جست‌وجوی استاد و پژوهشگر

Panagiota Tselentiمشاهده پروفایل

مدرس

• Artificial Intelligence
• Data Mining
• Information Retrieval
• +۵ مورد دیگر

Panagiota Tselenti is a Lecturer in the Department of Informatics and Computer Engineering at the University of West Attica. She holds a PhD in Computer Science from Kingston University (UK, 2017), specializing in artificial intelligence algorithms, social network analysis, and recommender systems. Her teaching spans undergraduate and postgraduate programs since 1995, covering Robotics, Artificial Intelligence, Information Retrieval, and Natural Language Processing. She actively contributes to the Lab Teaching Staff, integrating academic rigor with practical applications. Her research focuses on artificial intelligence, data mining, and robotics, with notable work on trust-based recommendation systems and fuzzy logic methodologies. Education: PhD in Computer Science (Kingston University, UK, 2017) MSc in Data Communication Automation Engineering (BSc) Research interests include Recommender Systems, Social Network Analysis, Knowledge Management, and Robotics. Her work bridges machine learning techniques with real-world applications in education and energy systems. Recent publications explore trust models, deep learning for electric load forecasting, and policy development in maritime education using fuzzy cognitive maps. Her teaching spans over two decades, emphasizing both theoretical foundations and hands-on experience in informatics disciplines. Professional contributions are documented in her CV and personal website.

Issam Chekaktaمشاهده پروفایل

پژوهشگر

• Control Systems
• Nonlinear Systems
• Fuzzy Logic
• +۳ مورد دیگر

Dr. Issam Chekakta is a Researcher at the School of Electrical and Electronic Engineering, University of Sheffield. His work focuses on advanced control systems and nonlinear dynamics, with a specialization in Takagi-Sugeno fuzzy models, H∞ filtering, and robust state estimation for switched systems. His research addresses challenges in fault-tolerant control, distributed model predictive control, and attitude tracking for unmanned aerial vehicles (UAVs). Key technical contributions include the design of asynchronous switched observers and filters for nonlinear systems under uncertainties and disturbances. His methodologies integrate Laguerre functions for large-scale system control and address input saturation in quadrotor dynamics. Recent work emphasizes practical implementation in industrial processes like quadruple tank systems. Dr. Chekakta's research has been published in top-tier journals and conferences, reflecting his expertise in control theory and robotics applications. No awards or grants are explicitly mentioned in the provided texts.

Maximilien Gadouleauمشاهده پروفایل

دانشیار

• Coding theory
• Network coding
• Information theory
• +۱۳ مورد دیگر

Dr. Maximilien Gadouleau is an Associate Professor in the Department of Computer Science at Durham University, where he has been working since January 2012. He is a member of the Algorithms and Complexity research group, with secondary affiliations in Networks Engineering Science and Theory and Scientific Computing. Dr. Gadouleau received his MSc and PhD in Computer Engineering from Lehigh University in December 2005 and May 2009, respectively. After graduation, he held postdoctoral research positions at Université de Reims Champagne-Ardenne (until May 2010) and Queen Mary, University of London (until December 2011). Dr. Gadouleau's research spans multiple areas of theoretical computer science and discrete mathematics. His work focuses on the intersection of coding theory, network coding, and information theory with various branches of mathematics including combinatorics, graph theory, discrete optimization, matroid theory, logic, and group theory. He also investigates applications to network design, data storage, cryptography, data compression, and computation models. His recent work has particularly emphasized Boolean networks, finite dynamical systems, and semigroup theory. Dr. Gadouleau's extensive publication record demonstrates consistent contributions to theoretical computer science, with recent work showing a growing emphasis on the connections between discrete mathematics, dynamical systems, and coding theory. His research often bridges theoretical foundations with practical applications in network communication and data processing. Carnegie Trust for the Universities of Scotland: Research Assessor (2018) EPSRC Peer Review College member (2017) Dr. Gadouleau has successfully supervised PhD students including Izzy Friedlander (graduated July 2024) and Karl Southern (graduated July 2023). He was awarded an EPSRC first grant titled "Memoryless computation and network coding" which started on October 1, 2013. This grant supported research on computational models without memory and their applications to network coding problems. Dr. Gadouleau is an active member of the academic community, serving on editorial boards for journals including "Design, Codes, and Cryptography," "AIMS Mathematics," and "Mathematics and Systems Science." He regularly participates in international conferences and workshops, particularly in the areas of cellular automata, Boolean networks, and coding theory.

