PYRSOS AI

Driving the AI strategy in TMC2s portfolio, creating technological value and unique IP.

A research and consulting business with a unique level of expertise in Artificial Intelligence and developing scalable solutions to big problems in a wide range of industries.

Our team have over 70 patents for their “inventions” and more in the pipeline.We have a proven track record of commercialisation of our creations.

The team

Dr. Nadine Kroher

Co-Founder

Nadine’s PhD in Applied Mathematics specialises in machine learning and pattern recognition for content-based music analysis.

Her work at Pyrsos addresses challenging AI problems in a variety of areas, including computer vision, machine listening, time series prediction and generative neural networks. She holds several patents in the field and has co-authored numerous journal publications and conference papers.

As well as her PhD, Nadine has a BSC and MSc in Electrical and Audio Engineering, a further MSc in Sound and Music Computing, and is a former employee of the Music Technology Group, Pompeu Fabra University, where she worked on audio analysis, pattern recognition, and machine learning.
Nadine’s PhD in Applied Mathematics specialises in machine learning and pattern recognition for content-based music analysis.

Her work at Pyrsos addresses challenging AI problems in a variety of areas, including computer vision, machine listening, time series prediction and generative neural networks. She holds several patents in the field and has co-authored numerous journal publications and conference papers.

As well as her PhD, Nadine has a BSC and MSc in Electrical and Audio Engineering, a further MSc in Sound and Music Computing, and is a former employee of the Music Technology Group, Pompeu Fabra University, where she worked on audio analysis, pattern recognition, and machine learning.

Dr. Aggelos Pikrakis

Co-Founder

Besides his work at Pyrsos, Aggelos is an Assistant Professor at the University of Piraeus, Greece.
His research interests lie in the areas of machine learning/AI for audio, video, speech and music signals with an emphasis on deep neural network architectures, dictionary learning algorithms, hidden Markov Models and dynamic time warping techniques.

He is a co-inventor of granted patents on music recommendation technology and he has co-authored two international textbooks with Academic Press, as well as more than 50 research papers in international journals and conferences. He has also served as an Associate Editor of the EURASIP Journal on Advances in Signal Processing.

During the past 15 years, he has been teaching various courses related to audiovisual signal processing and machine learning and is supervising numerous Ph.D. theses. His work has received award recognition through the years, including a 1st position in the MIREX contest for algorithms, an IEEE MMSP best paper award (co-author) and the 2019 EURASIP Meritorious Service Award.

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