جست‌وجوی استاد و پژوهشگر

Leslie Carrمشاهده پروفایل

استاد

• Web Science
• Research Software Engineering
• Social Media Analysis
• +۳ مورد دیگر

Professor Leslie Carr serves as Professor of Web Science at the University of Southampton's School of Electronics and Computer Science (ECS). She holds active membership in three major research entities: the Web and Internet Science group, Centre for Democratic Futures, and Web Science Institute. Her institutional profile highlights leadership in interdisciplinary projects bridging computer science, social sciences, and public policy. Her research focuses on the societal dimensions of digital technologies, with core interests in Web Science methodology, research software sustainability, and social media's role in contemporary issues. She investigates how digital platforms shape racial justice movements, public health responses, and open science practices through mixed-methods approaches combining network analysis, discourse studies, and software engineering principles. Current work examines AI integration in research workflows and democratic implications of datafication. Recent publications reveal a clear trajectory from foundational Web Science (2019) toward urgent societal applications: analyzing pandemic responses (2020-2022 mask/contact tracing studies) and advancing racial justice through digital allyship (2024). Her work consistently bridges technical and social domains, with 70% of recent articles employing Twitter data analysis to study real-world phenomena ranging from health misinformation to social movements. Scientific Recognition 6th Douglas Engelbert Best Paper Award (2001) Professor Carr actively supervises eight PhD candidates across Web Science and Computer Science programs, with current students including Peter Sturgess (iPhD Web Science) and Safiah Mohammed Alamr (PhD Computer Science). Her research is funded by major UK councils (EPSRC, ESRC, AHRC) and EU programs through projects like SSI3 and RSE Metascience. She maintains significant collaborations with Dame Wendy Hall and international partners on initiatives including the Future of Text and Academic Turing Test. Within ECS, she contributes to the Web Science Institute's mission of developing ethical frameworks for digital society. Her team operates at the intersection of software engineering and social science, maintaining strong ties with the Software Sustainability Institute and Centre for Democratic Futures to address challenges in research reproducibility and digital citizenship.

Ayşe Tosun Kühnمشاهده پروفایل

دانشیار

• Software Engineering
• Software Quality
• Defect Prediction
• +۹ مورد دیگر

Ayşe Tosun Kühn is an Associate Professor in the Department of Computer Engineering at Istanbul Technical University (ITU), where she also serves in administrative roles such as Deputy Dean and Management Board Member of the ITU Artificial Intelligence and Data Science Application and Research Center. She earned her Ph.D. in Computer Engineering from Boğaziçi University and has held academic positions at Sabancı University and the University of Oulu. Her research lies at the intersection of software engineering, empirical methods, and data science, with a focus on software quality, defect prediction, technical debt, vulnerability analysis, and test-driven development. She leads numerous funded research projects, including those supported by TÜBİTAK and industry collaborations, applying machine learning and reinforcement learning to software engineering challenges. Her recent publications reflect a strong trend in applying advanced machine learning techniques—particularly deep learning and reinforcement learning—to problems in software analytics, developer behavior modeling, and delivery optimization. She has made significant contributions to empirical studies on test-driven development, defect prediction models, and vulnerability detection in code. Her work is frequently published in high-impact journals such as IEEE Transactions on Software Engineering, Empirical Software Engineering, and Journal of Systems and Software. She has served as a guest editor and editorial board member for the Turkish Journal of Electrical Engineering and Computer Sciences , and has contributed book chapters on data science in software engineering. Her research has been cited over 1,700 times, with an h-index of 23. Scientific Awards: None explicitly mentioned. She advises several graduate students and has collaborated extensively with researchers in Turkey and internationally. She has also contributed to industry applications through projects on software measurement, defect prediction, and AI-based analytics. She is actively involved in organizing and contributing to major software engineering conferences and workshops. She is a key member of ITU’s AI and Data Science initiatives, contributing to both academic research and practical implementations in software engineering.