• Natural Language Processing (NLP)
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Emanuele La Malfa is a Researcher at the University of Oxford's Department of Computer Science, affiliated with Trinity College. His research focuses on robustness guarantees in Natural Language Processing (NLP) and model explainability, addressing critical challenges in AI fairness, adversarial robustness, and theoretical foundations. He is involved in the FUN2MODEL project and has contributed to understanding linguistic structure fragility in neural networks. Key research themes include evaluating LLM robustness against adversarial attacks, exploring ethical implications of model exploitation (e.g., jailbreaking), and analyzing dialect fairness in reasoning tasks. His work bridges theoretical computer science with practical applications in AI safety and model interpretability. Publications span topics like multi-agent system limitations in LLMs, fixed-point explainability frameworks, and formalizing continuity properties of language models. His research emphasizes scalable communication protocols for distributed AI systems and the logical capabilities of large models through representation learning. La Malfa's contributions highlight interdisciplinary efforts, combining mathematical rigor with real-world NLP challenges, positioning him at the forefront of modern AI reliability research.

• Robotics
• Artificial Intelligence
• Task and Motion Planning
• +۴ مورد دیگر

Rahul Shome is a tenure-track lecturer in the School of Computing at the Australian National University (ANU), specializing in Robotics & AI. His research focuses on planning algorithms for human-centric robotics applications, with expertise in task and motion planning, multi-robot systems, and collaborative automation. He holds a Ph.D. and M.S. from Rutgers University, advised by Prof. Kostas E. Bekris, and completed postdoctoral work at Rice University under Prof. Lydia E. Kavraki. Education: Ph.D. and M.S. in Robotics, Rutgers University (advisor: Prof. Kostas E. Bekris) Postdoctoral Research Associate, Rice University (advisor: Prof. Lydia E. Kavraki) Research Interests: Development of practical robotics solutions with theoretical guarantees Integration of AI techniques for real-world automation challenges Multi-robot coordination and manipulation in dynamic environments Human-centric robotics emphasizing privacy, ethics, and collaboration His publications span journals and conferences like IEEE Robotics and Automation Letters, with awards including the Best Paper Award at IEEE MRS. Shome actively serves on editorial and organizing boards for major robotics venues. Current research directions explore algorithmic foundations in stochastic decision-making, topology, and machine learning integration. Advising & Opportunities: Open PhD and research positions in robotics planning and collaborative automation Focus areas: AI-driven robotics, human-robot interaction, and perception systems

Alin Stefanescuمشاهده پروفایل

استاد

• Software Engineering
• Cybersecurity
• Artificial Intelligence
• +۳ مورد دیگر

Alin Stefanescu is a Professor and Head of the Computer Science Department at the University of Bucharest , Romania. He is also a founding member of the Institute for Logic and Data Science (ILDS) . His research focuses on software engineering, cybersecurity, and artificial intelligence, with contributions to formal methods, model-based testing, and distributed systems. Education: PhD (2006) in Computer Science, University of Stuttgart Habilitation Thesis (2017) in Formal Methods for Software Testing, University of Bucharest MSc (2000), BSc (1998) in Computer Science, University of Bucharest Research Interests: Formal verification of distributed systems Model-based testing and software quality assurance AI-driven tools for cybersecurity and testing (e.g., RobustCheck, CyberGuardian) Blockchain applications in AI and identity management Reinforcement learning for fuzz testing and automation Recent Trends in Publications: Recent work emphasizes AI integration in testing frameworks, blockchain for secure AI systems, and adaptive cybersecurity tools. He has pioneered open-source tools like RiverFuzzRL and EBLT, addressing challenges in automated testing and vulnerability analysis. Awards: Best Paper Award at ICSOFT'23 (2023) 10-Year Most Influential Paper Award (2023, for 2013 work) Best Student Paper Award (2010) Grants & Labs: Active in EU-funded projects like DYNABIC (AI techniques) and MEASURE (metrics modeling). Leads the ILDS institute, focusing on logic and data science research.

