جست‌وجوی استاد و پژوهشگر

Dollas Apostolosمشاهده پروفایل

استاد

• Reconfigurable Computing
• Hardware Architecture
• Embedded Systems
• +۴ مورد دیگر

Professor Dollas Apostolos serves as a Professor in the School of Electrical and Computer Engineering at the Technical University of Crete (TUC), where he has held leadership roles such as Department Chairman. He directs the Microprocessor and Hardware Laboratory, focusing on reconfigurable computing, embedded systems, and high-performance digital systems. His work emphasizes rapid prototyping and real-world implementation of computational solutions. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign (1987) M.Sc., Computer Science, University of Illinois at Urbana-Champaign (1984) B.Sc., Computer Science, University of Illinois at Urbana-Champaign (1982) Research Interests: Reconfigurable computing architectures FPGA-based acceleration for bioinformatics and genomics Embedded systems and real-time processing Hardware-software co-design for high-performance computing His research bridges theoretical innovation with practical applications, such as FPGA implementations for genome assembly and aquaculture monitoring systems. Publications: Recent work highlights FPGA-based solutions for bioinformatics (e.g., genome assembly acceleration), real-time embedded systems (e.g., fish cage net monitoring), and scalable data processing frameworks. His articles often explore the intersection of FPGA technology with computational biology, embedded vision, and distributed systems. Awards and Affiliations: Senior Member, IEEE and IEEE Computer Society Recipient of IEEE Computer Society Golden Core and Meritorious Service Awards Twice honored with the University of Illinois Teaching Excellence Award He is a co-founder of IEEE conferences like FCCM and RSP, reflecting his leadership in the reconfigurable computing community. Teaching and Labs: Teaches courses on computer architecture, logic design, and VLSI design. The Microprocessor and Hardware Lab under his direction drives advancements in FPGA-based systems, with projects ranging from bioinformatics hardware accelerators to embedded vision systems.

Alvin Cheungمشاهده پروفایل

دانشیار

• Data Management
• Programming Languages
• Software Systems
• +۴ مورد دیگر

Alvin Cheung is an Associate Professor in the Computer Science Division at UC Berkeley's EECS department. He is affiliated with the Data Systems and Foundations group, Programming Systems group, Sky Lab, and SLICE Lab, and serves as a faculty affiliate at the Berkeley Institute for Data Science. He advises the Data Science Discovery Program and provides technical guidance to industry partners. His research spans data management, programming languages, and scalable software systems, with emphasis on helping users process large datasets efficiently. Key innovations include verified lifting (applying formal methods and ML to infer program properties) and systems for optimizing database-backed applications and geospatial analytics. Recent work explores LLM-driven code optimization and transpilation techniques. His publications (2023-2025) show strong trends in ML-enhanced systems, verified compilation, and data management tools. Articles frequently integrate formal methods, program synthesis, and hardware-aware optimizations across domains like databases, distributed computing, and HCI. Scientific Awards: ACSIC Rock Star Award (2025) Dahl-Nygaard Junior Prize (2024) VLDB Early Career Research Contribution Award (2023) IEEE TCDE Rising Star Award (2020) Sloan Fellowship (2019) NSF CAREER Award (2017) 20+ additional honors Advising & Grants: He mentors PhD/MS students (e.g., Lily Liu at OpenAI, Chenglong Wang at Microsoft Research). Research is funded by: NSF DOE ONR ARO Intel Notable grants include ONR Young Investigator Award and ARO Early Career Program Award. Labs & Teams: Leads projects in Berkeley's Data Systems/Programming Systems groups and collaborates with Sky Lab/SLICE Lab. Manages labs focused on verified compilation (e.g., Tenspiler) and data infrastructure (e.g., Spatialyze).

Dimitris Maroulisمشاهده پروفایل

استاد

• Data Acquisition
• Real-Time Systems
• Pattern Recognition
• +۶ مورد دیگر

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.

Themos Stafylakisمشاهده پروفایل

دانشیار

• Speaker Recognition
• Audiovisual Speech Recognition
• Machine Learning
• +۳ مورد دیگر

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.

Zhenman Fangمشاهده پروفایل

دانشیار

• Hardware Acceleration
• Computer Architecture
• Big Data Computing
• +۷ مورد دیگر

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 Tsakalidesمشاهده پروفایل

استاد

• Statistical Signal Processing
• Compressed Sensing
• Machine Learning
• +۳ مورد دیگر

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 Iordanisمشاهده پروفایل

استاد

• Federated Learning
• Explainable Artificial Intelligence
• Edge Computing
• +۳ مورد دیگر

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.

Manolis Sangriotisمشاهده پروفایل

دانشیار

• Image Processing
• Computer Vision
• Stereo Image Coding
• +۴ مورد دیگر

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.

