Our Team

It’s (also) all about team-work. The three of us, Stavros, Vassilis and Nassos,  we know each other for more than a decade. We have worked together in between either during our PhDs and/or as post-doctoral researchers, or for product development. We have more than 10 years of working and research experience in either EU, Greek national, US funded projects, and more than 70 publications in peer reviewed scientific international journals and top research conferences, where we also offer our services as peer reviewers.  We had partners in research projects across several universities, and institutions. We consider the chemistry between all team members  to be a natural ingredient that composes  an inspiring collaborative working environment; this is the vehicle for succesfull work in both industrial and scientific challenging frameworks.


Founder, CEO

PhD (NTUA, 2014) in machine learning and computer vision. Served as research assistant in various EU projects (FP6/7, H2020). Strong research and working experience in a variety of applications in the areas of speech recognition, natural language processing, recommender systems and computer vision, applying state-of-the-art machine learning technologies. Interests in artificial intelligence: machine learning, deep learning, signal processing and reinforcement learning.


Founder & Chief Science Officer

PhD (NTUA, 2007) in signal processing and automatic speech recognition. Served as post-doctoral research associate with long experience in EU research projects (FP6/7, H2020). Interests and work span a variety of artificial intelligence, human-computer interaction and data analytics areas, especially targeting machine learning. Indicative applications include multimodal gesture and action recognition, multimodal fusion, language processing and automatic sign language recognition.


Senior Machine Learning Engineer

PhD (University of Edinburgh, 2018) in Computational Neuroscience & Neuroinformatics. Focus on signal processing and machine learning algorithms for neurorehabilitation. Served as post-doctoral Research Associate at Newcastle University (2018-2020) and University of Edinburgh (2017-2018), as well as Research Assistant at Southampton University (2012). Research experience includes areas such as upper-limb prosthetics, brain machine interfaces, audio signal processing and cryptography. Strong interest in machine learning, robotics and biomedical applications.


Senior Machine Learning Engineer

PhD (University of Nottingham, 2022) in Deep Learning and Computer Vision with focus on localisation tasks, particularly landmark detection and human pose estimation. Has previously interned as a Machine Learning Engineer at SamsungAI Cambridge (2020-2021) and also worked in enterprise software development. His research experience includes areas such as self-supervised learning, semi-supervised learning, self-training and learning from noisy data. Particularly interested in deep learning techniques for training neural networks under minimum manual supervision.


Senior Machine Learning Engineer

PhD (NTUA, 2020) in deep learning and computer vision, with a focus on neural networks and model interpretability. Served as a postdoctoral Research Associate at the Forecasting and Strategy Unit (NTUA, 2020-2021), mainly involved in timeseries forecasting. Have worked for and on behalf of several Greek companies and have participated in regional and EU (H2020) research projects. Also serves as a data science instructor in several bootcamps and a Lecturer at the Athens Tech College. Mainly interested in deep learning theory and applications.


Senior Machine Learning Engineer

PhD (University of Edinburgh, 2019) in natural language processing. Focus on deep learning methods for understanding long-form text with applications on summarization, opinion mining and question answering. Served as a postdoctoral Research Fellow at the University of Edinburgh, working in collaboration with the EdinburghNLP group and Megagon Labs (2019-2021). Has previously interned as an Applied Scientist at Amazon CoreAI. Particularly interested in applying novel deep learning solutions to problems where task-specific supervision is scarce.


Senior Machine Learning Engineer

PhD (EPFL, 2020) in robotics, control, and intelligent systems with a focus on machine learning and natural language processing. Served as a research assistant in various EU H2020 projects and interned as an Applied Scientist at Amazon Alexa. His research experience includes areas such as representation learning, knowledge graphs and natural language understanding. He has a lifelong interest in artificial intelligence, including machine learning, deep learning as well as reinforcement learning.    