Dov Krugerمشاهده پروفایل

استاد آموزشی

• High Performance Computing
• Network Programming
• 3D Printing
• +۳ مورد دیگر

Dov Kruger is an Associate Teaching Professor in the Department of Electrical Engineering at Rutgers University. He holds a BE in Electrical Engineering, an MS in Computer Science, and a PhD in Ocean Engineering, all from Stevens Institute of Technology. Prior to Rutgers, he spent 10 years as a professor at Stevens. His research focuses on high-performance computing, network programming, 3D printing, and computing education. He explores re-engineering software for efficiency, distributed programming models, and innovations in data compression and secure networking. His work also encompasses underwater acoustics and sensor systems from earlier career phases. Key themes in his recent articles include real-time video processing, federated learning privacy, AI bias mitigation, and blockchain-based systems. His earlier contributions involved underwater robotics and environmental sensor networks in estuaries. Dr. Kruger seeks collaborators in FPGA, network programming, and 3D printing. He has no listed scientific awards but maintains active research in multidisciplinary computer science and engineering education.

• Human-Computer Interaction
• Virtual Reality
• Virtual Humans
• +۳ مورد دیگر

Sanobar Dar serves as a Teaching Associate (mapped to Lecturer rank) in Human-Computer Interaction at Aston University's College of Engineering and Physical Sciences, School of Engineering and Applied Science. She teaches undergraduate and postgraduate computer science modules while overseeing university and NHS ethics applications for clinical research. Her educational qualifications include: BSc in Computing Applications PTLLS in Prepare to Teach in Life-Long Sector MSc in Computer Science ILTP in Introduction to Learning and Teaching Practice PhD in Computer Science (in progress, focus: Human and Virtual Human Interaction) Dr. Dar's research centers on virtual reality applications in healthcare, specializing in virtual human coaching systems for breathing relaxation and stress reduction. She develops adaptive real-time interaction frameworks that simulate human-to-virtual-human dynamics, with emphasis on user-centered design principles to enhance clinical outcomes and patient experiences in immersive environments. Her publication portfolio demonstrates consistent innovation in VR healthcare solutions, particularly web-based adaptive systems and virtual breathing coaches. These works bridge computer science, human factors, and medical technology, revealing strong thematic focus on real-time physiological interaction and therapeutic virtual environments. She received the Demo Award for Innovative Technology in 2019 and contributes as a reviewer for journals including MDPI publications and Autonomous Agents and Multi-Agent Systems. As an educator, Dar mentors students in HCI fundamentals, prototype development, and usability testing across modules like Machine Learning, Software Engineering, and Game Development using Unity 3D, while leveraging her ethics review expertise to guide clinical research compliance.

• Neuromorphic Computing
• Spiking Neural Networks
• Bio-inspired Artificial Intelligence
• +۸ مورد دیگر

Dr James Knight is a Senior Research Fellow in Informatics at the School of Engineering and Informatics, University of Sussex. He is currently an EPSRC Research Software Engineering Fellow (2022–2026), leading research in neuromorphic computing and spiking neural networks. His work bridges computer science, neuroscience, and robotics, with a focus on bio-inspired artificial intelligence and computational modeling of insect cognition. Education: PhD in Computer Science, University of Manchester (2013–2016) MPhil in Advanced Computer Science, University of Cambridge (2012–2013) BEng in Electronic Engineering, University of Warwick (2003–2006) His research interests center on neuromorphic computing , spiking neural networks , and bio-inspired AI , particularly drawing insights from insect neuroscience to develop efficient and robust machine learning systems. He explores event-based vision, neural hardware acceleration, and computational models of insect navigation and perception. The 15 most recent publications (2024–2025) reflect a strong trend in developing and benchmarking neuromorphic algorithms, including training methods like Eventprop, hardware-software co-design (e.g., FeNN processor), and modeling biological systems such as insect central complex and mushroom bodies. These works span journals like Nature Communications , PLoS Computational Biology , and Neuromorphic Computing and Engineering , as well as IEEE and Springer conferences. Scientific Grants: Unlocking spiking neural networks for machine learning research (EPSRC, 2022–2026) – Principal Investigator ActiveAI – active learning and selective attention for robust, transparent and efficient AI (EPSRC, 2019–2022) – Research Team Member Dr Knight actively collaborates with leading researchers including Thomas Nowotny, Andrew Philippides, and Paul Graham. His work contributes to both theoretical advances in neural computation and practical applications in robotics and AI. He is involved in developing frameworks such as NeuroBench for standardized evaluation of neuromorphic systems. Laboratories and Research Teams: He is part of the neuromorphic computing and computational neuroscience research groups at the University of Sussex, contributing to interdisciplinary projects that integrate software engineering, AI, and biological modeling.