• Compilers
• Computer Architecture
• High-Performance Storage
• +۵ مورد دیگر

Mahmut Taylan Kandemir is a Professor in the Department of Computer Science at Pennsylvania State University. His research spans optimizing compilers, runtime systems, embedded systems, I/O, high-performance storage, and power-aware computing. He leads the Microsystems Design Lab and collaborates with institutions like Argonne National Lab, Microsoft, and Intel. Education: B.S. Computer Engineering, Istanbul Technical University (1988) M.S. Computer Engineering, Istanbul Technical University (1992) Ph.D. Computer Science, Syracuse University (1999) Research Focus: Dr. Kandemir's work integrates hardware-software co-design to address challenges in multi-core architectures, non-volatile memory systems, and energy efficiency. His recent projects explore 3D NAND flash optimization, near-data computing, and reliability in heterogeneous systems. Key themes include reducing data movement overhead, enhancing storage longevity, and developing compiler-directed solutions for emerging hardware. Publications: His articles frequently appear in premier venues (PLDI, ASPLOS, HPCA) and emphasize memory hierarchy optimization, security, and parallelism. Trends include hardware-assisted resilience, approximate concurrency, and energy-efficient VR streaming. Awards: Premier Research Award, Penn State Engineering Society (2017) IEEE Fellow NSF CAREER Award (2000) Best Paper Awards (IPDPS 2008, ICPADS 2006) Top ACM Digital Library Download (2006) Advising & Grants: He has graduated 32 Ph.D. and 20 master's students, with 15 Ph.D. and 5 master's students currently advised. His research is funded by NSF, DARPA, DOE, and industry partners. Active projects include: NSF/OAC: Re-Engineering Galaxy for Performance (2019-2023) NSF/SHF: 3D NAND Flash Optimization (2019-2022) NSF/SPX: Heterogeneous Intermittent Accelerators (2018-2022) Labs & Teams: Leads the Microsystems Design Lab, focusing on architecture-compiler co-design. Collaborates with the Storage Systems Research Center and heterogeneous computing groups at Penn State.

Ioannis Ellinasمشاهده پروفایل

استاد

• Embedded Systems
• Image Processing
• Computer Vision

Ioannis Ellinas serves as a Professor in the Department of Computer Engineering at the School of Engineering, University of West Attica, with a career spanning advanced research in computational engineering disciplines. Education: Diploma in Electrical and Electronic Engineering, University of Sheffield (1977) Master's degree in Microwave Communications, University of Sheffield (1978) PhD in Computer Science and Telecommunications, University of Athens (2006) with thesis "Contribution to the improvement of stereoscopic image and video pair compression algorithms" Research Interests: Professor Ellinas specializes in Embedded Systems design, Image Processing algorithms, and Computer Vision applications. His foundational work on stereoscopic video compression bridges theoretical optimization with practical implementation in multimedia systems, emphasizing efficiency in resource-constrained environments. Current research integrates hardware-software co-design principles to advance real-time visual data processing. Publications: He has authored 36 peer-reviewed papers across international journals and conferences alongside 4 technical books, demonstrating sustained scholarly output in engineering informatics and digital media technologies.

Lisimachos P. Kondiمشاهده پروفایل

استاد

• signal processing
• communications
• image/video compression
• +۸ مورد دیگر

Lisimachos P. Kondi is a Professor at the University of Ioannina in the Department of Computer Science and Engineering, where he has established himself as a leading researcher in signal processing and communications. His academic career spans over two decades with significant contributions to video compression, wireless transmission, and image processing. Education: Diploma in Electrical Engineering, Aristotle University of Thessaloniki, Greece (1994) M.S. in Electrical and Computer Engineering, Northwestern University, USA (1996) Ph.D. in Electrical and Computer Engineering, Northwestern University, USA (1999) Professor Kondi's research focuses on signal processing and communications, with particular emphasis on image/video compression , video transmission over wireless channels , video quality assessment , sparse representations , compressive sensing , super-resolution of video sequences , image watermarking , and shape coding . His work bridges theoretical foundations with practical applications in wireless communications and medical imaging. His recent publications demonstrate a strong trend toward medical image processing and super-resolution techniques, with increasing integration of machine learning approaches. The research spans from theoretical frame construction for compressed sensing to practical applications in wireless visual sensor networks and medical imaging. Teaching: Current Courses (2022-2023): Communication Systems, Multimedia, Video Processing and Compression Previous Courses: Introduction to Programming, Signals and Systems, Topics in Digital Signal Processing, Statistical Signal Processing, Topics in Networking, Topics in Digital Image Processing Professor Kondi has authored the book 4G Wireless Video Communications (Wiley, 2009) and contributed chapters on Color Image Super-Resolution and Video Telephony to major reference works. His research has been published extensively in top-tier journals including IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing, and SPIE Journal of Electronic Imaging.

