جست‌وجوی استاد و پژوهشگر

Kovalchuk Myroslav Lyubomyrovychمشاهده پروفایل

دانشیار

• Neural networks
• database organization
• creation of information systems
• +۱ مورد دیگر

Myroslav Lyubomyrovych Kovalchuk serves as an Associate Professor in the Department of Computer Science at Yuriy Fedkovych Chernivtsi National University. His academic foundation includes degrees in Electronics and Microelectronics, culminating in a Candidate of Physical and Mathematical Sciences qualification. His educational background comprises: Bachelor of Electronics, Yuriy Fedkovych Chernivtsi National University (2001) Engineer-physicist in Microelectronics and Semiconductor Devices, Yuriy Fedkovych Chernivtsi National University (2002) Candidate of Physical and Mathematical Sciences, Specialty 01.04.01 (2010) Kovalchuk's research centers on neural networks, database systems, information system development, and electronics engineering. His work bridges theoretical computer science with practical engineering applications, particularly in AI-driven solutions for real-world problems. He has developed specialized systems for image analysis, financial forecasting, and tourism infrastructure, demonstrating consistent innovation in computational methodologies. Over the past five years, his publication record reveals a strategic focus on neural network optimization, distributed database systems, and intelligent information architectures. His textbooks and research articles show increasing integration of cloud computing with traditional AI techniques, reflecting industry trends toward scalable, accessible computational solutions across finance, healthcare, and tourism sectors. Kovalchuk actively contributes to the Bukovina Information Technology Cluster (since 2019) and provides scientific consulting to KM TRADE LLC on security systems. He maintains professional currency through Sigma Software University's Teachers' Smart Up program and international training initiatives in Warsaw and Suceava, emphasizing modern pedagogical approaches for technical education.

Christos Kotselidisمشاهده پروفایل

دانشیار

• Virtual Machines
• Compilers
• Hardware/Software Co-design
• +۷ مورد دیگر

Christos Kotselidis is an Associate Professor at the University of Manchester's School of Computer Science and serves as Chief Engineer at Pierer Innovation (previously mentioned as KTM Innovation). He leads the TornadoVM project, a groundbreaking Java Virtual Machine for heterogeneous hardware acceleration. His work bridges academia and industry, focusing on hardware/software co-design for virtual machines and embedded systems. His research spans chip design, micro-architecture, compilers, virtual machines, and garbage collection. Dr. Kotselidis has pioneered work in heterogeneous computing, particularly in accelerating Java applications on GPUs, FPGAs, and RISC-V architectures. His team's recent development of GPULlama3.java demonstrates the practical application of his research in bringing LLM inference to pure Java with GPU acceleration. His publications show a consistent focus on bridging hardware capabilities with managed runtime systems. The research trajectory reveals increasing sophistication in handling memory hierarchies, parallelism, and cross-architecture execution. His work has significant implications for high-performance computing, AI acceleration, and sustainable computing practices. Dr. Kotselidis actively contributes to the academic community as a program committee member for conferences like ISMM and as an organizer for workshops including VMIL and MoreVMs. He's also involved in EU-funded projects like AERO and DARE, which focus on European processor initiatives and software ecosystems. As project lead for TornadoVM, he mentors a research team at Manchester including Michalis Papadimitriou, Mary Xekalaki, and Thanos Stratikopoulos. His lab (Beehive Lab) develops open-source tools that are widely used in both academic and industrial settings for heterogeneous computing.

