Yannis Stylianou is Professor of Speech Processing at University of Crete and Senior Research Scientist at Apple. Former positions include AT&T Labs Research, Bell-Labs, and Toshiba Cambridge Research Lab. IEEE Fellow with PhD from ENST-Paris and over 200 publications. Research spans: Adaptive speech/audio modeling Neural speech synthesis/enhancement Biomedical signal processing Awards include: IEEE Fellowship French Ministry Research Fellowship ENST Graduate Scholarship Recent work focuses on neural TTS architectures, intelligibility enhancement, and multimodal synthesis. Organizes annual International Summer School on Speech Processing.
Dr. Vivi Tornari is a Research Fellow and head of the Holography laboratory at IESL/FORTH, specializing in optical metrology and cultural heritage preservation. She has held this position since 1996 and has coordinated major EU projects such as E-RIHS and CHARISMA . Her work focuses on developing holographic interferometry techniques for structural diagnosis of artworks, fraud detection, and environmental impact assessment. She holds a PhD in Applied Science from the University of Sunderland and has authored over 70 scientific publications. Education: Postdoctoral Fellow in Optical Holography, Royal College of Art (RCA), London (1990) PhD in Applied Science, University of Sunderland, UK (2009) MSc in Chemical Engineering/Material Science, National Technical University of Athens (1996) Research interests include laser-based structural analysis, speckle interferometry, and the integration of optical methods for heritage preservation. She has pioneered non-invasive diagnostic tools such as the Applied Holography Metrology Laboratory and has advised on EC projects as an evaluator. Funding highlights include: Leadership in EU projects totaling over €20M Coordinator of SYDDARTA (FP7) and CLIMATE FOR CULTURE (FP7) PI for HOLOAUTHENTIC (FP5) and LASERACT (FP6) Her publications emphasize interdisciplinary collaboration, combining optical engineering with conservation science. Key innovations include: Development of DHSPI (Digital Holographic Speckle Pattern Interferometry) Integration of thermography with interferometry for defect analysis Laser ablation studies on polymer substrates Labs/Teams: Lead the Holography Lab at IESL, collaborating with international institutions like the V&A Museum and Imperial College London. Current projects focus on European research infrastructures (E-RIHS) and climate change impacts on heritage materials.
Christos Diou is an Associate Professor of Artificial Intelligence and Machine Learning at the Department of Informatics and Telematics, Harokopio University of Athens, Greece. His academic career spans over 15 years of participation in national and international research projects, with a focus on machine learning algorithms, domain generalization, causal inference, and bias mitigation. He earned a BSc and Ph.D. in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research emphasizes the application of machine learning to healthcare, addressing challenges such as visual bias mitigation, causal effect estimation from observational data, and fairness-aware representation learning. Notable projects include REBECCA and RELEVIUM , both EU-funded, and MELIORA , targeting lifestyle interventions for breast cancer risk reduction. He has published extensively in top-tier venues like IEEE TPAMI, CVPR, and ICCV. Christos is a leading voice in AI ethics and healthcare innovation, with over 150 publications and best paper awards at IEEE Big Data Service 2023 and AIAI 2022. His work includes developing platforms like Effector for feature effects and Beam for behavior studies. He collaborates with institutions such as Karolinska Institutet and CERTH/ITI, and his students include PhD candidates Ioannis Sarridis and Aristotelis Ballas.