Senior Machine Learning Engineer

MSc in Electrical and Computer Engineering (AUTH) with a Diploma thesis in Non Linear Dimensionality Reduction in Pattern Recognition and deep technical skills in AI, Data & Software Engineering. Petros has extensive experience in state of the art Deep Learning algorithms development on production Recommender Systems as also in ML modelling and large scale production systems following the best in class practices for clean code development, big data-engineering and efficient machine learning pipelines.


Machine Learning Engineer

Electrical & Computer Engineering 5-year degree (NTUA, 2020). Master thesis was on the topic of visual relationship detection and was co-supervised by P. Maragos at NTUA and by N. Gkanatsios and V. Pitsikalis at Deeplab. Markos was a member of NTUA’s Prometheus racing team developing software for prototype electric vehicles. Interested in deep learning, fusion of computer vision and natural language processing for tasks related to perception and understanding.


HR & Office Administrator

Ba Hons (Manchester Metropolitan University, 2017) International Business & Marketing. Dissertation in “Developing a Digital Business”. Work experience in Marketing & Business Administration for companies in Greece and the UK. Business Administration Research Assistant (Manchester Metropolitan University, 2016) supporting Ph.D students in research,  surveys and analysing data. Organically growing a career experience in the digital solutions market and the management of niche firms.


Machine Learning Engineer

Electrical & Computer Engineering 5-year degree (NTUA, 2020). Master thesis was on the topic of sign language recognition and human pose estimation and was supervised by P. Maragos at NTUA. Mary was also a co-founder of a fintech start-up that aimed to deliver an automated shopping experience. Her main focus lies in the field of deep learning and computer vision. Highly interested in the fusion of computer vision and language modeling as well as visual understanding and reasoning.


Machine Learning Researcher

MSc (Technical University of Crete, Chania, Greece, 2012) in “Convex Optimization Methods for Machine Learning” and PhD candidate (expected to graduate in 2019) in the field of “Statistical Learning Theory” with PhD dissertation title “On Clustering, Classification and Dictionary Learning: A theoretical revisit of robust k-means, nearest neighbor classification, and dictionary learning with Moreau envelopes”. The research focuses primarily upon statistical aspects of pattern recognition, and to a lesser extent, clustering. Highly interested in statistics, machine learning, and non-linear optimization.


Machine Learning Engineer

Electrical & Computer Engineering 5-year degree (NTUA, 2020). Master thesis was on the topic of dialogue generation using generation-based models and was co-supervised by APotamianos at NTUA and by N. Katsamanis. Manos is interested in deep learning and specifically in natural language processing generation tasks or multimodal tasks combining computer vision and natural language processing


Machine Learning Engineer

MSc (NTUA, 2020) in Data Science and Machine Learning with a focus on neural networks and precisely on Deep Reinforcement Learning. He has previously worked in major Big Data and Data Science projects from Telco, Banking and Energy industries. His interests include a big spectrum of fields such as Deep Learning, Big Data and Distributed Systems.


Machine Learning Engineer

MSc (University of Edinburgh, 2019) in Artificial Intelligence. Masters dissertation on Spatio-Temporal Forecasting with Convolutional LSTM architectures. Background in Mathematics and Physics (joint honours BSc) from the University of Glasgow. ICML 2019  generalization workshop paper on adversarial examples titled “An Empirical Evaluation of Adversarial Robustness under Transfer Learning”. Highly interested in computer vision, natural language processing and deep learning and aspires to build upon and apply knowledge in both modern machine learning techniques and traditional statistics.


ML Engineer, External Collaborator

Electrical & Computer Engineering 5-year degree (NTUA, 2017). Master thesis was about segmentation and classification of fine-grained actions in videos. Nikos has also worked for 1.5 year as an Artificial Intelligence engineer in METIS Cybertechnology, developing Natural Language Processing systems for a commercial chatbot. Interested in fusion of both visual and linguistic cues for rich multimodal representation, perception and understanding.