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Saman AmarasingheView profile

Professor

• Programming Languages
• Compiler Design
• High-Performance Computing
• +5 more

Professor Saman Amarasinghe is a faculty member in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), where he leads the Commit compiler research group at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on programming languages and compilers that maximize application performance on modern computing platforms, with a particular emphasis on high-performance domain-specific languages. Professor Amarasinghe received his bachelor's degree in electrical engineering and computer science from Cornell University in 1988, followed by master's and PhD degrees in electrical engineering from Stanford University in 1990 and 1997, respectively. He joined the MIT faculty as an assistant professor in 1997 and has since become a world leader in his field. Professor Amarasinghe's research interests span programming languages, compiler design, and high-performance computing, with a particular focus on domain-specific languages. His group has developed numerous influential languages and compilers including Halide, TACO, Simit, StreamIt, StreamJIT, PetaBricks, MILK, Cimple, and GraphIt, which deliver unprecedented performance for application domains such as image processing, stream computations, and graph analytics. He has also pioneered the application of machine learning for compiler optimizations, from Meta optimization in 2003 to the OpenTuner autotuner framework. Professor Amarasinghe's publication history reveals a consistent research trajectory toward creating specialized language and compiler solutions that address performance challenges in specific domains while hiding complexity from application developers. His recent work focuses heavily on sparse computing, tensor algebra, graph processing, and the integration of machine learning techniques into compiler technology, demonstrating his ability to identify and address emerging computational challenges. ACM Fellow (2019) As an educator, Professor Amarasinghe has developed the popular Performance Engineering of Software Systems (6.172) class with Professor Charles Leiserson and created innovative project-based courses including the Open Source Software Project Lab, the Open Source Entrepreneurship Lab, and the Bring Your Own Software Project Lab. He also serves as the faculty director of MIT Global Startup Labs, which has helped create more than 20 startups across 17 countries. His research has translated into practical applications through startups like Determina, Inc. (acquired by VMware), demonstrating the real-world impact of his academic work. Professor Amarasinghe co-led the Raw architecture project with Professor Anant Agarwal, which did pioneering work on scalable multicores. His entrepreneurial activities include founding Determina, Inc. based on computer security research from his MIT lab and co-founding Lanka Internet Services, Ltd., the first Internet Service Provider in Sri Lanka, showcasing his ability to bridge academic research with commercial applications.

Dimitris MaroulisView profile

Professor

• Data Acquisition
• Real-Time Systems
• Pattern Recognition
• +6 more

Dimitris Maroulis is a Professor at the Department of Informatics and Telecommunications, University of Athens, leading the Real-Time Systems and Image Analysis Lab (RTS-image). With over 20 years of experience in data acquisition and real-time systems, and 15 years in image/signal analysis, he collaborates extensively with Greek and European hospitals in biomedical informatics. He has led 5 R&D projects and authored 150+ papers with 1400+ citations. University of Athens: Professor (2000–present) Meudon Observatory: Research Fellow (3 years) & Long-term Collaborator (10+ years) Research Interests focus on real-time systems , image/signal processing , and biomedical applications . Key areas include automated segmentation of proteomic images, noise removal methods, and stereo image coding. His 15 most recent publications (2003–2012) span 3D imaging , medical image analysis , and biomedical informatics , with sub-fields like autostereoscopic displays, wavelet-based coding, and computer-aided diagnosis. Awards : Best Paper Award (2012: Integral Image Analysis) Projects include European and national R&D initiatives in image analysis and real-time systems. Labs : RTS-image Lab develops methodologies for biomedical and proteomic applications.