• Biomedical Engineering
• Entropy Analysis
• Bubble Entropy
• +۱۳ مورد دیگر

George Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He is a member of the IPAN lab and serves as a Guest Editor for a special issue on 'Entropy in Biomedical Engineering' in the journal Entropy . His research bridges biomedical engineering and computational systems, with a strong focus on entropy-based methods and machine learning for physiological signal analysis. PhD in Computer Science, National Technical University of Athens (1993–1997) MSc in Advanced Methods in Computer Science, Queen Mary, University of London (1992–1993) Diploma in Electrical and Computer Engineering, National Technical University of Athens (1987–1992) His primary research interests include Biomedical Engineering , Entropy Analysis (especially Bubble Entropy), Fast Computation Algorithms , Biomedical Data Classification , Heart Rate Analysis , and Computing Systems with emphasis on parallelization. He teaches postgraduate courses in data analysis and biomedical data processing, and undergraduate courses in compilers. The analysis of his recent publications reveals a consistent trend in developing computationally efficient and robust methods for entropy estimation and classification in biomedical contexts. His work on Bubble Entropy eliminates the need for scale parameters and enhances stability, while his improvements to Random Forests and Support Vector Machines target enhanced diagnostic accuracy in diseases like Alzheimer’s and heart conditions. In computing systems, he has pioneered compiler technologies for parallelizing recursive functions and optimizing runtime scheduling. No scientific awards are explicitly mentioned in the provided text. George Manis has advised or collaborated with several researchers, including Evanthia Tripoliti, Dimitrios Fotiadis, Petros Arsenos, Argyro Kampouraki, and others, indicating active supervision and research leadership. He is currently involved in funded projects such as Palimpsest , an interactive museum system, and Homore , a smart monitoring system for elderly individuals. These projects reflect his interest in applying advanced computing to real-world biomedical and societal challenges. He is affiliated with the IPAN lab and contributes to the development of innovative algorithms for entropy computation and parallel processing. His work on the C2μTC/SL compiler and Ariadne system demonstrates deep expertise in compiler design for specialized architectures like the SVP processor.

Fabian Schelerمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Embedded Systems
• Operating Systems
• +۴ مورد دیگر

Fabian Scheler was a researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander University Erlangen-Nuremberg from 2005 to 2013. His research focused on reliable embedded real-time systems, culminating in his PhD thesis on Atomic Basic Blocks (ABB), which introduced a novel abstraction for manipulating real-time system architectures. He contributed to projects like the Real-Time Systems Compiler (RTSC), Aspect-Oriented Real-Time Architecture (AORTA), and Sloth, an interrupt-driven real-time operating system framework. Teaching activities included courses such as Real-Time Systems (since 2005), Dependable Real-Time Systems, and Concepts of Operating Systems components. Over 15 master’s and diploma theses were supervised, covering topics like real-time scheduling, compiler optimization, and embedded system reliability. Key research areas span real-time system design, compiler-driven architecture manipulation, and fault-tolerant embedded systems. Notable contributions include the RTSC framework for migrating event-triggered to time-triggered systems and Sloth’s hardware-based scheduling mechanisms. His work bridges theoretical compiler techniques with practical embedded system implementations. Contact details remain active at the university, including an office at Martensstr. 1, Erlangen, and email scheler@cs.fau.de. Publications span conferences like RTSS, IEEE SIES, and journals like Software: Practice and Experience, emphasizing real-time system reliability and compiler integration.

Shengyi Wangمشاهده پروفایل

پژوهشگر

• Formal Verification
• Programming Languages
• Mechanized Reasoning
• +۷ مورد دیگر

Shengyi Wang is an Associate Research Scholar in the Department of Computer Science at Princeton University, School of Engineering and Applied Science. He is actively engaged in research on formal verification, programming languages, and mechanized reasoning, with a focus on verifying concurrent systems, C programs, and network packet processing. Research Interests: His work centers on foundational and compositional verification of low-level systems using interactive theorem proving. Key areas include separation logic, concurrency, data structure invariants, and certified systems programming. He applies these to real-world challenges in systems security and network correctness. Recent Research Trends: His recent publications (2020–2024) show a strong trajectory in verifying complex systems such as concurrent C programs, P4-based packet processors, and enclave filesystems. The work consistently uses Coq and mechanized proofs to ensure correctness, emphasizing scalability and compositional techniques. Scientific Awards: No awards or fellowships are mentioned in the provided text. Advising and Grants: No formal students or advisees are listed. No grants or funding sources are explicitly mentioned. Labs and Teams: While not explicitly stated, his collaborations with researchers like Andrew W. Appel, Lennart Beringer, and William Mansky suggest involvement in Princeton’s formal methods and systems verification research group, likely associated with the Department of Computer Science.

• Computer Architecture
• Cybersecurity
• Energy Efficiency
• +۲ مورد دیگر

Andrew Douglas Hilton is a Teaching Professor in the Department of Electrical and Computer Engineering at Duke University , where he also serves as the Director of Innovation in Computing Education . He focuses on teaching professional-level programming, software engineering, and architecture courses to graduate and advanced undergraduate students, with a particular emphasis on preparing them for software engineering careers. Education: Ph.D. in Computer Science from the University of Pennsylvania (2010) Hilton’s research interests center on computer architecture , particularly architectural support for security and energy-efficient performance . His recent publications explore themes like secure memory, thermal management, and speculative execution in processor design. He has co-authored a widely used course textbook, All of Programming , and developed two Coursera specializations in Java and C. His teaching spans courses such as ECE 651 (Software Engineering) and ECE 553 (Compiler Construction), with a focus on design principles, testing, and teamwork. Scientific Awards: Klein Family Distinguished Teaching Award (2015) Hilton collaborates with faculty at Duke (Genevieve Lipp, Ben Lee, Daniel Sorin) and institutions such as UT Austin and IBM Research. His former students, Tamara Lehman and Ziqiang Huang, hold academic and research positions at the University of Colorado Boulder and University of Waterloo, respectively.

