جست‌وجوی استاد و پژوهشگر

Anton Dahburaمشاهده پروفایل

دانشیار

• Information Security
• Fault-tolerant Computing
• Distributed Systems
• +۶ مورد دیگر

Anton Dahbura is an Associate Professor at the Johns Hopkins University , affiliated with the Whiting School of Engineering and the Department of Computer Science . He serves as Executive Director of the Johns Hopkins University Information Security Institute , Co-director of the Institute of Assured Autonomy , and leads the Sports Analytics Research Group . He is also affiliated with the Malone Center for Engineering in Healthcare and the Laboratory for Computational Sensing and Robotics . Research Interests Information Security Fault-tolerant Computing Distributed Systems Protocol Conformance Testing Sports Analytics Scheduling Optimization Publications span IoT/CPS integration, protocol testing, fault-tolerant mobile networks, and ASIC array optimization. His work emphasizes algorithm development for system reliability and security, with historical contributions to multiprocessor fault diagnosis and protocol verification. Scientific Awards IEEE Fellow IEEE Browder J. Thompson Memorial Prize Paper Award Johns Hopkins Heritage Award (2004) He has held leadership roles at AT&T Bell Laboratories, Motorola Cambridge Research Center, and Princeton University. His academic career reflects deep engagement with systems engineering, security, and interdisciplinary sports analytics.

• Real-Time Systems
• Worst-Case Execution Time (WCET) Analysis
• Single-Path Code Optimization
• +۳ مورد دیگر

Peter Puschner is an Associate Professor at Vienna University of Technology (TU Wien), affiliated with the Cyber-Physical Systems Research Area. His work focuses on real-time systems, worst-case execution time (WCET) analysis, and time-predictable code execution. Key research areas: Real-Time Systems, Single-Path Code, Time-Triggered Networks, Cache Architectures Advisor to multiple thesis students including Michael Platzer and Bekim Cilku Co-developer of tools like the platin Toolkit for WCET analysis Recipient of Best Paper Award at ECRTS 2015 for Requirement Semi-formalization Methodology for SoC Design

• Power Electronics
• Industrial Automation
• Embedded Systems
• +۵ مورد دیگر

Mladen Knežić is an Associate Professor at the Faculty of Electrical Engineering, University of Banja Luka. He actively contributes to research in Power Electronics , Industrial Networking , and Embedded Systems with a focus on renewable energy and real-time communication protocols. Current Role: Associate Professor (since 2023) Key Collaborations: Partnerships with IEEE, international conferences, and institutions in Serbia and Germany His research emphasizes boost converter optimization , EtherCAT/Ethernet Powerlink protocols , and TSN (Time-Sensitive Networking) . Recent projects include "Sistem automatske regulacije i kontrole navodnjavanja" (2023-2024) and "Implementacija FTT paradigme u TSN standarda" (2019-2020). Key publication trends include energy efficiency in power electronics, deterministic networking solutions, and FPGA-based system designs. He has contributed to over 15 peer-reviewed articles and conference papers between 2006-2022. He collaborates with researchers such as Željko Ivanović and Branko Dokić , and has participated in projects funded by the Ministry of Science and Technology of Republika Srpska and the Ministry of Agriculture, Forestry, and Water Management (total funding exceeding 50,000 BAM). As co-author of the textbook Mikrokontroleri: arhitektura i projektovanje (2022), he contributes to academic education in microcontroller systems. His ORCID is 0000-0003-3240-9110 .

Viktor Vafeiadisمشاهده پروفایل

پژوهشگر

• Weak Memory Models
• Concurrency
• Program Verification
• +۴ مورد دیگر

Viktor Vafeiadis is a tenured researcher at the Max Planck Institute for Software Systems (MPI-SWS) in Germany. He received his BA and PhD from the University of Cambridge (2004, 2008) and worked as a postdoctoral researcher at Microsoft Research Cambridge and the University of Cambridge before joining MPI-SWS in 2010. His research focuses on concurrency , verification of concurrent programs, weak memory consistency , weak persistency , and formal semantics of programming languages. Research Areas: Weak Memory Models, Program Verification, Persistent Programming, Automated Model Checking Key Tools: Cave (automated verification tool), GenMC (model checker), Kater (consistency checker) His recent work explores linearizability under relaxed memory , mixed-size memory accesses , and formalizing ARMv8 persistency . Awards include the ACM SIGPLAN John C. Reynolds Award (2008), ERC Consolidator Grant (2020), and Robin Milner Young Researcher Award (2022). Selected Awards: ACM SIGPLAN John C. Reynolds Doctoral Dissertation Award (2008) ERC Consolidator Grant (2020) ACM SIGPLAN Robin Milner Young Researcher Award (2022) Distinguished Paper Awards: PLDI'17, OOPSLA'21, ECOOP'17 He has mentored numerous PhD students including Ellen Arlt , Pavel Golovin , and Aristotelis Koutsouridis , while alumni advisees include Soham Chakraborty and Michalis Kokologiannakis . His collaborative work spans institutions like University of Cambridge , Microsoft Research , and ETH Zürich .