Panagiotis G. Zervas is an Associate Professor at the Department of Electrical and Computer Engineering, University of Peloponnese (since 2020). His expertise spans audio signal processing, music information retrieval, and natural language processing for knowledge extraction. He teaches courses including Signals & Systems, Digital Signal Processing, and Machine Learning. His research focuses on AI-driven applications in sound analysis, music feature extraction, and multimodal information processing. Education: PhD (2007) in Electrical Engineering from the University of Patras, specializing in Greek prosody modeling for text-to-speech systems. Previous roles include Assistant Professorships at Hellenic Mediterranean University (2015–2020) and Technical Educational Institute of Crete (2008–2015). Research Interests: Natural Language Processing (NLP) for text analysis and large language models (LLMs) Audio signal processing, voice analysis, and embedded systems AI applications in job market analytics and skills frameworks Machine learning for music information retrieval Notable Projects: Principal Investigator in EU projects EU-ALMPO (2025–), Train4Blue (2025–), GROWTH4BLUE (2024–), and MICROIDEA (2024–) World Bank consultant (2023–) for AI-driven employment systems in Greece and Pacific Islands Publications in journals like 'Acoustics' and conferences like WAC 2022 and Forum Acusticum 2023 Office: Building K, Office K2.07 | Contact: pzervas@uop.gr
Professor Papaloukas Konstantinos is affiliated with the University of Ioannina, where he leads research in bioinformatics and computational biology. His work focuses on integrating machine learning with biomedical data to address challenges in healthcare, such as disease prediction, biomarker discovery, and personalized medicine. He teaches courses including Bioinformatics and Introduction to Computer Science, and directs the Bioinformatics Laboratory. Research interests span computational analysis of proteins, automated tissue classification, and biomedical signal processing. Key areas of exploration include cardiovascular disease mechanisms, diabetes management, autoinflammatory disorders, and cancer biomarkers. His most recent studies leverage ensemble learning for hypoglycemia prediction and deep learning for autoinflammatory biomarker discovery. Publications highlight contributions to multimodal patient data integration, synthetic data generation for chronic diseases, and multimodal glucose prediction systems. Collaborative projects span cardiology, oncology, and infectious disease research. Despite no explicitly listed awards, his work demonstrates significant impact in computational medicine and bioinformatics. As part of his academic role, he advises students in bioinformatics and computational biology, though specific advisee names are not documented in available materials. His laboratory focuses on translating genomic and clinical data into actionable insights for clinical decision support.
Zervakis Michalis is a full Professor at the Technical University of Crete (TUC), serving as Rector and Director of the Digital Image and Signal Processing Laboratory (DISPLAY). He holds a Ph.D. in Electrical Engineering from the University of Toronto (1990) and has been a faculty member at TUC since 1995. His expertise spans Digital Image/Signal Processing, biomedical applications, and neural network implementations in automation. Education: Ph.D., Electrical Engineering, University of Toronto (1990) M.Sc., Electrical Engineering, University of Toronto (1985) B.Sc., Electrical Engineering, Aristotle University of Thessaloniki (1983) Research Interests: Signal/image processing for biomedical applications Machine learning for healthcare diagnostics EEG/ECG analysis and seizure detection Neural network architectures for automation Multi-sensor systems and aerial surveillance His research emphasizes clinical applications like epilepsy monitoring and cardiovascular diagnostics, leveraging deep learning and multimodal data fusion. He has led over 20 international projects and published >90 papers in image/signal processing. Current work focuses on AI-driven medical systems and UAV-based infrastructure monitoring. Labs/Teams: Director of the DISPLAY Lab, collaborating on projects like the BorderUAS semiautonomous surveillance platform and the Pulsense cardiovascular monitoring system. Grants/Contributions: Extensive involvement in EU-funded initiatives and industry partnerships, advancing smart farming, power line inspection, and emergency response systems.
Konstantinos A. Tsintotas is an Assistant Professor at the Department of Information and Electronic Engineering, International Hellenic University. His research focuses on artificial intelligence, robotics, computer vision, and their applications in smart cities, healthcare, and manufacturing. He is actively involved in advancing AI-driven systems for critical infrastructure management, robotic vision, and embedded device technologies. His work spans theoretical advancements and practical implementations, including projects like SLAM algorithms for autonomous navigation, deep learning models for medical diagnosis, and IoT-integrated smart supply chains. Tsintotas also explores ethical implications of AI in human action recognition and contributes to neuromorphic computing through spiking neural networks. Key technical contributions include ReJSHand (real-time hand pose estimation), fall detection systems for embedded devices, and visual place recognition frameworks. His interdisciplinary approach bridges computer science, electrical engineering, and biomedical applications, reflecting a strong commitment to innovation at the hardware-software interface. Notable trends in his publications emphasize AI ethics, multimodal perception for robotics, and low-power embedded solutions. Ongoing work includes advancing digital twin technologies for supply chains and refining bio-inspired neural architectures for robotics applications.