• Fault-Tolerant Computing
• Digital Circuit Design
• Embedded Systems
• +۳ مورد دیگر

Jakob Lechner is an External Lecturer in the Computer Engineering department at Vienna University of Technology. His work focuses on fault-tolerant digital circuit design, asynchronous systems, and robust hardware architectures. Education : PhD in Computer Engineering (2014), Diploma in Computer Engineering (2008) Research interests include: Fault-tolerant computing Asynchronous circuit design Transient error mitigation in FPGAs Triple Modular Redundancy (TMR) Metastability containment Single Event Transients (SET) resilience His publications (2006–2018) emphasize fault injection techniques, robust GALS circuits, and asynchronous communication protocols. Key projects include Intel CARS (2017–2019) on delay-insensitive codes. Supervision : Guided K. D. Pados' thesis on AXI4 bus systems (2013).

Eric Goubaultمشاهده پروفایل

استاد

• Formal Verification
• Concurrent and Distributed Systems
• Directed Algebraic Topology
• +۳ مورد دیگر

Eric Goubault is a Professor of Computer Science at École Polytechnique, France, where he leads the Department of Computer Science. He holds a position at the Laboratoire d'informatique (LIX), part of the UMR 7161 research unit. His research focuses on formal verification of numerical programs, concurrency theory, directed algebraic topology, and hybrid systems. Currently, he directs the 'Engineering of Complex Systems' academic and research chair alongside colleagues from ENSTA ParisTech and Télécom ParisTech, supported by industry partners like Thales and Dassault Aviation. Key roles include heading the master's program COMASIC (Conception, Modélisation et Architecture des Systèmes Industriels Complexes) and overseeing ongoing projects such as the ANR-funded Coverif, Malthy, and CAFEIN initiatives. His work bridges theoretical computer science with practical applications in embedded systems and safety-critical software validation. Research interests span geometric methods for concurrency, topological approaches to verification, and robustness analysis of numerical computations. Notable contributions include developing abstract interpretation techniques for static analysis and co-authoring the book *Directed Algebraic Topology and Concurrency* (2016). He advises multiple PhD students and collaborates on projects involving distributed computing and fault-tolerant protocols. Recent activities include organizing academic positions openings at LIX and contributing to conferences like CAV, EMSOFT, and FLOC. His publications emphasize formal methods, hybrid systems analysis, and geometric models for distributed systems.

Steve Cookمشاهده پروفایل

استاد

• Time Series Econometrics
• Numerical Simulation
• Applied Econometrics
• +۶ مورد دیگر

Professor Steve Cook serves as Head of the Economics Department at Swansea University within the School of Social Sciences, Faculty of Humanities and Social Sciences. With a distinguished career spanning several decades, he has held multiple leadership positions including Head of Economics, Head of Accounting and Finance, Director of Research, Director of Learning and Teaching, Head of School, and Deputy Dean. His extensive editorial experience includes over 50 years of service, with current positions on the editorial boards of Applied Economics and Applied Economics Letters . Professor Cook earned his DPhil in econometric modeling from the University of Oxford under Professor Sir David Hendry, followed by work at the University of Cambridge on the Macroeconomic Modeling of the Business Cycle project funded by the ESRC under Professor Sean Holly. His academic journey reflects a deep commitment to both theoretical advancement and practical application in economics and education. Professor Cook's research spans two primary domains with equal expertise. In econometrics, he focuses on Time Series Econometrics, Numerical Simulation, Applied Econometrics, and Spatial Housing Economics, making significant contributions to understanding asymmetric price adjustment in housing markets and convergence of regional house prices. In educational research, he leads innovation in pedagogical approaches, particularly in addressing the quantitative skills gap and developing effective teaching methodologies for complex econometric concepts. His dual expertise creates a unique bridge between technical econometric methodology and practical educational application, making advanced concepts accessible to students while maintaining academic rigor. His recent publications (2023-2025) reveal a strategic balance between his dual expertise areas, with approximately 60% focusing on educational challenges in higher education and 40% continuing his foundational work in econometrics. This includes research on post-COVID teaching models, internet impacts on student learning, student dissatisfaction, and innovative approaches to teaching quantitative methods. His work consistently addresses real-world educational challenges while advancing methodological understanding. HEA Principal Fellowship (one of limited number of academics worldwide holding this status) SEDA Senior Fellowship National teaching awards for innovation in economics education Extensive recognition for developing pedagogical materials and conducting educational research Professor Cook has successfully supervised numerous PhD students over two decades and secured research funding from prestigious organizations including the British Academy and Higher Education Academy. As an external examiner for undergraduate Economics at King's College London and member of the Economics Network's Board of Associates, he influences academic standards and economics education nationally. His current work focuses on bridging the quantitative skills gap through simplicity and structured replication, developing heuristic models for post-pandemic teaching, and examining the relationship between teaching contracts and student satisfaction in UK higher education. Leading initiatives that combine his expertise in both econometrics and educational methodology, Professor Cook continues to shape the future of economics education through his departmental leadership at Swansea University and contributions to the broader academic community. His current research examines post-pandemic teaching challenges, student dissatisfaction in higher education, and methods for improving quantitative literacy among economics students.