Christopher Joseph Carmona del Jesusمشاهده پروفایل

استاد

• Data Science
• Big Data
• Subgroup Discovery
• +۳ مورد دیگر

Christopher Joseph Carmona del Jesus serves as a University Professor in the Department of Computer Science at the University of Jaén, Spain, affiliated with the Andalusian Interuniversity Institute for Data Science and Computational Intelligence and leading the Intelligent Systems and Data Mining research group. His work bridges theoretical computational intelligence with practical applications across diverse domains. His academic credentials include: PhD in Computer Science, University of Jaén (2011) Master's in Computer Science, University of Jaén (2007) Dr. Carmona specializes in Data Science, Big Data, and Subgroup Discovery using evolutionary fuzzy systems for descriptive rule extraction. His research particularly emphasizes Supervised Descriptive Rule Discovery and Emerging Patterns in dynamic data streaming environments, developing algorithms that balance interpretability with predictive power for real-world datasets. Recent work extends these methods to healthcare diagnostics and renewable energy forecasting. Analysis of his 15 most recent publications (2022-2025) reveals a strong focus on data streaming algorithms (60% of works), explainable AI systems (30%), and cross-domain applications in healthcare (20%) and cybersecurity (15%). Key technical contributions include evolutionary fuzzy frameworks for multiclustering, federated descriptive rule extraction, and spiking neural networks for energy-efficient computing. No scientific awards are documented in the provided materials. While his research leadership is evident through the Intelligent Systems and Data Mining group, specific details regarding student supervision or grant funding are not included in the available information. His methodological innovations in subgroup discovery and data streaming continue to drive practical implementations through tools like SDRDPy and the Clustering R library. He actively contributes to the Andalusian Interuniversity Institute for Data Science and Computational Intelligence, fostering collaborations that integrate computational intelligence with domain-specific challenges in energy, healthcare, and education.

Charlotte Frenkelمشاهده پروفایل

استادیار

• Neuromorphic Engineering
• AI Processor Design
• Digital and Mixed-Signal IC Design
• +۵ مورد دیگر

Charlotte Frenkel is a Tenure-Track Assistant Professor in the Microelectronics Department at Delft University of Technology (TU Delft), where she leads research in neuromorphic engineering and low-power AI hardware. Her work bridges the gap between biological intelligence and artificial neural networks, focusing on energy-efficient computing at the edge. Dr. Frenkel's research spans digital and mixed-signal IC design, computer architecture, learning algorithms, and neuroscience. She directs the Cognitive Sensor Nodes and Systems (CogSys) lab, which develops neuromorphic processors like ODIN, MorphIC, SPOON, and ReckOn that demonstrate competitive advantages over conventional neural network accelerators. Her publications reveal a strong focus on spiking neural networks, event-based processing, and on-chip learning. Key trends include developing hardware that leverages sparsity for energy efficiency, creating bio-inspired learning algorithms that solve weight transport and update locking problems, and establishing frameworks for benchmarking neuromorphic systems through initiatives like NeuroBench. Scientific Awards: IBM Innovation Award 2021 Nokia Bell Labs Scientific Award 2021 IEEE ISCAS 2020 Best Paper Award NEUROTECH/NICE Best Early Researcher Presentation 2021 AiNed Fellowship Grant Dr. Frenkel is actively expanding her research group through PhD and postdoc positions. She serves as Associate Editor for IEEE Transactions on Biomedical Circuits and Systems and Frontiers in Neuroscience, and has held numerous leadership roles in conference organization including Program Chair for tinyML Research Symposium 2024 and Neuro-Inspired Computational Elements conference 2023-2024. Her service includes extensive reviewing activities for top IEEE journals and conferences in her field.