Daniel Höllerمشاهده پروفایل

پژوهشگر

• AI Planning
• Hierarchical Task Network (HTN) Planning
• Lifted Planning
• +۱۲ مورد دیگر

Daniel Höller is a researcher in the Foundations of Artificial Intelligence (FAI) Group at the Department of Computer Science, Saarland University, Germany. He joined the group in January 2020, having previously worked at the Institute of Artificial Intelligence at Ulm University from November 2013 to December 2019. He holds an M.Sc. in Computer Science from Bonn-Rhein-Sieg University, where he studied from 2007 to 2013. Ph.D., Computer Science, Ulm University M.Sc., Computer Science, Bonn-Rhein-Sieg University (2013) Daniel Höller's research lies at the intersection of theoretical and practical aspects of AI planning. His primary focus is on Hierarchical Task Network (HTN) planning, where he has made significant contributions to expressivity analysis, solver development, and the use of classical planning heuristics to guide HTN search. He also works on lifted planning, plan repair, plan recognition, and the integration of planning with deep reinforcement learning. His work often involves formal analysis, heuristic development, and the creation of practical planning systems. He is particularly interested in how planning can be made more efficient, reliable, and applicable to real-world problems, including human-aware applications. His recent publications demonstrate a consistent trend in advancing HTN planning through novel formalisms (e.g., HDDL), sophisticated solving techniques (e.g., progression search, SAT-based approaches), and the development of robust software frameworks (e.g., PANDA, TOAD, LiSAT). His work increasingly bridges planning with learning, exploring how learned models can inform planning and how planning can provide structure for learning. The subfields span formal methods, search algorithms, knowledge representation, and system building. ICAPS 2024 Best Dissertation Award for his thesis on hierarchical planning SoCS 2024 Best Student Paper Award (co-authored) Winner in 4 out of 6 tracks in the 2023 IPC HTN competition ICAPS 2018 Best Student Paper Award ICTAI 2018 Best Paper Award TCTS 2018 Best Paper Award Shortlisted for Best Paper at KI 2020 Daniel Höller has been actively involved in teaching and mentoring, having taught courses on Artificial Intelligence and AI Planning at Saarland University, and previously served as a teaching assistant for a wide range of AI and computer science courses at Ulm and Bonn-Rhein-Sieg Universities. He has received funding through his involvement in the Transregional Collaborative Research Center SFB/Transregio 62 at Ulm University. He has organized and contributed to numerous workshops and conferences, demonstrating strong service to the academic community. Daniel Höller is a core developer of the PANDA planning framework, the TOAD HTN solver, and the LiSAT system for lifted planning. These systems are state-of-the-art tools that implement his research on heuristic search, model transformation, and SAT-based compilation. His work is conducted within the FAI group at Saarland University, a leading research group in automated planning.

Murat Kuzluمشاهده پروفایل

دانشیار

• Smart Grid
• Demand Response
• Home and Building Energy Management Systems
• +۹ مورد دیگر

Murat Kuzlu is an Associate Professor at Old Dominion University's Department of Engineering Technology within the Batten College of Engineering and Technology. He received his B.Sc., M.Sc., and Ph.D. in Electronics and Telecommunications Engineering from Kocaeli University, Turkey, in 2001, 2004, and 2010, respectively. Ph.D., Electronics and Telecommunications Engineering, Kocaeli University (2010) M.Sc., Electronics and Telecommunications Engineering, Kocaeli University (2004) B.Sc., Electronics and Telecommunications Engineering, Kocaeli University (2001) His research spans Smart Grid , Demand Response , and Home/Building Energy Management Systems , with a focus on Co-simulation , Blockchain , Explainable AI , and Wireless Communication . Recent publications emphasize IoT integration, transactive energy, and cybersecurity. His scientific awards include being elected a Senior Member of IEEE . He leads the Advanced Smart System Lab for Smart City and IoT Applications , which explores technologies like 5G, RF energy harvesting, and embedded systems for grid-interactive buildings.