Karen Hollebrandsمشاهده پروفایل

استاد

• Mathematics Education
• Technology in Education
• Teacher Preparation
• +۳ مورد دیگر

Dr. Karen Hollebrands serves as Associate Dean for Research and Innovation in NC State's College of Education and holds the rank of Professor in the Department of STEM Education. She specializes in how technology influences student and teacher mathematical understanding. Her leadership includes roles with NCTM, AMTE, and AERA, as well as editing Mathematics Teacher Educator (2018–2022). She has secured over $10M in grants for projects like the Preparing to Teach Mathematics with Technology initiative and Noyce programs. Education: Ph.D. in Curriculum & Instruction (Penn State, 2001); M.Ed. (NC State, 1995); B.S. in Secondary Mathematics Education (SUNY Oswego, 1989). Research focuses on technology integration in mathematics education, teacher professional development, and curriculum design. Key projects include MOOCs for Educators and studies on PK-2 mathematics learning. Awards include Alumni Distinguished Undergraduate Professor (2014) and University Faculty Scholar (2015–2020). Recent grants include a $673K NSF conference on PK-2 mathematics and a $1.8M Noyce Master Teacher program. Her work emphasizes equity, technology-driven pedagogy, and cross-disciplinary collaboration.

• Computer Architecture
• Microelectronics
• Nanoscale Technology
• +۹ مورد دیگر

Dr. Paul Beckett is an Honorary Associate Professor in the School of Engineering at RMIT University. His research focuses on cutting-edge areas such as computer architecture, nanoscale microelectronics, digital logic design, and photonics. He specializes in low-power circuit design, FPGA-based systems, and sensor technologies with applications in healthcare and environmental monitoring. Beckett's teaching interests include embedded systems, VLSI design, and hardware description languages (VHDL). His research spans disciplines such as electronics, communications engineering, and distributed computing, with notable contributions to null convention logic (NCL) circuits, plasmonic sensors, and spectral imaging systems. He has collaborated on innovative projects like the TIARA apnea monitoring system and wearable health technologies. His recent work emphasizes interdisciplinary applications, including healthcare technology and biomimetic optical systems. Notable publications include advancements in gas sensing (H2S detection), THz spectrum analysis, and machine learning optimization for embedded systems. Beckett actively supervises research projects in asynchronous computing architectures and nanotechnology.

Robert Woodleyمشاهده پروفایل

عضو هیئت علمی

• Computational Intelligence
• Embedded Systems
• Digital Logic
• +۳ مورد دیگر

Dr. Robert Woodley is an Associate Teaching Professor and Advising and Recruiting Specialist in the Department of Electrical and Computer Engineering at Missouri University of Science and Technology (Missouri S&T). He joined the faculty in January 2018, bringing 14 years of industry experience including co-founding a company. His role emphasizes academic advising, course redesign, and student recruitment. He holds a PhD, MS, and BS in Electrical Engineering from Missouri S&T. Research interests include Computational Intelligence, Embedded Systems, Digital Logic, and Control Systems. He co-authored a textbook for CpE 2210 and developed an online lab for digital logic courses. Dr. Woodley restructured the CpE 2210 course into an online format during the pandemic, introduced entrepreneurial components in senior design projects, and uses Kahoot! for interactive circuits education. He serves as IEEE Rolla Subsection treasurer and has received notable awards: 2023 Dean’s Educator Award, 2022 IEEE Outstanding Educator, and 2022 Missouri S&T Faculty Achievement Award. His industry roles include Senior Scientist at Triplet Tech Corporation and 21st Century Systems, Inc.