Flavius Gruianمشاهده پروفایل

مدرس ارشد

• Embedded Systems
• Real-Time Systems
• Hardware-Software Co-Design
• +۵ مورد دیگر

Flavius Gruian is a Senior Lecturer and Reader Project Manager at the Department of Computer Science, Lund University (LTH). He holds affiliations with ELLIIT (Linköping-Lund initiative on IT and mobile communication) and the LTH Profile Area: AI and Digitalization. His research focuses on resource-constrained embedded systems, real-time scheduling, and energy-efficient hardware-software co-design, with applications in IoT, radar systems, and radio astronomy. Education and Academic Roles: No explicit education details provided, but his roles include senior lecturer, project manager, and principal investigator (PI) in multiple research projects. He advises PhD students (Boulasikis, Callanan, Waldemarson) and contributes to initiatives like GPAI (AI hardware for computing) and NordicIoT (Nordic IoT hub). Research Interests: His work spans embedded systems modeling, real-time algorithms, custom hardware architectures, Java in embedded systems, and machine learning for industrial applications. He explores energy-efficient designs and reliability in distributed embedded systems. Key Projects: Active projects include GPAI (2021–2026), TaLMiRRA (machine learning in radar/astronomy, 2019–2022), and NordicIoT (2018–2023). He also leads research on scalable actor networks and GPU programming for visual systems. Grants and Funding: PI roles in TaLMiRRA (STINT-funded) and NordicIoT (Nordic collaboration). Projects involve collaboration with international teams and industry partners. Labs/Teams: Affiliated with ELLIIT and the LTH AI profile area. Collaborates on hardware-software co-design and embedded systems optimization.

• Computer Architecture
• Real-Time Systems
• Embedded Systems
• +۳ مورد دیگر

Martin Schöberl is affiliated with TU Wien's Institute of Computer Engineering (E191-01), part of the Faculty of Informatics. He holds the role of Privatdozent (Senior Lecturer) and specializes in computer architecture for real-time systems, embedded systems, and worst-case execution time analysis. His research emphasizes time-predictable computing, compiler optimization, and hardware-software co-design for real-time applications. Key research areas include compiler-directed execution time control, method cache analysis, and processor design for embedded systems. He has supervised multiple theses on topics like hard real-time garbage collection, WCET-driven inlining, and real-time Java processors. His work bridges theoretical computer science with practical embedded system implementations. Publications focus on optimizing code execution predictability, with contributions to real-time systems conferences like ISORC and WCET. His PhD thesis introduced the JOP processor, a stack-based architecture tailored for real-time Java applications. Collaborations include projects on Patmos processors and time-aware compiler techniques. Active in academic advising, he has guided students through advanced topics such as constant-loop optimization, scope-based caching, and multi-processor garbage collection. His email is martin.schoeberl@tuwien.ac.at , and his profile is accessible via TU Wien's faculty directory .

Foivos Zakkakمشاهده پروفایل

پژوهشگر

• Process Virtual Machines
• Managed Runtime Systems
• Garbage Collection Systems
• +۳ مورد دیگر

Foivos Zakkak is a Software Engineer at Red Hat’s Java platform team, focusing on Mandrel, GraalVM, and Quarkus. Previously, he held academic roles including Research Associate and Research Software Engineer at the Advanced Processor Technologies (APT) group at the University of Manchester, and Postdoctoral Researcher at the Computer Architecture and VLSI Systems Laboratory (CARV) of FORTH-ICS. He holds a PhD, MSc, and BSc in Computer Science from the University of Crete. His research interests center around Process Virtual Machines, Managed Runtime Systems, Garbage Collection, and Systems Software. Key projects include leading the Maxine VM (a metacircular Java-in-Java VM), developing DiSquawk (a JVM for non-cache-coherent architectures), and contributions to task-based runtime systems like TPC, BDDT, and PARTEE. His work spans optimizing managed applications for NUMA architectures and reducing memory pressure in big data frameworks. Publications include studies on NUMA system performance, memory analysis of Java benchmarks, and JIT compilation on ARM architectures. His technical expertise extends to system software development and performance engineering.