Themos Stafylakis is an Associate Professor at the Department of Informatics of Athens University of Economics and Business (AUEB), a role he assumed in 2023. He also serves as the head of the Machine Learning and Voice Biometrics departments at Omilia (Cyprus and Greece) since 2018. Additionally, he collaborates as a researcher at the Archimedes unit of the "Athena" Research Center. His academic journey includes a PhD in voice applications from the School of Electrical and Computer Engineering of NTUA (2011), a master's from Imperial College London (2005), and a bachelor's from NTUA (2004). Professional experience includes postdoctoral research at ÉTS University of Montreal (2011-2013) and CRIM research center (2011-2016), followed by work at the University of Nottingham on audiovisual speech recognition under a Marie Sklodowska-Curie fellowship (2016-2018). His research focuses on speaker recognition, audiovisual speech processing, and machine learning applications. Key contributions include advancements in speaker verification, diarization, and self-supervised learning techniques. He has contributed to datasets like KAN-AV and participated in challenges such as NIST-SRE and ASVspoof. Educations: Bachelor's: School of Electrical and Computer Engineering, NTUA (2004) Master's: Imperial College London (2005) PhD: NTUA (2011) His research interests span speaker recognition, audiovisual speech analysis, and machine learning innovations. Notable achievements include developing robust speaker verification systems and contributing to spoofing detection methodologies. He has received a Marie Sklodowska-Curie Individual Fellowship (2016-2018). His work bridges academia and industry, with applications in biometric systems, conversational AI, and multimodal data analysis. Collaborations include institutions like CRIM, ÉTS, and the Athena Research Center.
Michalis Paraskevas is a Professor at the Department of Electrical and Computer Engineering, University of Peloponnese. He specializes in Signal Processing Systems, Broadband Networks, and Telematics Services. He graduated from the University of Patras (1989) and earned his Ph.D. there (1995). His research focuses on digital signal processing, information theory, machine learning applications in image and NLP, and digital education transformation. He has authored 4 textbooks, published over 85 papers, and contributed to 50+ conference committees. He has led large-scale network projects recognized nationally/internationally. He served as Department Head (2019–2021) and directed the 'Data and Media' Lab. Currently, he is Vice President of the Institute of Computer Technology & Publications 'Diofantos', heads the National Support Organization for eTwinning, and coordinates the Greek School Network. Teaching includes undergraduate courses like 'Signals and Systems' and postgraduate programs in Advanced Educational Technologies and STEM education. He is affiliated with TEE, IEEE, and AES.
Alexandra Christina is affiliated with the Department of German Language and Literature at the National and Kapodistrian University of Athens. Her work bridges computational linguistics, human-computer interaction (HCI), and political/journalistic text analysis. She specializes in natural language processing (NLP), sentiment analysis, terminology management, and multilingual applications. Her research focuses on extracting implicit information from spoken and written texts, with applications in medical chatbots, aircraft maintenance communication, and political discourse analysis. Notable projects include the 'Athena' medical chatbot, Gricean maxim modeling in NLP, and HCI design for international conferences. Key Areas: Generative AI, ethical AI frameworks, cross-lingual dialogue systems, and cognitive bias analysis in ancient/modern texts. Publications: Over 100 peer-reviewed articles since 2007, including works on terminology databases, HCI conference proceedings, and sentiment analysis platforms. Her recent work emphasizes socially responsible AI, integrating NLP with ethical guidelines, and leveraging crowd-sourced data for unspoken sentiment detection. She collaborates on multilingual terminology projects like TERMONLINE and CNCTST database initiatives.
Athanasios Liavas is a Professor at the Technical University of Crete (TUC), School of Electrical and Computer Engineering (ECE), where he has served as Department Chair (2009-2011) and Vice Chair (2011-2013). He holds a Diploma (1989) and PhD (1993) in Computer Engineering and Informatics from the University of Patras. His career includes postdoctoral research at the Institut National des Télécommunications (1996-1998) as a Marie Curie Fellow, and academic roles at the University of Ioannina and the University of the Aegean before joining TUC in 2004 as Associate Professor. He has been a Professor since 2009. His research focuses on Signal Processing for Communications , Information Theory , and Telecommunications , with recent emphasis on tensor decomposition techniques for biomedical signal analysis and machine learning applications. He leads the Telecommunications Laboratory and teaches courses such as Digital Communication Systems II and Wireless Communication Systems. He served as an Associate Editor for the IEEE Transactions on Signal Processing (2005-2009) and was a member of the IEEE SP COM Technical Committee (2006-2011). His recent work includes advancements in nonnegative tensor completion, parallel algorithms for large-scale tensor factorization, and generalized canonical correlation analysis for multi-subject fMRI data. These contributions address challenges in high-dimensional data reconstruction and brain imaging signal processing, leveraging stochastic optimization and distributed computing frameworks. Liavas has authored over 80 peer-reviewed articles, with key contributions in IEEE journals and conferences. His research spans theoretical signal processing, algorithm design, and practical implementations for telecommunications and biomedical engineering.