• Data Science
• Artificial Intelligence
• Software Engineering
• +۱۳ مورد دیگر

Prof. Venkatakrishnan Lakshminarasimhan is the Patterson Endowed Professor in the Department of Math, Computer Science, and Engineering at Elizabeth City State University, NC, USA. He has held leadership roles as Senior Professor & Consultant Director at Kalasalingam University, India, and served in executive positions in U.S.-based organizations including Srikar & Associates International Inc. and Ms. Gill LLC. He is actively engaged in research, education, and professional service across computing disciplines. His research interests span a broad spectrum of computing and engineering fields, including Data Science , Artificial Intelligence , Software Engineering , Distributed and Parallel Computing , Information Security , and Information Management and Fusion . He is particularly invested in modern pedagogical frameworks such as Project-Based Learning (PBL), mMRM, and SLP, with extensive case studies and performance evaluations. His work bridges theoretical innovation with real-world application in both industry and academia. The publications and research output of Prof. Narasimhan reflect a strong focus on applied computing, with trends indicating deep engagement in AI-driven data systems, software process optimization, and secure distributed architectures. His scholarly impact is evident through high-volume publication in top-tier journals such as IEEE Transactions and IEE Proceedings, and leadership in over 90 international conference technical panels. Award Highlights: Senior Member, IEEE and ACM Fellow, Australian Computer Society (ACS) Fellow, Institution of Engineers Australia (IEAust) Fellow, Institution of Electrical Engineers (IEE, UK) IEEE Distinguished Visitor ACM Distinguished Speaker ABET Commissioner (USA) Prof. Narasimhan has secured over US$9 million in competitive research funding and has served as technical chair for nine international conferences. He has consulted for major organizations including Boeing Aerospace and the U.S. and Australian Departments of Defense . His advisory and grant work demonstrates a strong commitment to advancing technological innovation and educational standards in computing. He is an active technical member of international standards bodies such as ISO , ANSI , and IEEE , contributing to the development of global computing standards. His interdisciplinary lab and team collaborations span academia, government, and industry, focusing on performance-driven, standards-compliant systems engineering and educational transformation.

David W. Binkleyمشاهده پروفایل

استاد

• Software Engineering and Testing
• Program Slicing and Clustering
• Information Retrieval in Software Engineering
• +۶ مورد دیگر

David W. Binkley is a Professor in the Department of Computer Science at Loyola University Maryland. His research focuses on Software Engineering and Testing Program Slicing and Clustering Information Retrieval Techniques in Software Engineering Safety-Critical Systems Code Clone Detection Recent work includes dynamic slicing of WebAssembly binaries and adaptive change recommendation systems using association rules. He has contributed extensively to empirical studies on dependence clusters, testability transformations, and observational slicing techniques. Key collaborations include institutions like Simula Research Laboratory (Norway) and NIST (National Institute of Standards and Technology). His publications span top-tier venues such as IEEE Transactions on Software Engineering, ACM TOPLAS, and ICSE.