Gabriel Stoianمشاهده پروفایل

مدرس

• Computer Networks
• Digital Communications
• Operating Systems
• +۷ مورد دیگر

Gabriel Stoian is a Lecturer in the Computer Science Department at the Faculty of Mathematics and Computer Science, University of Craiova, Romania. He has been serving in this role since 2008, having previously held the position of Assistant Professor from 1992 to 2008. His academic and research activities are deeply rooted in computer systems and networking. His educational background includes a PhD from the University of Craiova (2007) with a thesis titled Model for quantitative and qualitative analysis of ADSL communication , and a degree in Computer Science from the Faculty of Automatics, Computers and Electronics at the University of Craiova (1984–1989), where his graduation paper was on a logic analyzer. Gabriel Stoian's research interests include Computer Networks, Digital Communications, Operating Systems, and Computer Architecture. His work emphasizes mobile and broadband communication systems, particularly in WiMAX and ADSL technologies, and explores innovative solutions using mobile agents and optimization algorithms. The recent publications reflect a consistent focus on network performance, traffic management, and communication system design. Key themes include handoff optimization in mobile networks, DSLAM and line card architecture, and intelligent systems for network control. His research bridges theoretical models with practical implementations in telecommunications and embedded systems. IEEE Member (Computer Society, Communication Society), since 2002 Association for Computing Machinery, since 2004 Romanian Mathematical Society (SSMR), since 2000 Research Center of Artificial Intelligence, Craiova, since 2000 Gabriel Stoian has participated in national research grants such as Algebraic Properties of the Labelled Stratified Graphs and Knowledge Representation System Based on Frames . While no formal advising roles are listed, his collaborative publications suggest mentorship and team-based research. He has taught courses including Operating Systems, Computer Networks, and Java Technologies. He is associated with the Research Center of Artificial Intelligence in Craiova and has contributed to projects involving frame-based knowledge systems and fault diagnosis in digital circuits. His ongoing work reflects a strong integration of academic teaching, applied research, and professional engagement in international computing societies.

Andrew Myersمشاهده پروفایل

استاد

• Programming Languages
• Computer Security
• Distributed Systems
• +۳ مورد دیگر

Andrew Myers is a Professor in the Department of Computer Science at Cornell University, specializing in programming languages, computer security, and distributed systems. He serves as the Editor-in-Chief for ACM Transactions on Programming Languages and Systems (TOPLAS) and has chaired major conferences including ACM POPL 2018, ACM CCS 2016, POST 2014, IEEE CSF 2010, and IEEE S&P 2009. Myers' research focuses on the intersection of programming languages and security, particularly in developing language-based approaches to ensure security properties in distributed systems. His pioneering work in information flow control has established foundational techniques for tracking and controlling how sensitive information propagates through programs. He has made significant contributions to secure compilation, type systems that enforce security policies, and programming models for geographically distributed applications where consistency and security are critical concerns. Analysis of Myers' publication record reveals a consistent research trajectory centered on using programming language techniques to address security challenges. His early work established fundamental approaches to information flow security, which evolved into practical systems like Jif (Java information flow) and more recently Viaduct for secure distributed programming. Recent publications show increasing focus on secure distributed programming, information flow control in complex systems, and type systems that enable secure concurrency without sacrificing performance. ACM Fellow POPL'99 Best Paper Award SOSP'01 Best Paper Award SOSP'07 Best Paper Award CIDR'13 Best Paper Award PLDI'13 Best Paper Award PLDI'15 Best Paper Award Through the Programming Languages Mentoring Workshop (PLMW) at major conferences including POPL and PLDI, Myers has been actively involved in mentoring the next generation of programming languages researchers. His service as Editor-in-Chief of TOPLAS demonstrates his leadership in the field, overseeing the publication of cutting-edge research in programming languages and systems. While specific grant information isn't detailed in the provided text, his sustained research output and leadership roles suggest significant external funding support over his career. Though specific lab affiliations aren't mentioned in the provided text, Myers' research has clearly involved collaboration with numerous students and colleagues across multiple institutions. His work on systems like Viaduct and Jif suggests the leadership of research teams focused on building practical implementations of language-based security techniques. His active participation in conference organization and program committees indicates strong connections with the broader programming languages and security research communities.