Sylvain Senéمشاهده پروفایل

استاد

• Computer Science
• Theoretical Computer Science
• Discrete Mathematics
• +۵ مورد دیگر

Sylvain Sené is a Professor of Computer Science at Aix-Marseille University (AMU), affiliated with the Department of Computer Science and Interactions (DII) and the Computer Science and Systems Laboratory (LIS). He leads the ANR-funded project FANs (Foundations of Automata Networks) and focuses on discrete mathematics, theoretical computer science, and computational properties of automaton networks. His research bridges abstract computational models with applications in biology, particularly gene regulatory networks and cellular reprogramming. Research Interests: Automaton networks, Boolean networks, and cellular automata Computational complexity and dynamical systems Discrete mathematics and theoretical computer science Applications in systems biology and genetic networks Key Projects: Principal investigator of the ANR project FANs (2019–2023), focusing on advancing automata network theory Collaborations with CNRS, Chilean universities, and international institutions Advising & Grants: Directed PhD students including Pacôme Perrotin and Martín Ríos Wilson Secured funding through ANR and other national/international grants Labs & Teams: LIS (Computer Science and Systems Laboratory), collaborating with interdisciplinary teams in biology and mathematics.

Rajit Manoharمشاهده پروفایل

استاد

• Asynchronous VLSI Design
• Concurrency
• Formal Methods
• +۵ مورد دیگر

Rajit Manohar is the John C. Malone Professor of Electrical & Computer Engineering at Yale University, with appointments in Applied & Computational Mathematics and Computer Science. He is a core member of the interdisciplinary Computer Systems Lab (CSL), which bridges ECE and CS departments. His research focuses on asynchronous VLSI design, neuromorphic computing, and hardware-software co-design. Education: Manohar holds a B.S., M.S., and Ph.D. from the California Institute of Technology. His academic career spans over two decades, with notable contributions to asynchronous circuit theory and neuromorphic engineering. Research Interests: Manohar's work emphasizes energy-efficient asynchronous architectures, concurrency control, and biologically inspired computing. He explores topics like formal methods for circuit verification, cognitive systems, and dynamic sensor networks. His lab develops tools like Fluid (asynchronous synthesis) and Neurobench (neuromorphic benchmarking). Publications: Recent work includes advancements in asynchronous logic synthesis (Maelstrom), neuromorphic frameworks (Neurobench), and scalable brain-computer interfaces (SCALO). His research often intersects NSF-funded projects in energy-aware computing and neuromorphic systems. Awards: Inaugural Misha Mahowald Prize (2025), MIT TR35 (2000s), IBM Goldberg Award (2023) Grants & Labs: Manohar leads NSF-supported initiatives in carbon-aware networking and neuromorphic hardware. The Computer Systems Lab collaborates across disciplines to advance sustainable computing and neuro-inspired architectures.

• Algorithmic Game Theory
• Stochastic Games
• Distributed Systems
• +۴ مورد دیگر

Hugo Gimbert is a CNRS Researcher at LaBRI (Laboratoire Bordelais de Recherche en Informatique), affiliated with the University of Bordeaux, where he serves as a PhD advisor and contributes to the Formal Methods research team. His work bridges theoretical computer science with practical applications in diverse domains. His research spans Algorithmic Game Theory, Stochastic Games, Distributed Systems, and Robotics, with current focus on stochastic games with partial observation, decidability of distributed games, and applications in precision agriculture. He explores intersections with social choice theory, probabilistic logics, and humanoid robot control using Markov Decision Processes. Publications from 2010-2017 reveal consistent contributions to game theory foundations (stochastic/mean-payoff/parity games), automata theory (decidability problems, stabilization monoids), and applied robotics (vineyard trellising systems). His work demonstrates a trajectory from pure theoretical results toward real-world implementations in agriculture and education systems. Gimbert actively mentors PhD candidates including Soumyajit Paul, Simon Mauras, and Edon Kelmendi. He leads critical national projects: serving as Chargé de mission for Parcoursup (France's centralized college admission platform) since 2018, developing its core algorithms with Claire Mathieu to handle quotas, housing constraints, and transparency requirements. He also co-founded the Rhoban System spin-off applying robotic control algorithms to precision agriculture. As a core member of the Rhoban robotics project, he develops real-time image processing systems for robot soccer competitions. His software contributions include Stamina (automata theory toolkit), Marmotte (CNRS committee management system), and BipBip (ROS-based weeding robot for vineyards), demonstrating commitment to translating research into tangible societal impact.