Paschalis AntonisView profile

Professor

• Computer Engineering
• Digital Signal Processing
• Space Systems
• +5 more

Paschalis Antonis is a Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on hardware architectures for space systems, embedded systems, and image compression standards such as CCSDS. He specializes in FPGA implementations, radiation-hardened electronics, and biomarker development for immunogenic responses to cancer therapies. Research Interests: High-performance FPGA-based hardware accelerators Space-grade embedded systems and data compression CCSDS standard implementations for aerospace applications Molecular biomarkers for immunotherapy response prediction Recent Trends: His work emphasizes resilient systems against radiation effects (e.g., SEUs in FPGAs), high-throughput image compression cores for space missions, and interdisciplinary research linking computational hardware with medical diagnostics via prothymosin α analysis. Grants & Labs: Leads the ASPIICS coronagraph project for ESA's Proba-3 mission, involving advanced optical instrumentation and formation flying systems. Collaborates on COTS FPGA utilization in extreme environments.

• Aerospace Engineering
• Fluid Dynamics
• Aerodynamics
• +3 more

Dimitrios Rozakis is an Assistant Professor of Mechanical and Aerospace Engineering. He is actively engaged in research and teaching at the College of Engineering, where he leads the Aerodynamics & Propulsion Laboratory . Education PhD in Aerospace Engineering, National Technical University of Athens (2012) MSc in Fluid Mechanics, University of Manchester (2008) Diploma in Mechanical Engineering, Aristotle University of Thessaloniki (2006) Research Interests His research spans computational and experimental aerodynamics , with particular emphasis on: Transonic and supersonic flows Flow control using plasma actuators Hypersonic boundary-layer transition Reduced-order modelling and machine-learning techniques Turbomachinery aerodynamics Recent work has focused on high-fidelity simulations of buffet phenomena, experimental investigations of plasma-based separation control, and the development of data-driven surrogate models for unsteady aerodynamic loads. Selected Scientific Awards ASME Best Paper Award (2020) European Research Council Starting Grant (2018) AIAA Young Investigator Award (2016) Students, Grants & Funding He currently supervises three PhD students—Maria Koutsogianni, Panagiotis Giannakakis, and Eleni Christoforou—working on projects funded by the ERC, Horizon Europe, and the Greek Secretariat for Research & Technology. Active grants include an ERC Starting Grant on “Physics-informed machine learning for unsteady aerodynamics” (€1.5 M) and a Horizon Europe project on “Green regional aircraft technologies” (€4.2 M). Laboratory & Collaborations He directs the Aerodynamics & Propulsion Laboratory , which houses low-speed and transonic wind tunnels, a Ludwieg-tube facility for short-duration hypersonic experiments, and a high-performance computing cluster (>2 000 CPU cores). Ongoing collaborations include the von Karman Institute, DLR, and ONERA.

• Computer Architecture
• Memory Systems
• Multicore Architectures
• +3 more

Georgios Keramidas is an Assistant Professor in Computer Architecture at the Department of Informatics, Aristotle University of Thessaloniki . He also holds an Adjunct Professor position at the Hellenic Open University and collaborates with institutions like the University of Peloponnese and University of Patras . Research Interests : Computer Architecture, Memory Systems, Multicore/GPU Design, Low-Power Techniques, Fault-Tolerant Systems His work focuses on cache optimization , energy-efficient computing , and security-aware memory design . Key contributions include DVFS frameworks , reuse-distance prediction , and non-deterministic cache mechanisms . Recent article trends highlight innovations in computation-in-memory , IoT platform components , and security/low-power co-design . Patents on image compression and GPU optimization reflect practical applications of his research. Academic Network : Collaborates with institutions including University of Patras , University of Manchester , and TU Dresden

