of Complexica. “It’s a pleasure for me to announce this very notable addition to our scientific team.”

Łukasz Brocki received his Ph.D. degree from the Polish-Japanese Academy of Information Technology, where his research was focused on using recurrent neural networks for acoustic and language modeling for speech recognition. Łukasz took part in several European scientific projects including Luna, EU-Bridge or Clarin. His current research interests focus on deep learning, stacked LSTM neural networks, extreme learning machines and evolutionary computation. He has published several papers on using neural networks in language technology and prediction tasks.

Pablo Moscato is an Australian Research Council Future Fellow (2012-16) and a Professor of Computer Science at The University of Newcastle.  At the California Institute of Technology (1988-89) he developed a methodology called memetic algorithms, which is now widely used around the world in Artificial Intelligence, Data Science, and Business and Consumer Analytics. His work and ideas have been highly influential in a large number of scientific and technological fields and his manuscripts have been widely cited. The journal "Memetic Computing" is largely dedicated to a methodology he championed. Every 48 hours a new published paper describes a novel application of these techniques.

Vic Ciesielskihas a long track record of successfully applying Artificial Intelligence to industrial problems. He has provided the scientific direction for over 20 industry projects of various sizes, which have involved the application of Artificial Intelligence techniques. These include an insurance underwriting system based on expert system technologies, an obstacle avoidance system for autonomous mining vehicles operating in tunnels, which uses machine learning and computer vision techniques, and a malt quality analysis system based on machine learning and texture analysis. Most recently he is responsible for the data mining behind the realas.com.au house price prediction app.

 

     

Topics: Artificial Intelligence

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