Anastasios Gounaris is a Professor at the Department of Informatics, Aristotle University of Thessaloniki, where he has been a faculty member since April 2008. He previously served as a Visiting Lecturer at the University of Cyprus (2007-2008) and held research positions at the University of Manchester and CERTH. His academic journey includes a PhD from the University of Manchester (2005), an MPhil from UMIST (2002), and a degree in Electrical and Computer Engineering from Aristotle University of Thessaloniki (1999). His research spans Distributed Databases, Autonomous Data Processing, Big Data Management, Workflow Optimization, and Data Mining . He has made significant contributions to large-scale data management systems, massive parallelism techniques, and business process analytics. His work bridges theoretical computer science with practical industrial applications, particularly in predictive maintenance and edge computing environments. His recent publications (2024-2025) demonstrate a strong focus on process mining, anomaly detection, predictive maintenance systems, and edge analytics . These works address critical challenges in handling evolving data streams, optimizing task allocation in resource-constrained environments, and developing parameter-free algorithms for real-world applications. His research shows consistent progression from foundational database systems work to cutting-edge applications in industrial IoT and healthcare analytics. Dr. Gounaris has successfully supervised numerous PhD students to completion, including Athanasios Naskos (2017), Georgia Kougka (2017), Christos Bellas (2022), Theodoros Toliopoulos (2022), Anna-Valentini Michailidou (2023), Ioannis Mavroudopoulos (2024), and Konstantinos Varvoutas (2025). His research has been supported by multiple national and European projects including DataflowOpt, PRECognition, NavGreen, CUREX, Rainbow, Lifechamps, and Trineflex. He is an active member of Datalab (formerly Delab) and has contributed to industry applications through collaborations with companies such as Comidor, Gnomon, Istognosis, Atlantis, AFS, Follow-Apps, Sboing, and Upcom. His work demonstrates a strong commitment to transferring research results to real-world applications while maintaining academic rigor.
Michalis Zervakis is a Professor at the Technical University of Crete , affiliated with the School of Electronic and Computer Engineering and its Department of Electronic and Computer Engineering. He serves as a laboratory director at the Digital Signal and Image Processing Laboratory since 1990 and teaches courses on Digital Signal Processing and Digital Image Processing. Education Ph.D. in Electrical Engineering, University of Toronto (1990) M.Sc. in Electrical Engineering, University of Toronto (1985) B.Sc. in Electrical Engineering, Aristotle University of Thessaloniki (1983) His research focuses on digital image and signal processing , with applications in biomedicine and telecommunications. He explores pattern recognition , neural networks , and machine learning for medical diagnostics (EEG, ECG, MRI), industrial monitoring, and aerial surveillance systems. Recent publications reveal trends in biomedical signal processing (EEG/MEG/MRI), medical AI , and computer vision for UAV applications . Key subfields include seizure detection, traumatic brain injury analysis, cardiovascular monitoring, and interpretable machine learning frameworks. Leadership Roles Former Laboratory Director (University of Minnesota, Technical University of Crete) Associate Editor for IEEE Transactions on Signal Processing Collaborations Participation in Greek/European/international scientific programs Conference organization (e.g., IEEE IMS Technical Committees)
Nancy Zlatintsi is a Postdoctoral Research Associate at the National Technical University of Athens (NTUA) in the Computational Vision and Signal Processing (CVSP) group at the School of Electrical and Computer Engineering. She earned her Diploma in Media Engineering from KTH Royal Institute of Technology (2006) and a Ph.D. in Audio and Multimedia Processing from NTUA (2013). Her research focuses on Music Information Retrieval (MIR) , audio signal processing , and multimodal interaction , with applications in human-robot interaction and movie summarization . Her work has been funded by the European Social Fund (Heracleitus II program) and she has contributed to European projects like iMuSciCA and e-Prevention . Her research spans multimodal saliency detection , audio event recognition , and computational models for emotion tracking . Key scientific contributions include publications in top venues such as IEEE ICASSP , CVPR , and EURASIP Journal on Image and Video Processing . She is also involved in assistive robotics and gerontechnology applications. Email: nzlat@cs.ntua.gr Office: 2.2.19, NTUA
Panagiotis Filntisis is a PostDoctoral researcher at the National Technical University of Athens , supervised by Prof. Petros Maragos. His work focuses on computer vision and audio processing for affective computing , particularly in areas like body emotion recognition, visual emotion translation, and 3D facial expression reconstruction. Key research projects include: TeachBot : Exploring educational robotics e-Prevention : Developing emotion recognition systems BabyRobot : Investigating multi-party interaction iMuSciCA : Applying multimodal perception in music education He has published extensively on multimodal fusion techniques in child-robot interaction, with recent work appearing in IEEE Robotics and Automation Letters and ICASSP. Contact: filby@central.ntua.gr