Elias N. ZoisView profile

Associate Professor

• Digital Signal Processing
• Image Processing
• Pattern Recognition
• +4 more

Elias N. Zois is an Associate Professor in the Department of Electrical & Electronics Engineering at the University of West Attica, where he has taught since 2019. Previously, he held positions as Lecturer (since 2009), Assistant Professor (2015-2022), and Adjunct Professor at multiple institutions including the Hellenic Army Academy and Hellenic Police Academy. He received his B.Sc. (1994), M.Sc. (1997), and Ph.D. (2000) in Physics and Electronics Engineering from the University of Patras, Greece. His research focuses on digital signal processing , image processing , pattern recognition , and specialized applications in handwriting biometry and offline signature verification . Recent work extends to smart grid optimization , including load forecasting and non-technical loss detection using machine learning techniques. Analysis of his 15 most recent publications reveals strong interdisciplinary trends: 60% focus on advanced biometric verification using Riemannian geometry and metric learning, while 40% apply machine learning to energy systems. Key methodologies include sparse coding, manifold learning, and neural network ensembles, with consistent applications in security systems and smart grid resilience. He has led multiple funded projects including: BioControl (2021-2023): Experienced Researcher for biometric systems Ireact-NG (2018-2021): Experienced Researcher in smart grid technologies ESA SimSat Engine Enhancement (2011-2015): Theoretical Project Manager for aerospace simulations He directs research at the TELSIP Laboratory (Building Z, University of West Attica), specializing in signal processing and pattern recognition systems.

Themos StafylakisView profile

Associate Professor

• Speaker Recognition
• Audiovisual Speech Recognition
• Machine Learning
• +3 more

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.

Dana Drachsler CohenView profile

Assistant Professor

• Formal Methods
• Deep Learning Security
• AI Safety Verification
• +2 more

Dana Drachsler Cohen is an Assistant Professor at the Faculty of Electrical and Computer Engineering, Technion, leading the SAFE lab (Secure Artificial Intelligence via Formal Methods and Engineering). Her research bridges formal methods and deep learning to establish security guarantees for AI systems. Her research focuses on leveraging formal analysis and synthesis techniques to mathematically prove the safety of deep learning models against adversarial attacks. Key interests include neural network robustness verification, program synthesis for repair, and privacy-preserving AI. The SAFE lab emphasizes practical system development that scales beyond theoretical methods while enhancing model transparency through customized verification programs. Her publication trends show consistent advancement in robustness verification techniques, evolving from pixel-level attacks to global robustness guarantees and privacy certification. Recent work integrates program synthesis with formal verification to create repair mechanisms and quantification methods with mathematical safety guarantees. Dr. Drachsler Cohen actively recruits students (PhD/MSc/BSc) for research in AI security and formal methods. She maintains significant service contributions as committee member for major conferences including PLDI, SPLASH, and POPL.

Zhenman FangView profile

Associate Professor

• Hardware Acceleration
• Computer Architecture
• Big Data Computing
• +7 more

Dr. Zhenman Fang is an Associate Professor in the School of Engineering Science (Computer Engineering Option) and Associate Member in the School of Computing Science at Simon Fraser University, Canada. He founded and directs the HiAccel Lab, focusing on accelerator-rich architectures. His PhD (2014) is from Fudan University, China, with 15 months spent at the University of Minnesota. Prior to SFU, he was a Staff Software Engineer at Xilinx (2017-2019) and a postdoc at UCLA (2014-2017). His research spans: Hardware acceleration for ML, big data, genomics, and HPC FPGA-based customizable computing and near-data processing Compiler/runtime systems for heterogeneous platforms Performance/reliability optimization of accelerator-rich systems His recent publications (2024-2025) focus on FPGA acceleration for machine learning (e.g., on-device training, quantization), computational chemistry, image/video compression, database systems, and reconfigurable computing, demonstrating cross-domain applications of specialized hardware. Awards & Honors: Best Paper Awards: FPL 2024, MEMSYS 2017, TCAD 2019 Best Paper Nominations: ICCAD 2025, FCCM 2025, HPCA 2017, ISPASS 2018 SFU Research Excellence Horizon Award (2025) NSERC Alliance, CFI JELF, and Xilinx University Awards He advises 20+ PhD/Master's students in HiAccel Lab, focusing on accelerator design. Major grants include NSERC Alliance (2020) and CFI JELF (2019). The lab operates a 10-node cluster with FPGA/GPU infrastructure.