Tom Igoeمشاهده پروفایل

استاد

• Interactive Design
• Physical Computing
• Creative Technology
• +۲ مورد دیگر

Tom Igoe serves as an Arts Professor at the Interactive Telecommunications Program (ITP) within New York University's Tisch School of the Arts, where he pioneers experimental approaches to time-based interactive systems. His research explores the intersection of physical computing and creative technology through unconventional clock designs, focusing on hardware fabrication, microcontroller programming, and tangible interfaces that challenge traditional timekeeping. Notable projects include the Email Clock (2002, 2005), which advances based on incoming email volume, and an extensive educational repository providing software examples, hardware schematics, and fabrication techniques for kinetic art installations. No scientific awards were documented in the source material. Igoe actively mentors students in the ITP program through collaborative development of interactive projects, though specific advisees and grant funding details were not disclosed. His work emphasizes pedagogical resource creation for the broader interactive design community. He maintains a specialized clock repository developed with students, featuring microcontroller-driven hardware examples and fabrication guides that serve as foundational resources for scholars exploring time as a creative medium.

Christian Derksenمشاهده پروفایل

پژوهشگر

• Smart Energy Systems
• Multi-Agent Systems
• Sustainable Energy
• +۴ مورد دیگر

Christian Derksen is a scientific assistant at the Faculty of Computer Science , University of Duisburg-Essen. He is affiliated with the ICB/Informatik department and actively involved in the SOFTEC team and IoT Lab cooperation. His research focuses on smart energy systems , multi-agent based simulation , and hybrid energy infrastructures , integrating engineering, economics, and computer science. Research Trends: Derksen's work emphasizes agent-based modeling for energy systems, smart grid development, and hybrid network simulation. His recent articles explore topics like energy conservation law applications, cross-domain resource allocation , and standardized control frameworks for decentralized energy networks. Advising: Supervised two theses in 2024: one on machine learning for energy models and another on cross-platform user interfaces for decentralized energy management systems. His methodological contributions include the Energy Option Model (EOM) and Agent.GUI simulation framework for hybrid energy systems and networks.

Jeff Shaferمشاهده پروفایل

دانشیار

• Network Systems Architecture
• Data-Intensive Computing
• Cloud-Computing
• +۱ مورد دیگر

Jeff Shafer serves as an Associate Professor at the University of the Pacific, specializing in network systems architecture and cloud computing infrastructure. His research directly addresses performance challenges in data-intensive environments through innovative virtualization and distributed systems approaches. His academic credentials include: PhD in Electrical and Computer Engineering from Rice University (2010) MS in Electrical Engineering from University of Dayton (2004) BS in Computer Engineering from University of Dayton (2002) Shafer's research program focuses on optimizing network architectures for cloud environments, with particular emphasis on virtualization efficiency and distributed file system performance. His work bridges theoretical computer architecture with practical implementation constraints in modern data centers. Analysis of his publications from 2007-2010 reveals consistent exploration of hardware-software co-design for network virtualization. Key themes include I/O bottleneck mitigation in virtualized systems, reconfigurable network interface development, and performance-portability tradeoffs in distributed storage solutions across cloud platforms. His teaching portfolio encompasses core computer engineering disciplines including Computer Architecture, Networking, Digital Systems, and Embedded Systems, reflecting the integration of his research expertise into curriculum development.

• MPSoC Architecture
• Memory Hierarchies
• Hardware Prefetching
• +۳ مورد دیگر

Oliver Lenke is a Scientific Assistant at the Chair of Integrated Systems , Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology . He completed his Bachelor’s (2015-2018) and Master’s (2018-2020) in Electrical Engineering at TUM and has been a PhD student since 2020 . His research focuses on MPSoC architectures , memory hierarchies , hardware preloading mechanisms , and FPGA-based system prototyping . His recent publications address topics like near-memory computing , cache prefetching , and runtime adaptive MPSoCs . He supervises students in projects involving VHDL coding , C programming , and MPSoC optimization , collaborating with industry partners such as Infineon AG , BMW AG , and Huawei . His work includes developing non-intrusive performance monitoring frameworks and dynamic memory preloading solutions .

