The Team

Previously COO of FTSE listed Man Group, COO and CFO of NYSE listed GLG Partners Inc. – two of the most prominent alternative fund management players globally. Since 2014 he has worked with tech and tech-facilitated start-ups in lending, mobile communications, supply chain finance, digital migration and music NED roles, including the NYSE listed Nomad foods with a $5bn market capitalization.

Ken was previously the head of business development UK for Triller, the globally popular AI-powered social media platform and MXX, the AI technology firm that secured over 30 patents for applications in diverse fields, including fintech, sports, music and media. Ken has twenty years of experience and an excellent track record in global direct and channel sales strategy and has introduced several innovative technologies into the UK as well as the sales models, competencies and processes while building brands, relationships and sales revenues for start-ups in new, existing and emerging markets around the world in b2b fintech, telecoms and SaaS applications.

Robert has over 10 years of sales leadership experience within the City of London focused on the technology and asset finance sectors.  He fosters a competitive but collaborative team mentality that has produced a track record of significant growth across multiple business revenue streams.  
Robert has opened new business units for Xerox, Samsung and Hp partners managing these new initiatives through to a business as usual state. Robert is currently based in East Africa as General Manager of the largest FMCG provider of high end wines and spirits. The company is currently projected to have a revenue growth of 50% since he took up the role in 2020.

Nadine’s PhD in Applied Mathematics specialises in machine learning and pattern recognition for content-based music analysis. Her work at TMC² 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. Occasionally, she composes abstract electro-acoustic music and designs electronic music instruments.

(Eng., Ph.D.): Aggelos Pikrakis is a Scientific Advisor with TMC² and an Assistant Professor with the Department of Informatics at the University of Piraeus, Greece. His research interests lie in the areas of machine learning/artificial intelligence 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 in the areas of pattern recognition and audio analysis, as well as more than 50 research papers in international journals and conferences, including IEEE Transactions on ASLP, IEEE Transactions on Multimedia and IEEE ICASSP. He has also served for a number of years 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 Ph.D. theses in the areas of speech pathology detection, intelligent music sensing and audio event detection in weakly labelled environments. 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. Aggelos provides research advice on state-of-the-art AI technologies for music/image/video recommendation/retrieval problems and pattern mining/knowledge discovery applications.