Michele BUGLIESIمشاهده پروفایل

استاد

• Computer Security
• Web Security
• Formal Methods
• +۴ مورد دیگر

Michele Bugliesi is a Full Professor of Computer Science at Ca' Foscari University of Venice, where he is affiliated with the Department of Environmental Sciences, Computer Science and Statistics. His research spans theoretical computer science with a strong emphasis on practical security applications in web technologies and distributed systems. Professor Bugliesi's primary research interests focus on computer security, particularly web security, formal methods for security analysis, programming languages, and blockchain technologies. His work combines theoretical foundations with practical implementations, addressing critical security challenges in modern computing environments. He has made significant contributions to understanding and preventing session hijacking attacks, developing content security policies, and analyzing smart contract security. Analysis of Professor Bugliesi's recent publications (2016-2025) reveals a clear evolution in his research focus. Initially centered on web security and formal verification methods, his work has expanded to include blockchain technologies, smart contracts, and more recently, the security implications of large language models. His publications consistently appear in top-tier computer security conferences and journals, demonstrating the high quality and impact of his research. Professor Bugliesi maintains an active research group and collaborates extensively with colleagues including Stefano Calzavara, Alvise Rabitti, and Sabina Rossi. His research has practical implications for improving the security of web applications, blockchain systems, and emerging AI technologies.

Kai-Hsiung Changمشاهده پروفایل

استاد

• Software Testing
• Software Comprehension and Visualization
• Software Complexity Metrics
• +۷ مورد دیگر

Kai-Hsiung Chang is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. He has been a faculty member since 1986, progressing from Assistant to Associate Professor in 1991, and to full Professor in 1998. He served as Department Chair from 2006 to 2016 and was honored with the Alumni Professorship from 2004 to 2009. Ph.D., Electrical and Computer Engineering, University of Cincinnati, 1986 M.S., Electrical and Computer Engineering, University of Cincinnati, 1982 Diploma, Electrical Engineering, Taipei Institute of Technology, 1977 Dr. Chang's research focuses on software testing, software comprehension and visualization, complexity metrics, information assurance education, computer supported cooperative work (CSCW), and artificial intelligence in software engineering. His work integrates formal methods and usage profiles to enhance software quality and safety. He has led research sponsored by the National Science Foundation (NSF) and the Department of Defense (DoD), particularly in pervasive and mobile computing and information assurance education. His recent publications reflect a strong focus on software testing methodologies, formal specification-based validation, collaborative systems, and intelligent software tools. Themes include object-oriented testing, complexity measurement, CSCW, and AI-driven test generation, indicating a long-standing commitment to improving software reliability and development processes. Alumni Professorship, Auburn University (2004–2009) ACM Certificate of Appreciation for Outstanding Service (1997) IEEE Senior Member INFOSEC Professional Certification (2005) Multiple Outstanding Teaching Awards at Auburn University (1989, 1992, 1997) Summer Faculty Fellowship at NASA Marshall Space Flight Center (1995) Dr. Chang has advised over 50 graduate students, including numerous Ph.D. and Master’s candidates, many of whom now hold academic and industry positions. He has served on NSF and DHS fellowship review panels, contributed to ABET accreditation as a commissioner and program evaluator, and participated in the IEEE-Computer Society/ACM Curriculum Committee for Software Engineering. He also served as Vice President of the International Society of Applied Intelligence. He has led significant research initiatives, including NSF-sponsored REU programs in pervasive computing, and has been deeply involved in curriculum development and professional service. His lab and research group have focused on software quality, intelligent systems, and collaborative environments, fostering interdisciplinary work in software engineering and AI.

Aviral Kumarمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۳ مورد دیگر

Aviral Kumar is an Assistant Professor in the School of Computer Science at Carnegie Mellon University (CMU), jointly appointed in the Computer Science Department (CSD) and Machine Learning Department (MLD). He earned his PhD from UC Berkeley in 2023, where he received prestigious awards including the CV Ramamoorthy Distinguished Research Award, Apple PhD Fellowship, and Facebook PhD Fellowship. His research focuses on reinforcement learning (RL), particularly offline RL, scaling RL methods, and their intersection with foundation models. He leads the CMU AI & Reinforcement Learning (AIRe) lab, exploring core RL algorithms, robotics applications, and AI foundation models. Education: PhD in Computer Science from UC Berkeley (2023) Research Interests: Reinforcement Learning Offline Reinforcement Learning Robotics Foundation Models His lab emphasizes scalable RL techniques and real-world applications. Current advisees include Bhavya Kumar Agrawalla and Max Sobol Mark. Notable awards include the CV Ramamoorthy Distinguished Research Award for pioneering contributions to CS research. Lab activities and future work focus on advancing RL for autonomous systems and integrating foundation models into decision-making frameworks. The lab recruits PhD students annually from CMU SCS programs (CS, ML, RI). Undergraduates and MS students can apply via a dedicated form for research opportunities.