Panagiotis TsakalidesView profile

Professor

• Statistical Signal Processing
• Compressed Sensing
• Machine Learning
• +3 more

Panagiotis Tsakalides is Professor of Computer Science at the University of Crete and Head of the Signal Processing Laboratory at FORTH-ICS. His research develops statistical signal processing and machine learning methods with applications in computational imaging, sensor networks, and remote sensing. He has secured over €15M in research funding through 22 projects, including: Horizon Europe TITAN Project (€2.5M): Frugal AI for astrophysics applications H2020 PHYSIS Project (€1M): Sparse processing for hyperspectral systems FP7 CS-ORION Project (€1.3M): Compressed sensing for aerial surveillance Research specialties include non-Gaussian signal modeling, compressed sensing architectures, and distributed processing algorithms. Applications span medical imaging, environmental monitoring, and space systems.

Koutsopoulos IordanisView profile

Professor

• Federated Learning
• Explainable Artificial Intelligence
• Edge Computing
• +3 more

Koutsopoulos Iordanis serves as a Professor in the Department of Informatics within the School of Information Sciences and Technology at Athens University of Economics and Business (AUEB). His office is located at 2, Troias, Kimolou & Spetson Str., 4th Floor, Office 402, with contact details including email jordan@aueb.gr and phone +30 210 - 8203 933. His research spans Federated Learning , Explainable AI for Healthcare , and Edge Computing Systems , with significant focus on the PRE-ACT project for breast cancer radiotherapy optimization. Key interests include energy efficiency algorithms, wireless networking, and AI deployment on resource-constrained devices. His work demonstrates strong interdisciplinary integration between computer science and clinical medicine. Recent publications reveal dominant trends in medical AI applications (particularly breast cancer treatment optimization), federated learning architectures for edge environments, and energy-aware systems . The PRE-ACT project constitutes a major research thrust, combining explainable AI with clinical radiotherapy decision support across multiple international institutions. He actively contributes to wireless networking research with emphasis on Software-Defined Networking (SDN) optimization, controller placement strategies, and tactical MANET implementations. His experimental work includes development of testbeds for federated learning on resource-constrained hardware.

• Electrical Engineering
• High Voltage Systems
• Partial Discharges
• +9 more

Michael Danikas is a Professor at Democritus University of Thrace's Department of Electrical and Computer Engineering. He teaches undergraduate courses (High Voltages I/II) and postgraduate courses (Partial Discharges: Mechanisms and Detection, Insulating Materials). His research focuses on dielectric phenomena, including partial discharges, electrical breakdown, and nanocomposite materials. 1980 B.Sc. in Electrical and Electronic Engineering, University of Newcastle-upon-Tyne 1982 M.Sc. in Electrical and Electronic Engineering, University of Newcastle-upon-Tyne 1985 Ph.D. in Electrical and Electronic Engineering, Queen Mary College, University of London His research interests span partial discharges, insulating materials, and electrical dendrite simulations. Recent publications highlight trends in nanocomposites, transformer oil analysis, and machine learning applications for discharge detection. He leads the Electrical Power Systems Laboratory and investigates high voltage systems. Scientific awards: No personal awards explicitly mentioned. Michael Danikas has published extensively in journals like IEEE Transactions on Dielectrics and Electrical Insulation, focusing on dielectric properties and high voltage engineering challenges. He has supervised no explicit students in the provided text.

Manolis SangriotisView profile

Associate Professor

• Image Processing
• Computer Vision
• Stereo Image Coding
• +4 more

Manolis Sangriotis is an Associate Professor at the National and Kapodistrian University of Athens, affiliated with the Department of Informatics and Telecommunications. His academic journey began with a B.Sc. in Physics (1970), followed by M.Sc. degrees in Electronics and Radioelectrology (1973) and Electronic Automation (1975), culminating in a Ph.D. in Informatics and Telecommunications (1980) from the University of Athens. His research focuses on image processing , computer vision , and 3D imaging , with emphasis on stereo image coding, integral photography, and real-time compression architectures. He explores applications in medical imaging, autostereoscopic displays, and multimedia systems, leveraging wavelet transforms, morphological operations, and statistical clustering. Recent publications (2012–2004) reveal a strong trend toward integral imaging innovations , including rectification frameworks, watermarking, and 3D-DCT compression. His work consistently addresses challenges in multiview data representation, disparity estimation, and photorealistic rendering, bridging computer vision with optical engineering. Scientific Awards: Best Paper Award at IEEE 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (2012) He actively advises PhD students, including Eirini Kostopoulou, Tzanoukos Georgios, and Papageorgiou Louis. His research group collaborates on projects related to real-time systems and image datasets, often supported by institutional grants. As part of the RTSImage laboratory, he contributes to developing computational tools for image analysis and compression, with applications spanning medical diagnostics and 3D display technologies. Future directions include advancing omnidirectional imaging and robustness in automated biomedical assessments.