Marco Liessمشاهده پروفایل

پژوهشگر

• SmartNIC Development
• 6G Networking
• FPGA-based Networking
• +۴ مورد دیگر

Marco Liess serves as a Scientific Staff Member and doctoral candidate at the Chair of Integrated Systems within the TUM School of Computation, Information and Technology. His work focuses on hardware aspects of network interfaces and processing resources, with particular emphasis on SmartNIC development for next-generation networking systems. The chair participates in multiple research initiatives including the 6G Future Lab Bavaria and 6G Life projects. Dr. Liess holds a Master of Science in Electrical Engineering and Information Technology from TUM (2019-2021), with specialization in Embedded and Control Systems. His master's thesis on 'Frame Synchronization for Satellite-based IoT Applications' was completed at the German Aerospace Center (DLR). Previously, he earned a Bachelor of Science in the same field (2016-2019), focusing on Communication Networks, Embedded Systems, and Security, with his bachelor's thesis on 'Efficient Key Establishment for IoT Applications' conducted at Fraunhofer AISEC. His research primarily investigates hardware acceleration of data paths between network interfaces and processors, memory bottleneck avoidance, dynamic power management, and efficient hash algorithms. These interests align with current 6G research directions focusing on deterministic real-time processing for mission-critical applications. His work bridges hardware design (particularly FPGA implementations), operating system interactions, and networking protocols to create energy-efficient, high-performance network processing solutions. Analysis of his publication record reveals strong focus on SmartNIC architectures, with consistent contributions to major conferences in networking and computer architecture. His work demonstrates progression from satellite IoT communications toward advanced packet processing pipelines and real-time networking solutions for 6G infrastructure. Key themes include hardware-software co-design, power efficiency, and deterministic performance guarantees for time-sensitive networking applications. As an academic supervisor, Dr. Liess actively mentors students through various thesis projects ranging from FPGA-based network testers to Linux scheduler optimizations. His teaching responsibilities include 'Chip Multicore Processors' since SS 2024 and previously supervised 'Seminar Integrierte Systeme' and 'Seminar on Topics in Integrated Systems' from WS 2022/23 to WS 2023/24. Current projects under his supervision address critical challenges in 100Gbps networking, hardware tracing mechanisms, and server state tracking using SmartNIC technology.

• Distributed computing
• Systems software
• Information systems
• +۶ مورد دیگر

Jade Alglave is a Professor of Computer Science at University College London, working within the Department of Computer Science. She is affiliated with the PPLV research group led by Peter O'Hearn, focusing on foundational aspects of programming languages and verification. Her work bridges the gap between theoretical computer science and practical systems implementation, particularly in the domain of memory models and concurrency. Alglave's research spans distributed computing, systems software, information systems, theory of computation, and software engineering, with a particular emphasis on weak memory models and concurrent systems . Her work develops formal methods for specifying, verifying, and testing memory models across various hardware architectures including ARM, POWER, and x86. She has made significant contributions to understanding the formal semantics of concurrent programming and has developed tools like the diy7 suite for generating and analyzing litmus tests that expose subtle concurrency behaviors. Her publications reveal a consistent research trajectory focused on creating rigorous formal frameworks for understanding weak memory behaviors, with applications to hardware verification, compiler design, and operating system development. The work has significant implications for ensuring correctness in concurrent and parallel systems where memory consistency is critical. Alglave actively contributes to the research community through professional activities including serving as a conference referee for major venues, participating in the ERC member DAC, reviewing for journals like TOPLAS, serving on program committees for JFLA and PLDI, and organizing workshops like CAV.

Daniel L. Silverمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Knowledge Discovery
• +۷ مورد دیگر

Daniel L. Silver is a Professor in the Jodrey School of Computer Science at Acadia University and former Director of the Acadia Institute for Data Analytics. He is also Professor of Business Informatics in the Faculty of Management at Dalhousie University. His research centers on machine learning, data mining, user modeling, robotics, and intelligent systems, with applications in medicine and business analytics. Education: Ph.D. in Computer Science, University of Western Ontario (in progress) M.Sc. in Computer Science, University of Western Ontario B.Sc. (Honours), Acadia University Research Interests: Dr. Silver’s primary focus is Machine Learning and Transfer Learning, particularly how knowledge can be consolidated and transferred between tasks in neural networks. He has contributed to user modeling, adaptive interfaces, handheld technology, robotics, and web-centric applications. His work bridges theoretical advances in AI with practical impacts in medical diagnostics and business intelligence. Leadership & Service: He served as President of the Canadian Artificial Intelligence Association (2009–2011), sits on the ChaLearn Board of Directors, and founded the Acadia Robot Programming Competitions. Since 2006 he has been the FIRST LEGO League Partner for Nova Scotia and was named an Honorary Colonel in the RCAF in 2014. Awards & Honors: Science Champion Award (2011) – Nova Scotia Discovery Centre Honorary Colonel, RCAF 14 Wing Software Engineering Squadron (2014) Labs & Initiatives: He directs the Intelligent Information Technology Research Laboratory (IITRL) and leads the ML3 (Machine Life-Long Learning) initiative at Acadia, fostering interdisciplinary collaboration in data analytics and AI.