Vijay Narayananمشاهده پروفایل

استاد

• Embedded Systems
• Computer Architecture
• Power-Aware Computing
• +۴ مورد دیگر

Vijay Narayanan serves as the Robert Noll Chair Professor in the Department of Computer Science & Engineering and Electrical Engineering at Pennsylvania State University, co-directing the Microsystems Design Lab and leading multiple interdisciplinary research initiatives. His academic credentials include: B.E. in Computer Science and Engineering from University of Madras (1989-1993), achieving University First Rank Ph.D. in Computer Science and Engineering from University of South Florida (1993-1998) with dissertation on "Issues in Design of a Java Processor" Research spans embedded visual analytics systems for UAVs and visually impaired assistance, non-volatile processors for unreliable power environments, and system design using emerging devices. His work integrates power-aware computing, computer architecture, and design automation to develop self-powered systems and intelligent vision technologies. Major recognitions include: IEEE Fellow ACM Fellow He directs the Visual Cortex on Silicon center for embedded vision systems, contributes to NSF ERC ASSIST on self-powered processors, and leads the Architecture, Benchmarking and Circuits Thrust in the DARPA/SRC LEAST Center for emerging device integration.

Christophe Dubachمشاهده پروفایل

دانشیار

• Data-Parallel Language Design
• Hardware Design Space Exploration
• Heterogeneous Computing
• +۴ مورد دیگر

Christophe Dubach is an Associate Professor at McGill University, jointly appointed in the Department of Electrical and Computer Engineering (ECE) and the School of Computer Science (CS). He holds a Canada CIFAR AI Chair at Mila. Previously, he was a Reader (Associate Professor) at the University of Edinburgh until 2019. His research focuses on data-parallel language design, high-level code generation for parallel hardware (GPUs/FPGAs), hardware design space exploration, and applying machine learning to these areas. He has advised numerous PhD and MSc students on topics like FPGA-based high-level synthesis, neural networks, and compiler optimization. Education: PhD in Informatics (2009, University of Edinburgh), MSc in Computer Science (2005, EPFL, Switzerland). Teaching includes courses on compiler design, computer organization, and high-level synthesis. His projects include Lift (a functional IR for GPU code generation) and High-Level Synthesis of Neural Networks on FPGAs. Collaborators include Michel Steuwer, Lu Li, and others in the fields of compilers, machine learning, and parallel computing.

Christos-Efthymios Kotselidisمشاهده پروفایل

دانشیار

• Computer Architecture
• Parallel and Distributed Computing
• High-Performance Computing
• +۴ مورد دیگر

Christos-Efthymios Kotselidis is an Associate Professor in the Department of Computer Science at the University of Manchester. His work focuses on runtime systems, heterogeneous computing, and high-performance computing. He leads research in optimizing Java programs using frameworks like TornadoVM and explores GPU acceleration for cryptography (FHE). His contributions include advancements in vectorization for RISC-V architectures and memory analysis of Java benchmarks. Education: PhD in Computer Science (2011) from the University of Manchester, supervised by Prof. Steve Furber and Dr. Chris Kirkham, with a thesis on Distributed Software Transactional Memory. Research Interests: Runtime environments, parallel programming models, compiler optimization, and hardware-software co-design. His work aligns with UN SDG 9 (Industry, Innovation, and Infrastructure) through digital futures research. Notable Achievements: Recipient of the Best Paper Award (2017) Principal Investigator in the Centre for Digital Trust and Society (2021–present) Over 49 peer-reviewed publications, including books and conference contributions on topics like FHE acceleration and runtime systems Lab/Team Affiliations: Member of the Advanced Processor Technology group and collaborates on the Digital Futures research beacon at the University of Manchester.

Adrian Johnstoneمشاهده پروفایل

استاد

• Programming Language Theory
• Compiler Design
• Generalised Parsing
• +۳ مورد دیگر

Adrian Johnstone is a Professor of Computing in the Department of Computer Science at Royal Holloway, University of London. He is affiliated with the Centre for Software Language Engineering and the Centre for Programming Languages and Systems. His research focuses on programming language theory and implementation, with notable contributions to generalized parsing algorithms like GLL and ambiguity retained translation (ART). He has collaborated on projects such as PLanCompS (EPSRC-funded) and leads research on Babbage's language of thought (Leverhulme Trust). Key research interests include context-free grammars, customisable processors, and the history of computing. He has authored over 50 publications, with recent work presented at the ACM SIGPLAN International Conference on Software Language Engineering (SLE). His software contributions include the ART toolkit and reference GLL implementations available on GitHub. Adrian has supervised three major research projects and contributed to datasets like the reference GLL implementation codebase. His work bridges theoretical foundations with practical parser development, emphasizing performance testing and principled algorithm design.