• Smart Textiles
• Medical Technologies
• Military Materials
• +7 more

Georgios Priniotakis is a Full Professor and Head of the Department of Industrial Design and Production Engineering at the University of West Attica in Athens, Greece. He holds a PhD in Textiles Sensors (2005) from Ghent University and a Master's in Fiber Science and Technology from the University of Leeds (1992). His research focuses on smart textiles for medical and military applications, wearable computing, sustainable materials, and industrial production optimization. He leads the lab of Innovative Textile Technologies for Multifunctional Garments and has coordinated numerous EU-funded projects, including TexModa and Smartex. Dr. Priniotakis is an active member of international organizations like AUTEX and COST Action CA17107, and has authored over 350 publications with an H-index of 12 (Google Scholar). His teaching spans courses like Wearable and Affective Computing and Artificial Intelligence , emphasizing sustainability and interdisciplinary collaboration. Education: PhD in Conductive Textiles (Ghent University, 2005) MSc in Fiber Science & Technology (University of Leeds, 1992) Key Roles: National Representative of Greece to EU Research Boards Scientific Director of EU Projects (e.g., Leonardo, Erasmus+, COST) Research interests include electroconductive textiles for medical diagnostics, environmental durability of composite materials, and upcycling industrial waste into functional textiles. His work bridges academia and industry via co-creation methodologies and digital tools for sustainable design. He chairs the AITAE conference and serves as a reviewer for multiple journals. Grants & Projects: Over 20 years of EU-funded projects, including roles as coordinator for TexModa (textile innovation), Texstra (sustainable logistics), and Difme (digital fashion). His labs develop smart garments for emergency response, healthcare monitoring, and ergonomic workplace solutions. Labs & Teams: Leads the Innovative Textile Technologies lab focusing on multifunctional garments, wearable sensors, and eco-friendly production. Collaborates internationally on circular economy initiatives for fibrous composites and technical textiles.

• Statistical Signal Processing
• Computational Finance
• Nonlinear Time Series Analysis
• +7 more

George Tzagkarakis is a Researcher at the Foundation for Research and Technology-Hellas (FORTH) and affiliated with the Institute of Computer Science (ICS) and the Signal Processing Laboratory. With over 15 years of experience in Scientific Data Analysis and Computational Finance, his expertise includes multimodal data learning, distributed information processing, mathematical modeling, and risk analytics. He holds two PhDs—one in Computer Science (Statistical Signal Processing) from the University of Crete and one in Finance (Risk Quantification) from the University of Bordeaux—as well as a BSc in Mathematics from the University of Crete. Education: PhD in Computer Science (1st in class, highest honors), University of Crete, Greece PhD in Finance, University of Bordeaux, France BSc in Mathematics (1st in class, highest honors), University of Crete, Greece His research focuses on Statistical Signal Processing , Nonlinear Time Series Analysis , Non-Gaussian Heavy-Tailed Models , Compressive Sensing , Distributed Signal Processing for Smart Sensor Networks , and Machine Learning in Operations Research . His work bridges academic and industrial applications, particularly in remote imaging and quantitative financial analysis. George has been recognized with academic distinctions from the University of Crete, FORTH-ICS, and external state foundations. He has contributed to European and national R&D and R&I projects, demonstrating his ability to transfer research into practical solutions.