Daniel Cocaمشاهده پروفایل

استاد

• Nonlinear and Complex Dynamical Systems
• Complex Systems Modelling, Identification and Control
• Bioimaging and Biological Data Analysis
• +۲ مورد دیگر

Professor Daniel Coca is an Honorary Professor of Nonlinear and Complex Systems in the School of Electrical and Electronic Engineering at the University of Sheffield, specializing in mathematical and computational methods for complex dynamical systems across physics, engineering, life sciences, and finance. Education: MEng PhD Research Interests: His work focuses on nonlinear and complex dynamical systems with applications in stem cell population dynamics, crystal growth, brain activity, solar wind-magnetosphere interaction, and financial markets. He develops advanced techniques in bioimaging (diffuse optical tomography, protein identification) and reconfigurable computing (FPGA hardware acceleration for proteomics and control algorithms), while advancing nonlinear control theory for PDEs and predictive systems. Publications: Recent work (2016-2020) demonstrates expertise in inverse problems for dynamical systems (Frobenius-Perron operator solutions), spiking neural network modeling (liquid state machines, sensory circuit identification), and interdisciplinary applications including urban air quality monitoring, stem cell characterization, and fly vision neuroscience. His publications span high-impact journals in computational neuroscience, environmental engineering, and nonlinear dynamics. Grants: Professor Coca has secured substantial funding from EPSRC, BBSRC, and MRC, including £2.1M for the Urban Flows Observatories, £530k for Digital Fly Brain, and multiple FPGA proteomics projects. His £4M+ apportioned grant portfolio covers digital built Britain, stem cell dynamics, and neuroimaging systems.

Yushen Zhangمشاهده پروفایل

پژوهشگر

• Microfluidics
• Electronic Design Automation
• 3D Printing
• +۵ مورد دیگر

Yushen Zhang is a PostDoctoral researcher at the Technical University of Munich (TUM), working within the Chair of Electronic Design Automation under Professor Ulf Schlichtmann. He earned his Dr.-Ing. degree with summa cum laude distinction in Electrical and Computer Engineering from TUM between 2020-2025, following his Master of Science in Computer Science from the same institution (2017-2020). His research focuses on Microfluidics, Electronic Design Automation, and 3D Printing technologies. Dr. Zhang has developed several innovative platforms including Cloud Columba, an online Microfluidic Large-Scale Integration Chip design automation tool, and has made significant contributions to open-source hardware for microfluidic applications. His work bridges the gap between electronic design automation and microfluidic systems, creating accessible and portable solutions for biochip development. Dr. Zhang's publications demonstrate a clear trend toward making microfluidic technology more accessible through 3D printing, open-source design platforms, and automation tools. His research spans from fundamental microfluidic design principles to practical implementation of low-cost, portable systems with applications in medical diagnostics and biological research. Recent work shows increasing sophistication in multi-layer microfluidic design, reliability testing, and integration with electronic control systems. Special prize COSIMA 2024 3rd prize iCANX Davos Summit 2024 3rd place COSIMA 2023 1st prize iCAN'23 3rd place COSIMA 2022 3rd place TUM Student Video Award 2020 1st place IBM Cloud Award 2019 Hackathon finalist StudySmarter Hackathon at Google Munich 2018 Dr. Zhang actively mentors students, having supervised over 19 theses across Bachelor, Master, and research internship levels. His Cloud Columba project has received significant recognition, including multiple awards in student competitions. He has also secured visiting researcher positions at Santa Clara University, demonstrating international collaboration in his field. Dr. Zhang currently serves as course instructor for the master's course VHDL System Design Laboratory at TUM. His laboratory work focuses on developing integrated microfluidic systems with an emphasis on accessibility and portability. The research group has created several open-source hardware platforms including ColoriSens, a portable color sensor board, and PAMICON, an all-in-one automated microfluidic system. Current work centers on multi-layer 3D-printed microfluidics with precise timing and volumetric control, representing the cutting edge of the field.