It’s (also) all about team-work. The two of us, Stavros and Vassilis, 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.
Stavros
Theodorakis
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.
Vassilis
Pitsikalis
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.
Stefanos
Angelidis
Senior Machine Learning Engineer - Team Lead
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.
Petros
Katsileros
Senior Machine Learning Engineer - Team Lead
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.
Aigli
Korfiati
Senior Machine Learning Researcher
MSc in Computer Science and Engineering (University of Patras,2014) and PhD candidate in biomedical informatics, specializing on Computational Methods for Transcriptomics Data Analysis. 10-year work experience as a software and machine learning engineer in six R&D European and Greek National Projects and as a product development manager of a machine learning empowered bioinformatics startup in the fields of precision medicine and nutrition.
Aris
Konidaris
Machine Learning Engineer
MSc (Technical University of Crete, Chania, Greece, 2021) in Electrical and Computer Science focused on Distributed Online Machine Learning and Dig Data technologies. Aris is an experienced Machine Learning and Big Data Engineer with a demonstrated history of working on industry and research alike. He specialises in the development of large-scale end-to-end production-level A.I. driven systems. Highly interested in Deep Learning, Reinforcement Learning and Streaming Analytics.
Giannis
Gkinis
Machine Learning Engineer
Msc (NTUA, 2019) in Geoinformatics with a focus on satellite imagery classification and transfer learning. He has spent the past 3 years working as a machine learning and data engineer, with a focus on various NLP, speaker recognition and computer vision projects. Highly interested in machine learning, deep learning and big data.
Nikos
Antonopoulos
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. 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.
Alexandros
Georgogiannis
Machine Learning Researcher
MSc (Technical University of Crete, Chania, Greece, 2014) in “Convex Optimization Methods for Machine Learning” and PhD (Technical University of Crete, Chania, Greece, 2022) in “Statistical Learning Theory”. Highly interested in statistics, probability and combinatorics.
Markos
Diomataris
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.
Afroditi
Kravari
HR & Business Ops
Integr. Hons (Manchester Metropolitan University, 2017) International Business/ Law & Marketing. Dissertation in “Developing a Digital Business”. Work experience in Marketing & HR/ Business Administration for companies in Greece and the UK. Business Administration and Psychology at Work 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.
Nikiforos
Mandilaras
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.
Panos
Antoniadis
Junior Machine Learning Engineer
Electrical & Computer Engineering 5-year degree (NTUA, 2021). Master thesis was on the topic of visual emotion recognition and was supervised by P. Maragos at NTUA. He has previously participated in Google Summer of Code where he implemented an online Greek mail dictation system. Strong interest in machine learning, computer vision and natural language processing.
Pantelis
Papageorgiou
Junior Machine Learning Engineer
BSc in Computer Science (NKUA 2021). Bachelor thesis was on the topic of unsupervised discovery of interpretable directions in the latent space of GANs and was supervised by Y. Panagakis at NKUA. Pantelis main focus lies in the field of deep learning and computer vision. He is also passionate about deploying solutions for real world applications, while utilising federated learning techniques.
Christina
Sartzetaki
Junior Machine Learning Engineer
Electrical & Computer Engineering 5-year degree (NTUA, 2022). Master’s thesis was on the topic of video question answering in social situations, a field at the intersection of computer vision and natural language processing, and was supervised by A. Potamianos at NTUA. Christina is passionate about building real world applications of impact, and AI that is human-centered, ethical, and fair.
Alexandros
Pittis
Research Associate, External Collaborator
PhD (CRG/UPF, 2016) in comparative genomics, phylogenomics, and cellular evolution. Served as post-doctoral research scientist at the American Museum of Natural History (AMNH), EMBO post-doctoral fellow at the University of British Columbia (UBC), and independent research fellow at the Berlin Institute for Advanced Study (WIKO). Strong interest in genome analysis and protein evolution, keen on exploiting evolutionary information to address biological questions.
Aris
Vrahatis
AI bioinformatics consultant, External Collaborator
PhD (UPATRAS, 2016) in Machine Learning and Bioinformatics. He is an Assistant Professor of Artificial Intelligence in Modeling Complex Systems, in the Department of Informatics, Ionian University, Corfu, Greece, and a member of the Bioinformatics and Human Electrophysiology Laboratory in the same Department. His research interests include Machine Learning, Biomedical Data Mining, Biological Complex Systems Modeling, and Network Medicine. He has more than 50 publications in journals and conference proceedings, including Oxford Bioinformatics, BMC genomics, IEEE journal of biomedical and health informatics, and Cellular and molecular life sciences.
Aristotelis
Misios
Bioinformatics expert consultant, External Collaborator
MSc in theoretical computer science and MSc in bioinformatics and systems biology, with a BSc in mathematics. PhD candidate in Bioinformatics at the Max Delbruck Center (MDC-berlin) and Humboldt University (Expected 2023). Extensive work in bioinformatics pipelines, single cell omics analyses, biological data analysis and machine learning applications. Certified carpentries instructor. Interested in Machine learning applications on single cell data.
Nikos
Ganatsios
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.