• Software Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +۴ مورد دیگر

Seung Yeob SHIN is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. He holds a PhD from the University of Massachusetts Amherst (2016), specializing in software engineering with a focus on system modeling and analysis through simulation and model checking frameworks. His work is centered at the Software Verification and Validation (V&V) Lab , led by Prof. Lionel Briand. Research Interests: Software Engineering Methodologies Cyber-Physical Systems Testing Real-Time Systems Analysis AI-Driven Testing Techniques Model Checking & Simulation Key Contributions: Pioneering work on fuzzing techniques for SDN controllers Development of probabilistic WCET estimation methods Advancements in metamorphic testing for CPS Control theory-based stress testing frameworks Publications: Over 30 peer-reviewed articles focusing on testing methodologies for real-time systems, cyber-physical systems, and quantum programming analysis. Recent trends emphasize AI integration in software validation and uncertainty-aware system design. Labs & Teams: Active member of the V&V Lab, collaborating on hardware-in-the-loop testing and embedded system validation projects.

Xavier Devroeyمشاهده پروفایل

استادیار

• Software Engineering
• Test Automation
• Search-Based Testing
• +۵ مورد دیگر

Xavier Devroey is an Assistant Professor of Software Engineering at the Faculty of Computer Science , University of Namur , where he co-leads the SNAIL Team . His research focuses on test automation for search-based and model-based software testing , test suite augmentation , DevOps , and variability-intensive systems . PhD in Computer Science (University of Namur, 2017) Master in Computer Science (University of Namur, 2010) Recent research highlights include: Automated Android safety/security audits (A3S3, 2025) REST API benchmarking infrastructure (2025) Energy consumption analysis through test execution (2025) Fuzzing approaches for Odoo integration testing (FuzzE, 2025) Scientific recognitions: 1st place Java Test Case Generation Tool Competition (2025) VAMOS 2024 Ten-Year Most Influential Paper SSBSE 2020 Best Paper Award ICST 2024 Distinguished Reviewer AST 2023 PC Reviewer Star He actively supervises PhD and master's students while organizing international conferences like ISSTA (2025) and Belgium-Netherlands Software Evolution Workshops (2024).

Peter Popovمشاهده پروفایل

پژوهشگر

• Software Reliability
• System Dependability
• Software Fault-Tolerance
• +۵ مورد دیگر

Peter Popov is a Reader at the Centre for Software Reliability (CSR) , City St George's, University of London , where he has been employed since 1997. He specializes in software dependability , fault tolerance , and stochastic modeling of critical infrastructures. Before his current position, he was an Associate Professor at the Bulgarian Academy of Sciences (1990-1997) and a Research Fellow at City St George's. Peter's academic journey began with a PhD in Computer Science from the Kiev National University of Technologies and Design (1989), following his BEng in Computer Engineering from the National Technical University of Ukraine (KPI, 1982). He has worked as a visiting scientist at renowned institutions including the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign , LAAS-CNRS in Toulouse, and Duke University . His research interests span Software reliability assessment System dependability Software fault-tolerance Performance evaluation Interdependencies of critical infrastructures He has contributed extensively to projects such as ReSIST , IRRIIS , DISPO , and AFTER , focusing on the dependability of composite systems and critical infrastructure resilience. Key publication trends reveal expertise in Stochastic modeling of autonomous vehicle safety Software diversity for fault tolerance Interdependency analysis in critical systems Bayesian reliability assessment Performance evaluation of distributed protocols Security implications in cyber-physical systems Peter has supervised several PhD students , including those researching autonomous vehicle resilience , safety assurance with ML components , and adaptable web services . His professional activities include serving on program committees for ISSRE , SAFECOMP , and EDCC conferences, as well as editorial contributions to CEUR Workshop Proceedings . He is proficient in Bulgarian , English , and Russian , with peer-review capabilities in all three languages.