Demetris P. Gerogiannisمشاهده پروفایل

پژوهشگر

• Computer Vision
• Image Processing
• Image Segmentation and Registration
• +۷ مورد دیگر

Demetris P. Gerogiannis is a researcher in the Department of Computer Science & Engineering at the University of Ioannina, Greece. His academic work focuses on Computer Vision and Image Processing, with specific expertise in image registration, pointset registration, and feature extraction. He has maintained a consistent publication record from 2007 through 2020, primarily collaborating with Christophoros Nikou and A. Likas. Gerogiannis' research interests span multiple areas within Computer Vision including Image Segmentation and Registration, Pointset Registration, Feature Extraction, Object Detection and Recognition, Pattern Recognition, Automatic Image Annotation, and Machine Learning applications. His work demonstrates a consistent focus on developing robust algorithms for geometric problems in vision, with particular attention to handling noise and outliers in visual data. He has made significant contributions to point set registration, shape representation, and vanishing point detection. His publication history reveals a strong trend toward developing mathematically rigorous approaches to Computer Vision problems, particularly utilizing statistical models like Student's t-distributions for robust registration. His work bridges theoretical computer vision with practical applications, including consumer-facing technologies like QR code systems. The 15 most recent publications show progression from foundational work in image registration to more applied research in texture analysis, word spotting, and biomedical applications. Gerogiannis is also an active entrepreneur, currently coordinating QReca!, a startup focused on consumer engagement through QR codes and NFC technology. He has previously worked on a Video On Demand startup and is developing a spin-off to commercialize his Computer Vision research through an API framework. He maintains a commitment to open academic knowledge by providing Matlab code for non-commercial use related to his publications. He has volunteered for the Athens 2004 Olympic Games and maintains a passion for Mathematics, particularly Number Theory and Euclidean Geometry. His academic profile suggests a researcher who bridges theoretical computer vision with practical applications and entrepreneurial ventures.

Angeliki Katsenouمشاهده پروفایل

پژوهشگر ارشد

• Video Compression
• Video Analysis and Synthesis Models
• Video Communications
• +۵ مورد دیگر

Angeliki Katsenou is a Marie Sklodowska-Curie Research Fellow at the Visual Information Lab, University of Bristol, UK. She holds a Ph.D. in Computer Science and Engineering from the University of Ioannina (2014), an MSc from the University of Patras (2007), and a Diploma in Electrical Engineering and Computer Technology from the same university (2004). Her research focuses on video compression, communications, and sensor networks, with expertise in resource allocation and cross-layer design for wireless networks. She has contributed to European and international projects as a freelance researcher since 2007. Her affiliations include the Visual Information Lab (University of Bristol) and the Computer Science Department at the University of Ioannina, where she maintains contact information. Research interests span interdisciplinary topics such as video analysis models, visual sensor networks, and QoS optimization in multiaccess systems. No specific scientific awards or grants are listed, though her work emphasizes collaborative projects. She has no listed advisees at this time.

• Computer Science
• Electrical Engineering
• Multimedia Systems
• +۳ مورد دیگر

Lisimachos Paul Kondis is a Professor at the Department of Computer Science and Engineering, School of Engineering, University of Ioannina (email: lkon@cse.uoi.gr). He has served as a teaching faculty member and administrative staff member in the university's computer science department. Education: Diploma in Electrical Engineering, Aristotle University of Thessaloniki, 1994 M.S. in Electrical and Computer Engineering, Northwestern University, 1996 Ph.D. in Electrical and Computer Engineering, Northwestern University, 1999 Research Interests include communication systems, multimedia processing, and video compression technologies. His teaching responsibilities in 2024/25 cover courses in: Communication Systems (MYY603) Multimedia Processing (MYE025) Video Processing and Compression (D4)

Christophoros Nikouمشاهده پروفایل

استاد

• Image Processing
• Computer Vision
• Pattern Recognition
• +۱۲ مورد دیگر

Christophoros Nikou is a Professor in the Department of Computer Science and Engineering at the University of Ioannina, Greece. He holds a Ph.D. in Image Processing and Computer Vision from Université Louis Pasteur - Strasbourg I, France (1999), a DEA in Photonics and Image Processing from the same institution (1995), and a Diploma in Electrical Engineering from Aristotle University of Thessaloniki, Greece (1994). His research interests include: Image Processing Computer Vision Pattern Recognition Biomedical Image Analysis Medical Imaging Machine Learning His recent publications (2022–2024) reflect a strong trend toward deep learning, generative models, and multimodal analysis, particularly in document image analysis, super-resolution, and biomedical applications. He has made significant contributions to visual tracking, segmentation, and image registration, with recent work extending into virtual reality, hypercomplex neural networks, and model compression. Scientific awards include: Best paper award, IAPR/IEEE International Conference on Biometrics (ICB’16), 2016 Best paper award, Bayesian and Graphical Models for Biomedical Imaging (BAMBI’16), 2016 He has supervised numerous students, many of whom have co-authored publications with him, and his research has been supported by collaborations across multiple institutions. He has also co-edited a book on biomedical image processing and contributed to several book chapters. His work spans both theoretical and applied domains, with consistent publication in top-tier IEEE and Springer venues.